Editor’s Choice Articles

Background: Preclinical cell tracking is enhanced with a multimodal imaging approach. Bioluminescence imaging (BLI) is a highly sensitive optical modality that relies on engineering cells to constitutively express a luciferase gene. Magnetic particle imaging (MPI) is a newer imaging modality that directly detects superparamagnetic iron oxide (SPIO) particles used to label cells. Here, we compare BLI and MPI for imaging cells in vitro and in vivo. Methods: Mouse 4T1 breast carcinoma cells were transduced to express firefly luciferase, labeled with SPIO (ProMag), and imaged as cell samples after subcutaneous injection into mice. Results: For cell samples, the BLI and MPI signals were strongly correlated with cell number. Both modalities presented limitations for imaging cells in vivo. For BLI, weak signal penetration, signal attenuation, and scattering prevented the detection of cells for mice with hair and for cells far from the tissue surface. For MPI, background signals obscured the detection of low cell numbers due to the limited dynamic range, and cell numbers could not be accurately quantified from in vivo images. Conclusions: It is important to understand the shortcomings of these imaging modalities to develop strategies to improve cellular detection sensitivity. Full article

Objective: To investigate the association between sarcopenia, as appraised with CT-derived muscle metrics, and cardiovascular status, as assessed via coronary CT angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS) and with pericoronary adipose tissue (pCAT) metrics. Methods: A retrospective observational study conducted on patients who underwent CCTA. The cross-sectional area (CSA) and attenuation values of the paravertebral muscles at the T8 level and the pectoralis major muscles at the T6 level were measured. The patient height was employed for the normalization of the skeletal muscle CSA. The pCAT attenuation around the coronary arteries was assessed, and the CAD severity was graded using the CAD-RADS reporting system. Regression analyses were performed to assess the impact of demographics, clinical factors, and CT variables on the CAD-RADS and pCAT. Results: A total of 220 patients were included (132 males, median age 65 years). Regression analyses showed the associations of CAD with age and sex (p < 0.001). Familiarity with CAD was related to the left anterior descending artery pCAT (p = 0.002) and circumflex artery pCAT (p = 0.018), whereas age was related to the left anterior descending artery pCAT (p = 0.032). Weak positive correlations were found between the lower muscle density and lower pCAT attenuation (ρ = 0.144–0.240, p < 0.039). Conclusions: This study demonstrated weak associations between the sarcopenia indicators and the cardiovascular risk, as assessed by the CAD severity and pCAT inflammation. However, these correlations were not strong predictors of CAD severity, as age and traditional cardiovascular risk factors overshadowed the impact of sarcopenia in the cardiovascular risk assessment. Full article

Background: The combination of oral pentoxifylline (Ptx) and vitamin E (VitE) has been used to treat radiation-induced fibrosis and soft tissue injury. Here, we review outcomes and perform a radiomic analysis of treatment effects in patients prescribed Ptx + VitE at our institution for the treatment of radiation necrosis (RN). Methods: A total of 48 patients treated with stereotactic radiosurgery (SRS) had evidence of RN and had MRI before and after starting Ptx + VitE. The radiation oncologist’s impression of the imaging in the electronic medical record was used to score response to treatment. Support Vector Machine (SVM) was used to train a model of radiomics features derived from radiation necrosis on pre- and 1st post-treatment T1 post-contrast MRIs that can classify the ultimate response to treatment with Ptx + VitE. Results: A total of 43.8% of patients showed evidence of improvement, 18.8% showed no change, and 25% showed worsening RN upon imaging after starting Ptx + VitE. The median time-to-response assessment was 3.17 months. Nine patients progressed significantly and required Bevacizumab, hyperbaric oxygen therapy, or surgery. Patients who had multiple lesions treated with SRS were less likely to show improvement (p = 0.037). A total of 34 patients were also prescribed dexamethasone, either before (7), with (16), or after starting (11) treatment. The use of dexamethasone was not associated with an improved response to Ptx + VitE (p = 0.471). Three patients stopped treatment due to side effects. Finally, we were able to develop a machine learning (SVM) model of radiomic features derived from pre- and 1st post-treatment MRIs that was able to predict the ultimate treatment response to Ptx + VitE with receiver operating characteristic (ROC) area under curve (AUC) of 0.69. Conclusions: Ptx + VitE appears safe for the treatment of RN, but randomized data are needed to assess efficacy and validate radiomic models, which may assist with prognostication. Full article

This review is focused on the current status of quantitative MRI (qMRI) of skeletal muscle. The first section covers the techniques of qMRI in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1-weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, and diffusion tensor imaging to emerging qMRI features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMRI of muscle; the intent is to demonstrate the utility of qMRI in different disease states of the muscle rather than a complete comprehensive survey. Full article

This study reviews the two most important and frequently used systems of tomography used in dentistry today. These are the dental panoramic radiograph (DPR) and cone-beam computed tomography (CBCT). The importance of the DPR has been accentuated by the recent COVID-19 pandemic, as it does not produce an aerosol. Its clinical importance is derived from its panoramic display of the jaws and associated structures and should be examined for incidental findings that may portend a potentially serious outcome. An important recent spin-off of the DPR is the extra-oral bitewing, which can replace its traditional, uncomfortable and aerosol-generating intra-oral counterpart. Although much has been written about them, this paper reviews their essential attributes and limitations in clinical dentistry. Although attempts have been made to reproduce some of the attributes of CT in CBCT such as Hounsfield Units (HU) and improve the contrast resolution of the soft tissues, these remain elusive. Nevertheless, CBCT’s dataset should be appropriately reconstructed to fully display the clinical feature prompting its prescription. In certain cases, more than one mode of reconstruction is required. Full article

The determination of death by neurological criteria (DNC) stands as a pivotal aspect of medical practice, involving a nuanced clinical diagnosis. Typically, it comes into play following a devastating brain injury, signalling the irreversible cessation of brain function, marked by the absence of consciousness, brainstem reflexes, and the ability to breathe autonomously. Accurate DNC diagnosis is paramount for adhering to the ‘Dead donor rule’, which permits organ donation solely from deceased individuals. However, complexities inherent in conducting a comprehensive DNC examination may impede reaching a definitive diagnosis. To address this challenge, ancillary testing such as computed tomography angiography (CTA) has emerged as a valuable tool. The aim of our study is to review the technique and interpretation of CTA for DNC diagnoses. CTA, a readily available imaging technique, enables visualization of the cerebral vasculature, offering insights into blood flow to the brain. While various criteria and scoring systems have been proposed, a universally accepted standard for demonstrating full brain circulatory arrest remains elusive. Nonetheless, leveraging CTA as an ancillary test in DNC assessments holds promise, facilitating organ donation and curbing healthcare costs. It is crucial to emphasize that DNC diagnosis should be exclusively entrusted to trained physicians with specialized DNC evaluation training, underscoring the importance of expertise in this intricate medical domain. Full article

Purpose: Water freely diffuses across cell membranes, making it suitable for measuring absolute tissue perfusion. In this study, we introduce an imaging method for conducting coronary artery angiography and quantifying myocardial perfusion across the entire heart using hyperpolarized water. Methods: ¹H was hyperpolarized using dissolution dynamic nuclear polarization (dDNP) with UV-generated radicals. Submillimeter resolution coronary artery images were acquired as 2D projections using a spoiled GRE (SPGRE) sequence gated on diastole. Dynamic perfusion images were obtained with a multi-slice SPGRE with diastole gating, covering the entire heart. Perfusion values were analyzed through histograms, and the most frequent estimated perfusion value (the mode of the distribution), was compared with the average values for ¹⁵O water PET from the literature. Results: A liquid state polarization of 10% at the time of the injection and a 30 s T₁ in D₂O TRIS buffer were measured. Both coronary artery and dynamic perfusion images exhibited good quality. The main and small coronary artery branches were well resolved. The most frequent estimated perfusion value is around 0.6 mL/g/min, which is lower than the average values obtained from the literature for ¹⁵O-water PET (around 1.1 and 1.5 mL/g/min). Conclusions: The study successfully demonstrated the feasibility of achieving high-resolution, motion-free coronary artery angiography and 3D whole-heart quantitative myocardial perfusion using hyperpolarized water. Full article

Ultra-high contrast (UHC) MRI describes forms of MRI in which little or no contrast is seen on conventional MRI images but very high contrast is seen with UHC techniques. One of these techniques uses the divided subtracted inversion recovery (dSIR) sequence, which, in modelling studies, can produce ten times the contrast of conventional inversion recovery (IR) sequences. When used in cases of mild traumatic brain injury (mTBI), the dSIR sequence frequently shows extensive abnormalities in white matter that appears normal when imaged with conventional T₂-fluid-attenuated IR (T₂-FLAIR) sequences. The changes are bilateral and symmetrical in white matter of the cerebral and cerebellar hemispheres. They partially spare the anterior and posterior central corpus callosum and peripheral white matter of the cerebral hemispheres and are described as the whiteout sign. In addition to mTBI, the whiteout sign has also been seen in methamphetamine use disorder and Grinker’s myelinopathy (delayed post-hypoxic leukoencephalopathy) in the absence of abnormalities on T₂-FLAIR images, and is a central component of post-insult leukoencephalopathy syndromes. This paper describes the concept of ultra-high contrast MRI, the whiteout sign, the theory underlying the use of dSIR sequences and post-insult leukoencephalopathy syndromes. Full article

In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecting and diagnosing neurodegenerative diseases. In this study, we propose a methodology to analyze functional Magnetic Resonance Imaging signals and perform classification between Parkinson’s disease patients and healthy participants using Machine Learning algorithms. In addition, the proposed approach provides insights into the brain regions affected by the disease. The functional Magnetic Resonance Imaging from the PPMI and 1000-FCP datasets were pre-processed to extract time series from 200 brain regions per participant, resulting in 11,600 features. Causal Forest and Wrapper Feature Subset Selection algorithms were used for dimensionality reduction, resulting in a subset of features based on their heterogeneity and association with the disease. We utilized Logistic Regression and XGBoost algorithms to perform PD detection, achieving 97.6% accuracy, 97.5% F₁ score, 97.9% precision, and 97.7%recall by analyzing sets with fewer than 300 features in a population including men and women. Finally, Multiple Correspondence Analysis was employed to visualize the relationships between brain regions and each group (women with Parkinson, female controls, men with Parkinson, male controls). Associations between the Unified Parkinson’s Disease Rating Scale questionnaire results and affected brain regions in different groups were also obtained to show another use case of the methodology. This work proposes a methodology to (1) classify patients and controls with Machine Learning and Causal Forest algorithm and (2) visualize associations between brain regions and groups, providing high-accuracy classification and enhanced interpretability of the correlation between specific brain regions and the disease across different groups. Full article

Objective: To determine the added value of digital breast tomosynthesis (DBT) in the assessment of lesions detected by contrast-enhanced mammography (CEM). Material and methods: A retrospective study was conducted in a tertiary university medical center. All CEM studies including DBT performed between January 2016 and December 2020 were included. Lesions were categorized and scored by four dedicated breast radiologists according to the recent CEM and DBT supplements to the Breast Imaging Reporting and Data System (BIRADS) lexicon. Changes in the BIRADS score of CEM-detected lesions with the addition of DBT were evaluated according to the pathology results and 1-year follow-up imaging study. Results: BIRADS scores of CEM-detected lesions were upgraded toward the lesion’s pathology with the addition of DBT (p > 0.0001), overall and for each reader. The difference in BIRADS scores before and after the addition of DBT was more significant for readers who were less experienced. The reason for changes in the BIRADS score was better lesion margin visibility. The main BIRADS descriptors applied in the malignant lesions were spiculations, calcifications, architectural distortion, and sharp or obscured margins. Conclusions: The addition of DBT to CEM provides valuable information on the enhancing lesion, leading to a more accurate BIRADS score. Full article

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women’s physical and mental health. Early breast cancer screening—through mammography, ultrasound, or magnetic resonance imaging (MRI)—can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI. Full article

Background: The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time–concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. Purpose: When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. Methods: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and $k^{trans}$ results were assessed. Results: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from −23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding $k^{trans}$ error was reduced from −13.5 ± 8.8% to −0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding $k^{trans}$ error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and $k^{trans}$ error (−2.4 ± 6.7%). Conclusions: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset. Full article

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 ${\mathrm{m}\mathrm{m}}^2$ with section thickness of 3.0 mm and a 2 mm³ isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm²) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland–Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm³ voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics. Full article

Background: Refractory ascites affects the prognosis and quality of life in patients with liver cirrhosis. Peritoneovenous shunt (PVS) is a treatment procedure of palliative interventional radiology for refractory ascites. Although it is reportedly associated with serious complications (e.g., heart failure, thrombotic disease), the clinical course of PVS has not been thoroughly evaluated. Objectives: To evaluate the relationship between chronological course and complications after PVS for refractory ascites in liver cirrhosis patients. Materials and Methods: This was a retrospective study of 14 patients with refractory ascites associated with decompensated cirrhosis who underwent PVS placement between June 2011 and June 2023. The clinical characteristics, changes in cardiothoracic ratio (CTR), and laboratory data (i.e., brain natriuretic peptide (BNP), D-dimer, platelet) were evaluated. Follow-up CT images in eight patients were also evaluated for ascites and complications. Results: No serious complication associated with the procedure occurred in any case. Transient increases in BNP and D-dimer levels, decreased platelet counts, and the worsening of CTR were observed in the 2 days after PVS; however, they were improved in 7 days in all cases except one. In the follow-up CT, the amount of ascites decreased in all patients, but one patient with a continuous increase in D-dimer 2 and 7 days after PVS had thrombotic disease (renal and splenic infarction). The mean PVS patency was 345.4 days, and the median survival after PVS placement was 474.4 days. Conclusions: PVS placement for refractory ascites is a technically feasible palliative therapy. The combined evaluation of chronological changes in BNP, D-dimer, platelet count and CTR, and follow-up CT images may be useful for the early prediction of the efficacy and complications of PVS. Full article

Detailed visualization of the cribriform plate is challenging due to its intricate structure. This study investigates how computed tomography (CT) with a novel photon counting (PC) detector enhance cribriform plate visualization compared to traditionally used energy-integrated detectors in patients. A total of 40 patients were included in a retrospective analysis, with half of them undergoing PC CT (Naeotom Alpha Siemens Healthineers, Forchheim, Germany) and the other half undergoing CT scans using an energy-integrated detector (Somatom Sensation 64, Siemens, Forchheim, Germany) in which the cribriform plate was visualized with a temporal bone protocol. Both groups of scans were evaluated for signal-to-noise ratio, radiation dose, the imaging quality of the whole scan overall, and, separately, the cribriform plate and the clarity of volume rendering reconstructions. Two independent observers conducted a qualitative analysis using a Likert scale. The results consistently demonstrated excellent imaging of the cribriform plate with the PC CT scanner, surpassing traditional technology. The visualization provided by PC CT allowed for precise anatomical assessment of the cribriform plate on multiplanar reconstructions and volume rendering imaging with reduced radiation dose (by approximately 50% per slice) and higher signal-to-noise ratio (by approximately 75%). In conclusion, photon-counting technology provides the possibility of better imaging of the cribriform plate in adult patients. This enhanced imaging could be utilized in skull base-associated pathologies, such as cerebrospinal fluid leaks, to visualize them more reliably for precise treatment. Full article

(1) Background: The intravoxel incoherent motion (IVIM) model can provide information about both molecular diffusion and blood flow for the evaluation of skeletal muscle inflammation. MRI-based fat quantification is advantageous for assessing fat infiltration in skeletal muscle. (2) Purpose: We aimed to quantitatively measure various parameters associated with IVIM diffusion-weighted imaging (DWI) and fat quantification in the muscles of patients with polymyositis and dermatomyositis using magnetic resonance imaging and to investigate the relationship between these parameters and electromyography (EMG) findings. (3) Material and methods: Data were retrospectively evaluated for 12 patients with polymyositis and dermatomyositis who underwent thigh MRI, including IVIM-DWI and fat quantification. The IVIM-derived parameters included the pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f). Fat fraction values were assessed using the six-point Dixon technique. Needle EMG was performed within 9 days of the MRI. (4) Results: The f values (19.02 ± 4.87%) in muscles with pathological spontaneous activity on EMG were significantly higher than those (14.60 ± 5.31) in muscles without pathological spontaneous activity (p < 0.027). There were no significant differences in D, D*, ADC, or fat fraction between muscles with and without pathologic spontaneous activity. Significant negative correlations were observed between fat fraction and amplitude (r = −0.402, p < 0.015) and between fat fraction and duration (r = −0.360, p < 0.031). (5) Conclusion: The current study demonstrates that IVIM-DWI and fat quantification using 3.0 T MRI may aid in predicting EMG findings in patients with polymyositis and dermatomyositis and promote the pathophysiological study of idiopathic inflammatory myopathies. Full article

This study investigated the efficacy of single-phase dual-energy CT (DECT) in differentiating pulmonary hamartomas from malignant lung lesions using virtual non-contrast (VNC), iodine, and fat quantification. Forty-six patients with 47 pulmonary lesions (mean age: 65.2 ± 12.1 years; hamartomas-to-malignant lesions = 22:25; male: 67%) underwent portal venous DECT using histology, PET-CT and follow-up CTs as a reference. Quantitative parameters such as VNC, fat fraction, iodine density and CT mixed values were statistically analyzed. Significant differences were found in fat fractions (hamartomas: 48.9%; malignancies: 22.9%; p ≤ 0.0001) and VNC HU values (hamartomas: −20.5 HU; malignancies: 17.8 HU; p ≤ 0.0001), with hamartomas having higher fat content and lower VNC HU values than malignancies. CT mixed values also differed significantly (p ≤ 0.0001), but iodine density showed no significant differences. ROC analysis favored the fat fraction (AUC = 96.4%; sensitivity: 100%) over the VNC, CT mixed value and iodine density for differentiation. The study concludes that the DECT-based fat fraction is superior to the single-energy CT in differentiating between incidental pulmonary hamartomas and malignant lesions, while post-contrast iodine density is ineffective for differentiation. Full article

Radiological imaging is essential for acute patient management in Intensive Care Units (ICUs); however, it introduces the risk of exposure to ionizing radiation. This review synthesizes research on radiation exposure in ICU settings, highlighting its rise during the COVID-19 pandemic and the rise in repetitive imaging. Our analysis extends to radiation safety thresholds, revealing that some ICU patients exceed the diagnostic reference level, emphasizing the need to balance diagnostic utility against potential long-term risks, such as cancer. Prospective studies have demonstrated an increase in the median cumulative effective dose in patients with trauma over time, prompting calls for improved awareness and monitoring. Moreover, innovative dose-reduction strategies and optimized protocols, especially in neuro-ICUs, promise to mitigate these risks. This review highlights the essential but risky role of radiological imaging in critical care. It advocates for rigorous radiation management protocols to safeguard patient health while ensuring the continuity of high-quality medical care. Full article

Hepatocellular carcinoma (HCC) is the principal primary liver cancer and one of the most frequent malignant tumors worldwide in patients with chronic liver disease. When diagnosed at an advanced stage, it is often associated with portal vein tumor thrombosis (PVTT), which heavily affects patients’ prognosis. Imaging evaluation is crucial in PVTT detection and staging; computed tomography and magnetic resonance are the principal diagnostic tools. Contrast-enhanced ultrasound (CEUS) is a non-invasive and easily repeatable method that can also be used in patients with impaired renal function. It represents an important means for the identification of PVTT, particularly differentiating neoplastic and non-neoplastic thrombosis through the analysis of ultrasound enhancement characteristics of the thrombosis (arterial hyperenhancement and portal washout), thus allowing more refined disease staging, appropriate treatment planning, and response evaluation, along with prognosis assessment. Full article

Background: Biliary leaks are a severe complication after pediatric liver transplantation (pLT), and successful management is challenging. Objectives: The aim of this case series was to assess the outcome of percutaneous transhepatic biliary drainage (PTBD) in children with bile leaks following pLT. The necessity of additional percutaneous bilioma drainage and laboratory changes during therapy and follow-up was documented. Material and Methods: All children who underwent PTBD for biliary leak following pLT were included in this consecutive retrospective single-center study and analyzed regarding site of leak, management of additional bilioma, treatment response, and patient and transplant survival. The courses of inflammation, cholestasis parameters, and liver enzymes were retrospectively reviewed. Results: Ten children underwent PTBD treatment for biliary leak after pLT. Seven patients presented with leakage at the hepaticojejunostomy, two with leakage at the choledocho-choledochostomy and one with a bile leak because of an overlooked segmental bile duct. In terms of the mean, the PTBD treatment started 40.3 ± 31.7 days after pLT. The mean duration of PTBD treatment was 109.7 ± 103.6 days. Additional percutaneous bilioma drainage was required in eight cases. Bile leak treatment was successful in all cases, and no complications occurred. The patient and transplant survival rate was 100%. CRP serum level, leukocyte count, gamma-glutamyl transferase (GGT), and total and direct bilirubin level decreased significantly during treatment with a very strong effect size. Additionally, the gamma-glutamyl transferase level showed a statistically significant reduction during follow-up. Conclusions: PTBD is a very successful strategy for bile leak therapy after pLT. Full article

Background: Bladder cancer is the sixth most common malignancy in the United States (US). Despite its high prevalence and the significant potential benefits of early detection, no reliable, cost-effective screening algorithm exists for asymptomatic patients at risk. Nonetheless, reports of incidentally identified early bladder cancer on CT/MRI scans performed for other indications are emerging in the literature. This represents a new opportunity for early detection, with over 80 million CT scans performed in the US yearly, 40% of which are abdominopelvic CTs. This investigation aims to define the imaging features of early bladder cancer, with the mission of facilitating early diagnosis. Methods: Following IRB approval with a waiver of informed consent, a retrospective review was performed, identifying 624 patients with non-muscle-invasive bladder cancer diagnosed at Johns Hopkins Hospital between 2000 and 2019. Of these patients, 99 patients underwent pelvic CT within the 5 years preceding pathologic diagnosis. These imaging studies were reviewed retrospectively to evaluate for the presence and features of any focal bladder wall abnormality. Results: Median age at the time of pathologic diagnosis was 70 years (range: 51–88 years), and 82% (81/99) of patients were male. A total of 226 CT studies were reviewed. The number of studies per patient ranged from 1 to 33. Median time interval between all available imaging and pathologic diagnosis was 14 months. A total of 62% (141/226) of the scans reviewed were performed for indications other than suspected urinary tract cancer (UTC). A bladder wall mass was visualized in 67% (66/99) of patients and on 35% (78/226) of scans performed before diagnosis. The majority (84%, 67/80) of masses were intraluminal. Mean transverse long- and short-axis measurements were 24 mm and 17 mm, respectively, with long dimension measurements ranging between 5 and 59 mm. Conclusions: Early bladder cancer was visualized on CT preceding pathologic diagnosis in more than 2/3 of patients, and the majority of scans were performed for indications other than suspected urinary tract cancer/UTC symptoms. These results suggest that cross-sectional imaging performed for other indications can serve as a resource for opportunistic bladder cancer screening, particularly in high-risk patients. Full article

Background. The E-MIOT (Extension-Myocardial Iron Overload in Thalassemia) project is an Italian Network assuring high-quality quantification of tissue iron overload by magnetic resonance imaging (MRI). We evaluated the impact of the COVID-19 pandemic on E-MIOT services. Methods. The activity of the E-MIOT Network MRI centers in the year 2020 was compared with that of 2019. A survey evaluated whether the availability of MRI slots for patients with hemoglobinopathies was reduced and why. Results. The total number of MRI scans was 656 in 2019 and 350 in 2020, with an overall decline of 46.4% (first MRI: 71.7%, follow-up MRI: 36.9%), a marked decline (86.9%) in the period March–June 2020, and a reduction in the gap between the two years in the period July–September. A new drop (41.4%) was recorded in the period October–December for two centers, due to the general reduction in the total amount of MRIs/day for sanitization procedures. In some centers, patients refused MRI scans for fear of getting COVID. Drops in the MRI services >80% were found for patients coming from a region without an active MRI site. Conclusions. The COVID-19 pandemic had a strong negative impact on MRI multi-organ iron quantification, with a worsening in the management of patients with hemoglobinopathies. Full article

The development of efficient biomarkers and probes for monitoring and treating cancer, specifically metastatic cancer, is a critical research area that can have a significant impact on both patient outcomes and drug discovery. In this context, TiNIR has been developed to detect tumor-initiating cells (TICs), with heme oxygenase 2 (HO2) as a promising therapeutic biomarker for tumor-initiating cells. In this study, TiNIR has demonstrated its effectiveness as an in vivo metastatic lung cancer tracker, highlighting its potential as a valuable tool in cancer research and therapy. The development of innovative approaches that selectively target metastatic cancers represents a promising avenue for improving survival rates and enhancing the quality of life of cancer patients. Full article

This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases. Full article

In breast tomosynthesis, multiple low-dose projections are acquired in a single scanning direction over a limited angular range to produce cross-sectional planes through the breast for three-dimensional imaging interpretation. We built a next-generation tomosynthesis system capable of multidirectional source motion with the intent to customize scanning motions around “suspicious findings”. Customized acquisitions can improve the image quality in areas that require increased scrutiny, such as breast cancers, architectural distortions, and dense clusters. In this paper, virtual clinical trial techniques were used to analyze whether a finding or area at high risk of masking cancers can be detected in a single low-dose projection and thus be used for motion planning. This represents a step towards customizing the subsequent low-dose projection acquisitions autonomously, guided by the first low-dose projection; we call this technique “self-steering tomosynthesis.” A U-Net was used to classify the low-dose projections into “risk classes” in simulated breasts with soft-tissue lesions; class probabilities were modified using post hoc Dirichlet calibration (DC). DC improved the multiclass segmentation (Dice = 0.43 vs. 0.28 before DC) and significantly reduced false positives (FPs) from the class of the highest risk of masking (sensitivity = 81.3% at 2 FPs per image vs. 76.0%). This simulation-based study demonstrated the feasibility of identifying suspicious areas using a single low-dose projection for self-steering tomosynthesis. Full article

Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R–R interval, matching the aim of reducing radiation dose in this increasingly used radiological examination. In this work, we analyzed how the median DLP (Dose-Length Product) values for CCTA of our Center decreased significantly in recent times mainly due to a notable change in the technology used. We passed from a median DLP value of 1158 mGy·cm to 221 mGy·cm for the whole exam and from a value of 1140 mGy·cm to 204 mGy·cm if considering CCTA scanning only. The result was obtained through the association of important factors during the dose imaging optimization: technological improvement, acquisition technique, and image reconstruction algorithm intervention. The combination of these three factors allows us to perform a faster and more accurate prospective CCTA with a lower radiation dose. Our future aim is to tune the image quality through a detectability-based study, combining algorithm strength with automatic dose settings. Full article

Although the clinical benefits of computed tomography (CT) are undoubtedly high, radiation doses received by patients are also relatively high; therefore, radiation dose management is mandatory to optimize CT radiation doses and prevent excessive radiation events. This article describes CT dose management practice at a single facility. Many imaging protocols are used in CT depending on the clinical indications, scan region, and CT scanner; thus, managing the protocols is the first step for optimization. The appropriateness of the radiation dose for each protocol and scanner is verified, while answering whether the dose is the minimum to obtain diagnostic-quality images. Moreover, examinations with exceptionally high doses are identified, and the cause and clinical validity of the high dose are assessed. Daily imaging practice should follow standardized procedures, avoiding operator-dependent errors, and information required for radiation dose management should be recorded at each examination. The imaging protocols and procedures are reviewed for continuous improvement based on regular dose analysis and multidisciplinary team collaboration. The participation of many staff members in the dose management process is expected to contribute to promoting radiation safety through increased staff awareness. Full article

Computed Tomography Urography (CTU) is a multiphase CT examination optimized for imaging kidneys, ureters, and bladder, complemented by post-contrast excretory phase imaging. Different protocols are available for contrast administration and image acquisition and timing, with different strengths and limits, mainly related to kidney enhancement, ureters distension and opacification, and radiation exposure. The availability of new reconstruction algorithms, such as iterative and deep-learning-based reconstruction has dramatically improved the image quality and reducing radiation exposure at the same time. Dual-Energy Computed Tomography also has an important role in this type of examination, with the possibility of renal stone characterization, the availability of synthetic unenhanced phases to reduce radiation dose, and the availability of iodine maps for a better interpretation of renal masses. We also describe the new artificial intelligence applications for CTU, focusing on radiomics to predict tumor grading and patients’ outcome for a personalized therapeutic approach. In this narrative review, we provide a comprehensive overview of CTU from the traditional to the newest acquisition techniques and reconstruction algorithms, and the possibility of advanced imaging interpretation to provide an up-to-date guide for radiologists who want to better comprehend this technique. Full article

Background: The accurate classification between malignant and benign breast lesions detected on mammograms is a crucial but difficult challenge for reducing false-positive recall rates and improving the efficacy of breast cancer screening. Objective: This study aims to optimize a new deep transfer learning model by implementing a novel attention mechanism in order to improve the accuracy of breast lesion classification. Methods: ResNet50 is selected as the base model to develop a new deep transfer learning model. To enhance the accuracy of breast lesion classification, we propose adding a convolutional block attention module (CBAM) to the standard ResNet50 model and optimizing a new model for this task. We assembled a large dataset with 4280 mammograms depicting suspicious soft-tissue mass-type lesions. A region of interest (ROI) is extracted from each image based on lesion center. Among them, 2480 and 1800 ROIs depict verified benign and malignant lesions, respectively. The image dataset is randomly split into two subsets with a ratio of 9:1 five times to train and test two ResNet50 models with and without using CBAM. Results: Using the area under ROC curve (AUC) as an evaluation index, the new CBAM-based ResNet50 model yields AUC = 0.866 ± 0.015, which is significantly higher than that obtained by the standard ResNet50 model (AUC = 0.772 ± 0.008) (p < 0.01). Conclusion: This study demonstrates that although deep transfer learning technology attracted broad research interest in medical-imaging informatic fields, adding a new attention mechanism to optimize deep transfer learning models for specific application tasks can play an important role in further improving model performances. Full article

Chronic obstructive pulmonary disease (COPD) and emphysema are characterized by functional and structural damage which increases the spaces for gaseous diffusion and impairs oxygen exchange. Here we explore the potential for hyperpolarized (HP) ³He MRI to characterize lung structure and function in a large-scale population-based study. Participants (n = 54) from the Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study, a nested case-control study of COPD among participants with 10+ packyears underwent HP ³He MRI measuring p_AO₂, apparent diffusion coefficient (ADC), and ventilation. HP MRI measures were compared to full-lung CT and pulmonary function testing. High ADC values (>0.4 cm²/s) correlated with emphysema and heterogeneity in p_AO₂ measurements. Strong correlations were found between the heterogeneity of global p_AO₂ as summarized by its standard deviation (SD) (p < 0.0002) and non-physiologic p_AO₂ values (p < 0.0001) with percent emphysema on CT. A regional study revealed a strong association between p_AO₂ SD and visual emphysema severity (p < 0.003) and an association with the paraseptal emphysema subtype (p < 0.04) after adjustment for demographics and smoking status. HP noble gas p_AO₂ heterogeneity and the fraction of non-physiological p_AO₂ results increase in mild to moderate COPD. Measurements of p_AO₂ are sensitive to regional emphysematous damage detected by CT and may be used to probe pulmonary emphysema subtypes. HP noble gas lung MRI provides non-invasive information about COPD severity and lung function without ionizing radiation. Full article

Background: There is growing evidence that supports the use of chest ultrasound (CUS) versus conventional chest X-ray (CXR) in order to diagnose postoperative complications. However, data regarding its use after thoracic surgery are scarce and contradictory. The aim of this study was to conduct a systematic review to evaluate the accuracy of CUS after thoracic surgery. Methods: An electronic search in MEDLINE (via PubMed), complemented by manual searches in article references, was conducted to identify eligible studies. Results: Six studies with a total of 789 patients were included in this meta-analysis. Performing CXR decreased in up to 61.6% of cases, with the main reasons for performing CXR being massive subcutaneous emphysema or complex hydrothorax. Agreement between CUS and routine-based therapeutic options was, in some studies, up to 97%. Conclusions: The selectively postoperative use of CUS may reduce the number of routinely performed CXR. However, if CUS findings are inconclusive, further radiological examinations are obligatory. Full article

Background: The aim of this study was to assess the technical feasibility and the impact on image quality and acquisition time of a deep learning-accelerated fat-saturated T2-weighted turbo spin echo sequence in musculoskeletal imaging of the extremities. Methods: Twenty-three patients who underwent MRI of the extremities were prospectively included. Standard T2w turbo inversion recovery magnitude (TIRMStd) imaging was compared to a deep learning-accelerated T2w TSE (TSEDL) sequence. Image analysis of 23 patients with a mean age of 60 years (range 30–86) was performed regarding image quality, noise, sharpness, contrast, artifacts, lesion detectability and diagnostic confidence. Pathological findings were documented measuring the maximum diameter. Results: The analysis showed a significant improvement for the T2 TSEDL with regard to image quality, noise, contrast, sharpness, lesion detectability, and diagnostic confidence, as compared to T2 TIRMStd (each p < 0.001). There were no differences in the number of detected lesions. The time of acquisition (TA) could be reduced by 52–59%. Interrater agreement was almost perfect (κ = 0.886). Conclusion: Accelerated T2 TSEDL was technically feasible and superior to conventionally applied T2 TIRMStd. Concurrently, TA could be reduced by 52–59%. Therefore, deep learning-accelerated MR imaging is a promising and applicable method in musculoskeletal imaging. Full article

Current strategies for the evaluation of patients with chest pain have significantly changed thanks to the implemented potentiality of CT and MRI. The possible fatal consequences and high malpractice costs of missed acute coronary syndromes lead to unnecessary hospital admissions every year. CT provides consistent diagnostic support, mainly in suspected coronary disease in patients with a low or intermediate pre-test risk. Moreover, it can gain information in the case of cardiac involvement in pulmonary vascular obstructive disease. MRI, on the other hand, has a leading role in the condition of myocardial damage irrespective of the underlying inflammatory or stress related etiology. This article discusses how radiology techniques (CT and MRI) can impact the diagnostic workflow of the most common cardiac and vascular pathologies that are responsible for non-traumatic chest pain admissions to the Emergency Department. Full article

The purpose of this study was to investigate if radiomic analysis based on spectral micro-CT with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte burden. High mutational load transplant soft tissue sarcomas were initiated in Rag2^+/− and Rag2^−/− mice to model varying lymphocyte burden. Mice received radiation therapy (20 Gy) to the tumor-bearing hind limb and were injected with a liposomal iodinated contrast agent. Five days later, animals underwent conventional micro-CT imaging using an energy integrating detector (EID) and spectral micro-CT imaging using a photon-counting detector (PCD). Tumor volumes and iodine uptakes were measured. The radiomic features (RF) were grouped into feature-spaces corresponding to EID, PCD, and spectral decomposition images. The RFs were ranked to reduce redundancy and increase relevance based on TL burden. A stratified repeated cross validation strategy was used to assess separation using a logistic regression classifier. Tumor iodine concentration was the only significantly different conventional tumor metric between Rag2^+/− (TLs present) and Rag2^−/− (TL-deficient) tumors. The RFs further enabled differentiation between Rag2^+/− and Rag2^−/− tumors. The PCD-derived RFs provided the highest accuracy (0.68) followed by decomposition-derived RFs (0.60) and the EID-derived RFs (0.58). Such non-invasive approaches could aid in tumor stratification for cancer therapy studies. Full article

The purpose of this retrospective study was to investigate the association between ipsilateral recurrence of ductal carcinoma in situ (DCIS) and radiomics features from DCIS and contralateral normal breast on contrast enhanced breast MR imaging. A total of 163 patients with DCIS who underwent preoperative MR imaging between January 2010 and December 2014 were included (training cohort; n = 117, validation cohort; n = 46). Radiomics features were extracted from whole tumor volume of DCIS on early dynamic T1-subtraction images and from the contralateral normal breast on precontrast T1 and early dynamic T1-subtraction images. After feature selection, a Rad-score was established by LASSO Cox regression model. Performance of Rad-score was evaluated by the receiver operating characteristic (ROC) curve and Kaplan Meier curve with log rank test. The Rad-score was significantly associated with ipsilateral recurrence free survival (RFS). The low-risk group with a low Rad-score showed higher ipsilateral RFS than the high-risk group with a high Rad-score in both training and validation cohorts (p < 0.01). The Rad-score based on radiomics features from DCIS and contralateral normal breast on breast MR imaging showed the potential for prediction of ipsilateral RFS of DCIS. Full article

Purpose: Success of clinical trials increasingly relies on effective selection of the target patient populations. We hypothesize that computational analysis of pre-accrual imaging data can be used for patient enrichment to better identify patients who can potentially benefit from investigational agents. Methods: This was tested retrospectively in soft-tissue sarcoma (STS) patients accrued into a randomized clinical trial (SARC021) that evaluated the efficacy of evofosfamide (Evo), a hypoxia activated prodrug, in combination with doxorubicin (Dox). Notably, SARC021 failed to meet its overall survival (OS) objective. We tested whether a radiomic biomarker-driven inclusion/exclusion criterion could have been used to improve the difference between the two arms (Evo + Dox vs. Dox) of the study. 164 radiomics features were extracted from 296 SARC021 patients with lung metastases, divided into training and test sets. Results: A single radiomics feature, Short Run Emphasis (SRE), was representative of a group of correlated features that were the most informative. The SRE feature value was combined into a model along with histological classification and smoking history. This model as able to identify an enriched subset (52%) of patients who had a significantly longer OS in Evo + Dox vs. Dox groups [p = 0.036, Hazard Ratio (HR) = 0.64 (0.42–0.97)]. Applying the same model and threshold value in an independent test set confirmed the significant survival difference [p = 0.016, HR = 0.42 (0.20–0.85)]. Notably, this model was best at identifying exclusion criteria for patients most likely to benefit from doxorubicin alone. Conclusions: The study presents a first of its kind clinical-radiomic approach for patient enrichment in clinical trials. We show that, had an appropriate model been used for selective patient inclusion, SARC021 trial could have met its primary survival objective for patients with metastatic STS. Full article

Non-traumatic thoracic aorta emergencies are associated with significant morbidity and mortality. Diseases of the intimomedial layers (aortic dissection and variants) have been grouped under the common term of acute aortic syndrome because they are life-threatening conditions clinically indistinguishable on presentation. Patients with aortic dissection may present with a wide variety of symptoms secondary to the pattern of dissection and end organ malperfusion. Other conditions may be seen in patients with acute symptoms, including ruptured and unstable thoracic aortic aneurysm, iatrogenic or infective pseudoaneurysms, aortic fistula, acute aortic thrombus/occlusive disease, and vasculitis. Imaging plays a pivotal role in the patient’s management and care. In the emergency room, chest X-ray is the initial imaging test offering a screening evaluation for alternative common differential diagnoses and a preliminary assessment of the mediastinal dimensions. State-of-the-art multidetector computed tomography angiography (CTA) provides a widely available, rapid, replicable, noninvasive diagnostic imaging with sensitivity approaching 100%. It is an impressive tool in decision-making process with a deep impact on treatment including endovascular or open surgical or conservative treatment. Radiologists must be familiar with the spectrum of these entities to help triage patients appropriately and efficiently. Understanding the imaging findings and proper measurement techniques allow the radiologist to suggest the most appropriate next management step. Full article

Deep learning (DL) has become a remarkably powerful tool for image processing recently. However, the usefulness of DL in positron emission tomography (PET)/computed tomography (CT) for breast cancer (BC) has been insufficiently studied. This study investigated whether a DL model using images with multiple degrees of PET maximum-intensity projection (MIP) images contributes to increase diagnostic accuracy for PET/CT image classification in BC. We retrospectively gathered 400 images of 200 BC and 200 non-BC patients for training data. For each image, we obtained PET MIP images with four different degrees (0°, 30°, 60°, 90°) and made two DL models using Xception. One DL model diagnosed BC with only 0-degree MIP and the other used four different degrees. After training phases, our DL models analyzed test data including 50 BC and 50 non-BC patients. Five radiologists interpreted these test data. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. Our 4-degree model, 0-degree model, and radiologists had a sensitivity of 96%, 82%, and 80–98% and a specificity of 80%, 88%, and 76–92%, respectively. Our 4-degree model had equal or better diagnostic performance compared with that of the radiologists (AUC = 0.936 and 0.872–0.967, p = 0.036–0.405). A DL model similar to our 4-degree model may lead to help radiologists in their diagnostic work in the future. Full article