Journal Description
Tomography
Tomography
is an international, scientific, peer-reviewed open access journal on imaging technologies published bimonthly online by MDPI (from Volume 7 Issue 1-2021).
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, MEDLINE, PMC, Embase, and other databases.
- Journal Rank: JCR - Q3 (Radiology, Nuclear Medicine & Medical Imaging) / CiteScore - Q2 (Radiology, Nuclear Medicine and Imaging)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 24.7 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2022).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Impact Factor:
3.000 (2021);
5-Year Impact Factor:
3.263 (2021)
Latest Articles
Advances in Focused Ultrasound for the Treatment of Brain Tumors
Tomography 2023, 9(3), 1094-1109; https://doi.org/10.3390/tomography9030090 - 29 May 2023
Abstract
Employing the full arsenal of therapeutics to treat brain tumors is limited by the relative impermeability of the blood–brain and blood–tumor barriers. In physiologic states, the blood–brain barrier serves a protective role by passively and actively excluding neurotoxic compounds; however, this functionality limits
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Employing the full arsenal of therapeutics to treat brain tumors is limited by the relative impermeability of the blood–brain and blood–tumor barriers. In physiologic states, the blood–brain barrier serves a protective role by passively and actively excluding neurotoxic compounds; however, this functionality limits the penetrance of therapeutics into the tumor microenvironment. Focused ultrasound technology provides a method for overcoming the blood–brain and blood–tumor barriers through ultrasound frequency to transiently permeabilize or disrupt these barriers. Concomitant delivery of therapeutics has allowed for previously impermeable agents to reach the tumor microenvironment. This review details the advances in focused ultrasound in both preclinical models and clinical studies, with a focus on its safety profile. We then turn towards future directions in focused ultrasound-mediated therapies for brain tumors.
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(This article belongs to the Special Issue Current Trends in Diagnostic and Therapeutic Imaging of Brain Tumors)
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Spontaneous Soft Tissue Hematomas in Patients with Coagulation Impairment: Safety and Efficacy of Transarterial Embolization
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Tomography 2023, 9(3), 1083-1093; https://doi.org/10.3390/tomography9030089 - 28 May 2023
Abstract
The aim of this study is to report the authors’ experience of percutaneous transarterial embolization (TAE) in patients with spontaneous soft tissue hematomas (SSTH) and active bleeding with anticoagulation impairment. The study retrospectively identified 78 patients who received a diagnosis of SSTH by
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The aim of this study is to report the authors’ experience of percutaneous transarterial embolization (TAE) in patients with spontaneous soft tissue hematomas (SSTH) and active bleeding with anticoagulation impairment. The study retrospectively identified 78 patients who received a diagnosis of SSTH by CT scan and underwent TAE between 2010 and 2019 in a single trauma center. The patients were stratified using Popov classification into categories: 2A, 2B, 2C, and 3. The patient’s 30-day survival after TAE was considered the primary outcome; immediate technical success, the need for additional TAE, and TAE-related complications were considered secondary outcomes. Immediate technical success, complication rate, and risk factors for death were analyzed. Follow-up stopped on day 30 from TAE. 27 patients (35%) fell into category 2A, 8 (10%) into category 2B, 4 (5%) into category 2C, and 39 (50%) into category 3. Immediate technical success was achieved in 77 patients (98.7%). Complications included damage at the arterial puncture site (2 patients, 2.5%) and acute kidney injury (24 patients, 31%). Only 2 patients (2.5%) had been discharged with a new diagnosis of chronic kidney disease. The 30-day overall mortality rate was 19% (15 patients). The mortality rate was higher in hemodynamically unstable patients, in Popov categories 2B, 2C, and 3, and in patients with an initial eGFR < 30 mL/min × 1.73 m2. The study demonstrated a higher mortality risk for categories 2B, 2C, and 3 compared to category 2A. Nonetheless, TAE has proven effective and safe in type 2A patients. Even though it is unclear whether type 2A patients could benefit from conservative treatment rather than TAE, in the authors’ opinion, a TAE endovascular approach should be promptly considered for all patients in ACT with active bleeding demonstrated on CT scans.
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(This article belongs to the Section Cardiovascular Imaging)
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Open AccessReview
Extended Reality in Diagnostic Imaging—A Literature Review
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Tomography 2023, 9(3), 1071-1082; https://doi.org/10.3390/tomography9030088 - 24 May 2023
Abstract
The utilization of extended reality (ER) has been increasingly explored in the medical field over the past ten years. A comprehensive analysis of scientific publications was conducted to assess the applications of ER in the field of diagnostic imaging, including ultrasound, interventional radiology,
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The utilization of extended reality (ER) has been increasingly explored in the medical field over the past ten years. A comprehensive analysis of scientific publications was conducted to assess the applications of ER in the field of diagnostic imaging, including ultrasound, interventional radiology, and computed tomography. The study also evaluated the use of ER in patient positioning and medical education. Additionally, we explored the potential of ER as a replacement for anesthesia and sedation during examinations. The use of ER technologies in medical education has received increased attention in recent years. This technology allows for a more interactive and engaging educational experience, particularly in anatomy and patient positioning, although the question may be asked: is the technology and maintenance cost worth the investment? The results of the analyzed studies suggest that implementing augmented reality in clinical practice is a positive phenomenon that expands the diagnostic capabilities of imaging studies, education, and positioning. The results suggest that ER has significant potential to improve diagnostic imaging procedures’ accuracy and efficiency and enhance the patient experience through increased visualization and understanding of medical conditions. Despite these promising advancements, further research is needed to fully realize the potential of ER in the medical field and to address the challenges and limitations associated with its integration into clinical practice.
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(This article belongs to the Topic Artificial Intelligence in Medical Imaging and Image Processing)
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Perfusion-Weighted Imaging: The Use of a Novel Perfusion Scoring Criteria to Improve the Assessment of Brain Tumor Recurrence versus Treatment Effects
Tomography 2023, 9(3), 1062-1070; https://doi.org/10.3390/tomography9030087 - 23 May 2023
Abstract
Introduction: Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)—among other advanced brain tumor imaging modalities—is a useful adjunctive
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Introduction: Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)—among other advanced brain tumor imaging modalities—is a useful adjunctive tool for distinguishing between these two entities but can be clinically unreliable, leading to the need for tissue sampling to confirm diagnosis. This may be partially because clinical PWI interpretation is non-standardized and no grading criteria are used for assessment, leading to interpretation discrepancies. This variance in the interpretation of PWI and its subsequent effect on the predictive value has not been studied. Our objective is to propose structured perfusion scoring criteria and determine their effect on the clinical value of PWI. Methods: Patients treated at a single institution between 2012 and 2022 who had prior irradiated malignant brain tumors and subsequent progression of contrast-enhancing lesions determined by PWI were retrospectively studied from CTORE (CNS Tumor Outcomes Registry at Emory). PWI was given two separate qualitative scores (high, intermediate, or low perfusion). The first (control) was assigned by a neuroradiologist in the radiology report in the course of interpretation with no additional instruction. The second (experimental) was assigned by a neuroradiologist with additional experience in brain tumor interpretation using a novel perfusion scoring rubric. The perfusion assessments were divided into three categories, each directly corresponding to the pathology-reported classification of residual tumor content. The interpretation accuracy in predicting the true tumor percentage, our primary outcome, was assessed through Chi-squared analysis, and inter-rater reliability was assessed using Cohen’s Kappa. Results: Our 55-patient cohort had a mean age of 53.5 ± 12.2 years. The percentage agreement between the two scores was 57.4% (κ: 0.271). Upon conducting the Chi-squared analysis, we found an association with the experimental group reads (p-value: 0.014) but no association with the control group reads (p-value: 0.734) in predicting tumor recurrence versus treatment effects. Conclusions: With our study, we showed that having an objective perfusion scoring rubric aids in improved PWI interpretation. Although PWI is a powerful tool for CNS lesion diagnosis, methodological radiology evaluation greatly improves the accurate assessment and characterization of tumor recurrence versus treatment effects by all neuroradiologists. Further work should focus on standardizing and validating scoring rubrics for PWI evaluation in tumor patients to improve diagnostic accuracy.
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(This article belongs to the Special Issue Current Trends in Diagnostic and Therapeutic Imaging of Brain Tumors)
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Applying a Radiation Therapy Volume Analysis Pipeline to Determine the Utility of Spectroscopic MRI-Guided Adaptive Radiation Therapy for Glioblastoma
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Tomography 2023, 9(3), 1052-1061; https://doi.org/10.3390/tomography9030086 - 21 May 2023
Abstract
Accurate radiation therapy (RT) targeting is crucial for glioblastoma treatment but may be challenging using clinical imaging alone due to the infiltrative nature of glioblastomas. Precise targeting by whole-brain spectroscopic MRI, which maps tumor metabolites including choline (Cho) and N-acetylaspartate (NAA), can quantify
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Accurate radiation therapy (RT) targeting is crucial for glioblastoma treatment but may be challenging using clinical imaging alone due to the infiltrative nature of glioblastomas. Precise targeting by whole-brain spectroscopic MRI, which maps tumor metabolites including choline (Cho) and N-acetylaspartate (NAA), can quantify early treatment-induced molecular changes that other traditional modalities cannot measure. We developed a pipeline to determine how spectroscopic MRI changes during early RT are associated with patient outcomes to provide insight into the utility of adaptive RT planning. Data were obtained from a study (NCT03137888) where glioblastoma patients received high-dose RT guided by the pre-RT Cho/NAA twice normal (Cho/NAA ≥ 2x) volume, and received spectroscopic MRI scans pre- and mid-RT. Overlap statistics between pre- and mid-RT scans were used to quantify metabolic activity changes after two weeks of RT. Log-rank tests were used to quantify the relationship between imaging metrics and patient overall and progression-free survival (OS/PFS). Patients with lower Jaccard/Dice coefficients had longer PFS (p = 0.045 for both), and patients with lower Jaccard/Dice coefficients had higher OS trending towards significance (p = 0.060 for both). Cho/NAA ≥ 2x volumes changed significantly during early RT, putting healthy tissue at risk of irradiation, and warranting further study into using adaptive RT planning.
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(This article belongs to the Special Issue Current Trends in Diagnostic and Therapeutic Imaging of Brain Tumors)
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Comparison of CT and Dixon MR Abdominal Adipose Tissue Quantification Using a Unified Computer-Assisted Software Framework
Tomography 2023, 9(3), 1041-1051; https://doi.org/10.3390/tomography9030085 - 20 May 2023
Abstract
Purpose: Reliable and objective measures of abdominal fat distribution across imaging modalities are essential for various clinical and research scenarios, such as assessing cardiometabolic disease risk due to obesity. We aimed to compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues
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Purpose: Reliable and objective measures of abdominal fat distribution across imaging modalities are essential for various clinical and research scenarios, such as assessing cardiometabolic disease risk due to obesity. We aimed to compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues in the abdomen between computed tomography (CT) and Dixon-based magnetic resonance (MR) images using a unified computer-assisted software framework. Materials and Methods: This study included 21 subjects who underwent abdominal CT and Dixon MR imaging on the same day. For each subject, two matched axial CT and fat-only MR images at the L2-L3 and the L4-L5 intervertebral levels were selected for fat quantification. For each image, an outer and an inner abdominal wall regions as well as SAT and VAT pixel masks were automatically generated by our software. The computer-generated results were then inspected and corrected by an expert reader. Results: There were excellent agreements for both abdominal wall segmentation and adipose tissue quantification between matched CT and MR images. Pearson coefficients were 0.97 for both outer and inner region segmentation, 0.99 for SAT, and 0.97 for VAT quantification. Bland–Altman analyses indicated minimum biases in all comparisons. Conclusion: We showed that abdominal adipose tissue can be reliably quantified from both CT and Dixon MR images using a unified computer-assisted software framework. This flexible framework has a simple-to-use workflow to measure SAT and VAT from both modalities to support various clinical research applications.
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(This article belongs to the Section Abdominal Imaging)
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Quantitative Assessment of Intervertebral Disc Composition by MRI: Sensitivity to Diurnal Variation
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Tomography 2023, 9(3), 1029-1040; https://doi.org/10.3390/tomography9030084 - 16 May 2023
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Whether diurnal variation exists in quantitative MRI indices such as the T1rho relaxation time (T1ρ) of the intervertebral disc (IVD) is yet to be explored. This prospective study aimed to evaluate the diurnal variation in T1ρ, apparent diffusion coefficient (ADC), and electrical conductivity
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Whether diurnal variation exists in quantitative MRI indices such as the T1rho relaxation time (T1ρ) of the intervertebral disc (IVD) is yet to be explored. This prospective study aimed to evaluate the diurnal variation in T1ρ, apparent diffusion coefficient (ADC), and electrical conductivity (σ) of lumbar IVD and its relationship with other MRI or clinical indices. Lumbar spine MRI, including T1ρ imaging, diffusion-weighted imaging (DWI), and electric properties tomography (EPT), was conducted on 17 sedentary workers twice (morning and evening) on the same day. The T1ρ, ADC, and σ of IVD were compared between the time points. Their diurnal variation, if any, was tested for correlation with age, body mass index (BMI), IVD level, Pfirrmann grade, scan interval, and diurnal variation in IVD height index. The results showed a significant decrease in T1ρ and ADC and a significant increase in the σ of IVD in the evening. T1ρ variation had a weak correlation with age and scan interval, and ADC variation with scan interval. Diurnal variation exists for the T1ρ, ADC, and σ of lumbar IVD, which should be accounted for in image interpretation. This variation is thought to be due to diurnal variations in intradiscal water, proteoglycan, and sodium ion concentration.
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Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction
Tomography 2023, 9(3), 1019-1028; https://doi.org/10.3390/tomography9030083 - 16 May 2023
Abstract
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,
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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.
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(This article belongs to the Special Issue Radiation Protection Opportunities in Medical Imaging)
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Frequency and Pattern of MRI Diffusion Restrictions after Diagnostic Catheter Neuroangiography
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Tomography 2023, 9(3), 1010-1018; https://doi.org/10.3390/tomography9030082 - 12 May 2023
Abstract
(1) Background: We investigated the frequency, location, and lesion size of diffusion restrictions (DR) in magnetic resonance imaging (MRI) of asymptomatic patients after diagnostic angiography and assessed risk factors for their occurrence. (2) Methods: We analyzed diffusion-weighted images (DWI) of 344 patients undergoing
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(1) Background: We investigated the frequency, location, and lesion size of diffusion restrictions (DR) in magnetic resonance imaging (MRI) of asymptomatic patients after diagnostic angiography and assessed risk factors for their occurrence. (2) Methods: We analyzed diffusion-weighted images (DWI) of 344 patients undergoing diagnostic angiographies in a neuroradiologic center. Only asymptomatic patients who received a magnetic resonance imaging (MRI) examination within seven days after the angiography were included. (3) Results: Asymptomatic infarcts on DWI were identified in 17% of the cases after diagnostic angiography. In these 59 patients, a total of 167 lesions were noted. The diameter of the lesions was 1–5 mm in 128 lesions, and 5–10 mm in 39 cases. Dot-shaped diffusion restrictions were found most frequently (n = 163, 97.6%). None of the patients had neurological deficits during or after angiography. Significant correlations were found between the occurrence of lesions and patient age (p < 0.001), history of atherosclerosis (p = 0.014), cerebral infarction (p = 0.026), or coronary heart disease/heart attack (p = 0.027); and the amount of contrast medium used (p = 0.047) and fluoroscopy time (p = 0.033). (4) Conclusions: With an incidence of 17%, we observed a comparatively high risk for asymptomatic cerebral ischemia after diagnostic neuroangiography. Further measures to reduce the risk of silent embolic infarcts and improve the safety of neuroangiography are warranted.
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(This article belongs to the Section Neuroimaging)
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Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging
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Tomography 2023, 9(3), 995-1009; https://doi.org/10.3390/tomography9030081 - 11 May 2023
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Abstract
Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute’s (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases
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Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute’s (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.
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(This article belongs to the Special Issue Advances in Co-clinical Quantitative Imaging Research)
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Extension of Lung Damage at Chest Computed Tomography in Severely Ill COVID-19 Patients Treated with Interleukin-6 Receptor Blockers Correlates with Inflammatory Cytokines Production and Prognosis
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Tomography 2023, 9(3), 981-994; https://doi.org/10.3390/tomography9030080 - 11 May 2023
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Elevated inflammatory markers are associated with severe coronavirus disease 2019 (COVID-19), and some patients benefit from Interleukin (IL)-6 pathway inhibitors. Different chest computed tomography (CT) scoring systems have shown a prognostic value in COVID-19, but not specifically in anti-IL-6-treated patients at high risk
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Elevated inflammatory markers are associated with severe coronavirus disease 2019 (COVID-19), and some patients benefit from Interleukin (IL)-6 pathway inhibitors. Different chest computed tomography (CT) scoring systems have shown a prognostic value in COVID-19, but not specifically in anti-IL-6-treated patients at high risk of respiratory failure. We aimed to explore the relationship between baseline CT findings and inflammatory conditions and to evaluate the prognostic value of chest CT scores and laboratory findings in COVID-19 patients specifically treated with anti-IL-6. Baseline CT lung involvement was assessed in 51 hospitalized COVID-19 patients naive to glucocorticoids and other immunosuppressants using four CT scoring systems. CT data were correlated with systemic inflammation and 30-day prognosis after anti-IL-6 treatment. All the considered CT scores showed a negative correlation with pulmonary function and a positive one with C-reactive protein (CRP), IL-6, IL-8, and Tumor Necrosis Factor α (TNF-α) serum levels. All the performed scores were prognostic factors, but the disease extension assessed by the six-lung-zone CT score (S24) was the only independently associated with intensive care unit (ICU) admission (p = 0.04). In conclusion, CT involvement correlates with laboratory inflammation markers and is an independent prognostic factor in COVID-19 patients representing a further tool to implement prognostic stratification in hospitalized patients.
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Automated Placement of Scan and Pre-Scan Volumes for Breast MRI Using a Convolutional Neural Network
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Tomography 2023, 9(3), 967-980; https://doi.org/10.3390/tomography9030079 - 10 May 2023
Abstract
Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical
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Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical with the rise in abbreviated breast MRI exams for screening purposes. This work proposes an automated approach for the placement of scan and pre-scan volumes for breast MRI. Anatomic 3-plane scout image series and associated scan volumes were retrospectively collected from 333 clinical breast exams acquired on 10 individual MRI scanners. Bilateral pre-scan volumes were also generated and reviewed in consensus by three MR physicists. A deep convolutional neural network was trained to predict both the scan and pre-scan volumes from the 3-plane scout images. The agreement between the network-predicted volumes and the clinical scan volumes or physicist-placed pre-scan volumes was evaluated using the intersection over union, the absolute distance between volume centers, and the difference in volume sizes. The scan volume model achieved a median 3D intersection over union of 0.69. The median error in scan volume location was 2.7 cm and the median size error was 2%. The median 3D intersection over union for the pre-scan placement was 0.68 with no significant difference in mean value between the left and right pre-scan volumes. The median error in the pre-scan volume location was 1.3 cm and the median size error was −2%. The average estimated uncertainty in positioning or volume size for both models ranged from 0.2 to 3.4 cm. Overall, this work demonstrates the feasibility of an automated approach for the placement of scan and pre-scan volumes based on a neural network model.
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(This article belongs to the Special Issue New Advances in Breast Imaging)
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Radiation Dose Management in Computed Tomography: Introduction to the Practice at a Single Facility
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Tomography 2023, 9(3), 955-966; https://doi.org/10.3390/tomography9030078 - 06 May 2023
Abstract
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
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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.
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(This article belongs to the Special Issue Radiation Dose Management in Computed Tomography)
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Mutant Isocitrate Dehydrogenase 1 Expression Enhances Response of Gliomas to the Histone Deacetylase Inhibitor Belinostat
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Tomography 2023, 9(3), 942-954; https://doi.org/10.3390/tomography9030077 - 04 May 2023
Abstract
Histone deacetylase inhibitors (HDACis) are drugs that target the epigenetic state of cells by modifying the compaction of chromatin through effects on histone acetylation. Gliomas often harbor a mutation of isocitrate dehydrogenase (IDH) 1 or 2 that leads to changes in their epigenetic
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Histone deacetylase inhibitors (HDACis) are drugs that target the epigenetic state of cells by modifying the compaction of chromatin through effects on histone acetylation. Gliomas often harbor a mutation of isocitrate dehydrogenase (IDH) 1 or 2 that leads to changes in their epigenetic state presenting a hypermethylator phenotype. We postulated that glioma cells with IDH mutation, due to the presence of epigenetic changes, will show increased sensitivity to HDACis. This hypothesis was tested by expressing mutant IDH1 with a point alteration—converting arginine 132 to histidine—within glioma cell lines that contain wild-type IDH1. Glioma cells engineered to express mutant IDH1 produced D-2-hydroxyglutarate as expected. When assessed for response to the pan-HDACi drug belinostat, mutant IDH1-expressing glioma cells were subjected to more potent inhibition of growth than the corresponding control cells. Increased sensitivity to belinostat correlated with the increased induction of apoptosis. Finally, a phase I trial assessing the addition of belinostat to standard-of-care therapy for newly diagnosed glioblastoma patients included one patient with a mutant IDH1 tumor. This mutant IDH1 tumor appeared to display greater sensitivity to the addition of belinostat than the other cases with wild-type IDH tumors based on both standard magnetic resonance imaging (MRI) and advanced spectroscopic MRI criteria. These data together suggest that IDH mutation status within gliomas may serve as a biomarker of response to HDACis.
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(This article belongs to the Special Issue Current Trends in Diagnostic and Therapeutic Imaging of Brain Tumors)
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Open AccessReview
The National Cancer Institute’s Co-Clinical Quantitative Imaging Research Resources for Precision Medicine in Preclinical and Clinical Settings
Tomography 2023, 9(3), 931-941; https://doi.org/10.3390/tomography9030076 - 30 Apr 2023
Abstract
Genetically engineered mouse models (GEMMs) and patient-derived xenograft mouse models (PDXs) can recapitulate important biological features of cancer. They are often part of precision medicine studies in a co-clinical setting, in which therapeutic investigations are conducted in patients and in parallel (or sequentially)
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Genetically engineered mouse models (GEMMs) and patient-derived xenograft mouse models (PDXs) can recapitulate important biological features of cancer. They are often part of precision medicine studies in a co-clinical setting, in which therapeutic investigations are conducted in patients and in parallel (or sequentially) in cohorts of GEMMs or PDXs. Employing radiology-based quantitative imaging in these studies allows in vivo assessment of disease response in real time, providing an important opportunity to bridge precision medicine from the bench to the bedside. The Co-Clinical Imaging Research Resource Program (CIRP) of the National Cancer Institute focuses on the optimization of quantitative imaging methods to improve co-clinical trials. The CIRP supports 10 different co-clinical trial projects, spanning diverse tumor types, therapeutic interventions, and imaging modalities. Each CIRP project is tasked to deliver a unique web resource to support the cancer community with the necessary methods and tools to conduct co-clinical quantitative imaging studies. This review provides an update of the CIRP web resources, network consensus, technology advances, and a perspective on the future of the CIRP. The presentations in this special issue of Tomography were contributed by the CIRP working groups, teams, and associate members.
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(This article belongs to the Special Issue Advances in Co-clinical Quantitative Imaging Research)
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Computed Tomography Urography: State of the Art and Beyond
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Tomography 2023, 9(3), 909-930; https://doi.org/10.3390/tomography9030075 - 30 Apr 2023
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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
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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.
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Can Machine Learning Be Better than Biased Readers?
Tomography 2023, 9(3), 901-908; https://doi.org/10.3390/tomography9030074 - 28 Apr 2023
Abstract
Background: Training machine learning (ML) models in medical imaging requires large amounts of labeled data. To minimize labeling workload, it is common to divide training data among multiple readers for separate annotation without consensus and then combine the labeled data for training a
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Background: Training machine learning (ML) models in medical imaging requires large amounts of labeled data. To minimize labeling workload, it is common to divide training data among multiple readers for separate annotation without consensus and then combine the labeled data for training a ML model. This can lead to a biased training dataset and poor ML algorithm prediction performance. The purpose of this study is to determine if ML algorithms can overcome biases caused by multiple readers’ labeling without consensus. Methods: This study used a publicly available chest X-ray dataset of pediatric pneumonia. As an analogy to a practical dataset without labeling consensus among multiple readers, random and systematic errors were artificially added to the dataset to generate biased data for a binary-class classification task. The Resnet18-based convolutional neural network (CNN) was used as a baseline model. A Resnet18 model with a regularization term added as a loss function was utilized to examine for improvement in the baseline model. Results: The effects of false positive labels, false negative labels, and random errors (5–25%) resulted in a loss of AUC (0–14%) when training a binary CNN classifier. The model with a regularized loss function improved the AUC (75–84%) over that of the baseline model (65–79%). Conclusion: This study indicated that it is possible for ML algorithms to overcome individual readers’ biases when consensus is not available. It is recommended to use regularized loss functions when allocating annotation tasks to multiple readers as they are easy to implement and effective in mitigating biased labels.
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(This article belongs to the Section Artificial Intelligence in Medical Imaging)
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Open AccessCase Report
COVID-19 Pneumonia with Migratory Pattern in Agammaglobulinemic Patients: A Report of Two Cases and Review of Literature
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Tomography 2023, 9(3), 894-900; https://doi.org/10.3390/tomography9030073 - 23 Apr 2023
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X-linked agammaglobulinemia (XLA) is a primary immunodeficiency characterized by marked reduction in serum immunoglobulins and early-onset infections. Coronavirus Disease-2019 (COVID-19) pneumonia in immunocompromised patients presents clinical and radiological peculiarities which have not yet been completely understood. Very few cases of agammaglobulinemic patients with
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X-linked agammaglobulinemia (XLA) is a primary immunodeficiency characterized by marked reduction in serum immunoglobulins and early-onset infections. Coronavirus Disease-2019 (COVID-19) pneumonia in immunocompromised patients presents clinical and radiological peculiarities which have not yet been completely understood. Very few cases of agammaglobulinemic patients with COVID-19 have been reported since the beginning of the pandemic in February 2020. We report two cases of migrant COVID-19 pneumonia in XLA patients.
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Open AccessArticle
The Cerebellum’s Orchestra: Understanding the Functional Connectivity of Its Lobes and Deep Nuclei in Coordination and Integration of Brain Networks
Tomography 2023, 9(2), 883-893; https://doi.org/10.3390/tomography9020072 - 21 Apr 2023
Abstract
The cerebellum, a crucial brain region, significantly contributes to various brain functions. Although it occupies a small portion of the brain, it houses nearly half of the neurons in the nervous system. Previously thought to be solely involved in motor activities, the cerebellum
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The cerebellum, a crucial brain region, significantly contributes to various brain functions. Although it occupies a small portion of the brain, it houses nearly half of the neurons in the nervous system. Previously thought to be solely involved in motor activities, the cerebellum has since been found to play a role in cognitive, sensory, and associative functions. To further elucidate the intricate neurophysiological characteristics of the cerebellum, we investigated the functional connectivity of cerebellar lobules and deep nuclei with 8 major functional brain networks in 198 healthy subjects. Our findings revealed both similarities and differences in the functional connectivity of key cerebellar lobules and nuclei. Despite robust functional connectivity among these lobules, our results demonstrated that they exhibit heterogeneous functional integration with different functional networks. For instance, lobules 4, 5, 6, and 8 were linked to sensorimotor networks, while lobules 1, 2, and 7 were associated with higher-order, non-motor, and complex functional networks. Notably, our study uncovered a lack of functional connectivity in lobule 3, strong connections between lobules 4 and 5 with the default mode networks, and connections between lobules 6 and 8 with the salience, dorsal attention, and visual networks. Additionally, we found that cerebellar nuclei, particularly the dentate cerebellar nuclei, were connected to sensorimotor, salience, language, and default-mode networks. This study provides valuable insights into the diverse functional roles of the cerebellum in cognitive processing.
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(This article belongs to the Section Neuroimaging)
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Application of Magnetic Resonance Strain Analysis Using Feature Tracking in a Myocardial Infarction Model
Tomography 2023, 9(2), 871-882; https://doi.org/10.3390/tomography9020071 - 18 Apr 2023
Abstract
This study validates the usefulness of myocardial strain analysis with cardiac cine magnetic resonance imaging (MRI) by evaluating the changes in the cardiac function and myocardial strain values longitudinally in a myocardial disease model. Six eight-week-old male Wistar rats were used as a
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This study validates the usefulness of myocardial strain analysis with cardiac cine magnetic resonance imaging (MRI) by evaluating the changes in the cardiac function and myocardial strain values longitudinally in a myocardial disease model. Six eight-week-old male Wistar rats were used as a model of myocardial infarction (MI). Cine images were taken in the short axis, two-chamber view longitudinal axis, and four-chamber view longitudinal axis directions in rats 3 and 9 days after MI and in control rats, with preclinical 7-T MRI. The control images and the images on days 3 and 9 were evaluated by measuring the ventricular ejection fraction (EF) and the strain values in the circumferential (CS), radial (RS), and longitudinal directions (LS). The CS decreased significantly 3 days after MI, but there was no difference between the images on days 3 and 9. The two-chamber view LS was −9.7 ± 2.1% at 3 days and −13.9 ± 1.4% at 9 days after MI. The four-chamber view LS was −9.9 ± 1.5% at 3 days and −11.9 ± 1.3% at 9 days after MI. Both the two- and four-chamber LS values were significantly decreased 3 days after MI. Myocardial strain analysis is, therefore, useful for assessing the pathophysiology of MI.
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(This article belongs to the Topic Cardiac Imaging: State of the Art)
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