Search Results (23)

Background: The accurate and early distinction of glioblastomas (GBMs) from single brain metastases (BMs) provides a window of opportunity for reframing treatment strategies enabling optimal and timely therapeutic interventions. We sought to leverage physiologically sensitive parameters derived from diffusion tensor imaging (DTI) and dynamic susceptibility contrast (DSC)–perfusion-weighted imaging (PWI) along with machine learning-based methods to distinguish GBMs from single BMs. Methods: Patients with histopathology-confirmed GBMs (n = 62) and BMs (n = 26) and exhibiting contrast-enhancing regions (CERs) underwent 3T anatomical imaging, DTI and DSC-PWI prior to treatment. Median values of mean diffusivity (MD), fractional anisotropy, linear, planar and spheric anisotropic coefficients, and relative cerebral blood volume (rCBV) and maximum rCBV values were measured from CERs and immediate peritumor regions. Data normalization and scaling were performed. In the next step, most relevant features were extracted (non-interacting features), which were subsequently used to generate a set of new, innovative, high-order features (interacting features) using a feature engineering method. Finally, 10 machine learning classifiers were employed in distinguishing GBMs and BMs. Cross-validation and receiver operating characteristic (ROC) curve analyses were performed to determine the diagnostic performance. Results: A random forest classifier with ANOVA F-value feature selection algorithm using both interacting and non-interacting features provided the best diagnostic performance in distinguishing GBMs from BMs with an area under the ROC curve of 92.67%, a classification accuracy of 87.8%, a sensitivity of 73.64% and a specificity of 97.5%. Conclusions: A machine learning based approach involving the combined use of interacting and non-interacting physiological MRI parameters shows promise to differentiate between GBMs and BMs with high accuracy. Full article

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10⁻⁶ mm²/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10⁻⁶ mm²/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL. Full article

Purpose: The clinical condition of a brain abscess is a potentially life-threatening disease. The combination of MRI-based imaging, surgical therapy and microbiological analysis is critical for the treatment and convalescence of the individual patient. The aim of this study was to evaluate brain tissue oxygenation measured with dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) in patients with brain abscess and its potential benefit for a better understanding of the environment in and around brain abscesses. Methods: Using a local database, 34 patients (with 45 abscesses) with brain abscesses treated between January 2013 and March 2021 were retrospectively included in this study. DSC-PWI imaging and microbiological work-up were key inclusion criteria. These data were analysed regarding a correlation between DSC-PWI and microbiological result by quantifying brain tissue oxygenation in the abscess itself, the abscess capsula and the surrounding oedema and by using six different parameters (CBF, CBV, CMRO2, COV, CTH and OEF). Results: Relative cerebral blood flow (0.335 [0.18–0.613] vs. 0.81 [0.49–1.08], p = 0.015), relative cerebral blood volume (0.44 [0.203–0.72] vs. 0.87 [0.67–1.2], p = 0.018) and regional cerebral metabolic rate for oxygen (0.37 [0.208–0.695] vs. 0.82 [0.55–1.19], p = 0.022) were significantly lower in the oedema around abscesses without microbiological evidence of a specific bacteria in comparison with microbiological positive lesions. Conclusions: The results of this study indicate a relationship between brain tissue oxygenation status in DSC-PWI and microbiological/inflammatory status. These results may help to better understand the in vivo environment of brain abscesses and support future therapeutic decisions. Full article

The 2021 WHO (World Health Organization) classification of brain tumors incorporated the rapid advances in the molecular, genetic, and pathogenesis understanding of brain tumor pathogenesis, behavior, and treatment response. It revolutionized brain tumor classification by placing great emphasis on molecular types and completely splitting adult-type and pediatric-type diffuse gliomas. Brainstem gliomas (BSGs) are the leading primary tumors of the brainstem, although they are quite uncommon in adults compared with the pediatric population, representing less than 2% of adult gliomas. Surgery is not always the treatment of choice since resection is rarely feasible and does not improve overall survival, and biopsies are not generally performed since the location is treacherous. Therefore, MRI (Magnetic Resonance Imaging) without and with gadolinium administration represents the optimal noninvasive radiological technique to suggest brainstem gliomas diagnosis, plan a multidisciplinary treatment and for follow-up evaluations. The MRI protocol encompasses morphological sequences as well as functional and advanced sequences, such as DWI/ADC (Diffusion-Weighted Imaging/Apparent Diffusion Coefficient), DTI (Diffusion Tensor Imaging), PWI (Perfusion-Weighted Imaging), and MRS (Magnetic Resonance Spectroscopy), which improve the accuracy of the diagnosis of BSGs by adding substantial information regarding the cellularity, the infiltrative behavior toward the v fiber tracts, the vascularity, and the molecular changes. Brainstem gliomas have been divided into four categories on the basis of their MRI radiological appearance, including diffuse intrinsic low-grade gliomas, enhancing malignant gliomas, localized tectal gliomas, and other forms. The aim of our review is to provide insight into the role of advanced MRI sequences in the diagnosis and follow-up of adult brainstem gliomas. Full article

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. Full article

The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-¹¹C]methionine, 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG), O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) and 6-[¹⁸F]-fluoro-3,4-dihydroxy-L-phenylalanine ([¹⁸F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP. Full article

The purpose of this study was to assess the value of perfusion-weighted imaging (PWI) in the differential diagnosis of sellar and parasellar tumors, as an additional sequence in the magnetic resonance imaging (MRI) protocol. Analysis was based on a substantial group of subjects and included 124 brain and pituitary MRI examinations with a dynamic susceptibility contrast (DSC) PWI sequence. The following perfusion parameters were determined for the tumors: relative cerebral blood volume (rCBV), relative peak height (rPH) and relative percentage of signal intensity recovery (rPSR). To ensure greater repeatability, each of the aforementioned parameters was calculated as: arithmetic mean of the values of the whole tumor, arithmetic mean of the maximum values on each axial slice within the tumor and maximum values derived from the whole tumor. In our study, we established that meningiomas compared to both non-functional and hormone-secreting pituitary adenomas (pituitary neuroendocrine tumors—PitNET) had significantly higher values of rCBV with cut-off points set at 3.45 and 3.54, respectively (mean rCBV). Additionally, meningiomas presented significantly higher maximum and mean maximum rPH values compared to adenomas. DSC PWI imaging adds significant value to conventional MRI examinations and can be helpful in differentiating equivocal pituitary tumors. Full article

The purpose of this study was to differentiate post-chemoradiotherapy (CRT) changes from tumor persistence/recurrence in early follow-up of naso-oropharyngeal carcinoma on magnetic resonance (MRI) with diffusion (DWI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI). A total of 37 patients were assessed with MRI both for tumor staging and 4-month follow-up from ending CRT. Mean apparent diffusion coefficient (ADC) values, area under the curve (AUC), and K(trans) values were calculated from DWI and DCE-PWI images, respectively. DWI and DCE-PWI values of primary tumor (ADC, AUC, K(trans)_pre), post-CRT changes (ADC, AUC, K(trans)_post), and trapezius muscle as a normative reference before and after CRT (ADC, AUC, K(trans)_muscle pre and _muscle post; AUC_{post/muscle post}:AUC_{pre/muscle pre} (AUC_{post/pre/muscle}); K(trans)_{post/muscle post}:K(trans)_{pre/muscle pre} (K(trans)_{post/pre/muscle}) were assessed. In detecting post-CRT changes, ADC_post > 1.33 × 10⁻³ mm²/s and an increase >0.72 × 10⁻³ mm²/s and/or >65.5% between ADC_post and ADC_pre values (ADC_post-pre; ADC_post-pre%) had 100% specificity, whereas hypointense signal intensity on DWIb800 images showed specificity 80%. Although mean AUC_{post/pre/muscle} and K(trans)_{post/pre/muscle} were similar both in post-CRT changes (1.10 ± 0.58; 1.08 ± 0.91) and tumor persistence/recurrence (1.09 ± 0.11; 1.03 ± 0.12), K(trans)_{post/pre/muscle} values < 0.85 and >1.20 suggested post-CRT fibrosis and inflammatory edema, respectively. In early follow-up of naso-oropharyngeal carcinoma, our sample showed that ADC_post > 1.33 × 10⁻³ mm²/s, ADC_post-pre% > 65.5%, and ADC_post-pre > 0.72 × 10⁻³ mm²/s identified post-CRT changes with 100% specificity. K(trans)_{post/pre/muscle} values less than 0.85 suggested post-CRT fibrosis, whereas K(trans)_{post/pre/muscle} values more than 1.20 indicated inflammatory edema. Full article

Perfusion imaging is preferred for identifying hypoperfusion in the management of acute ischemic stroke, but it is not always feasible/available. An alternative method for quantifying hypoperfusion, using FLAIR-hyperintense vessels (FHVs) in various vascular regions, has been proposed, with evidence of a statistical relationship with perfusion-weighted imaging (PWI) deficits and behavior. However, additional validation is needed to confirm that areas of suspected hypoperfusion (per the location of FHVs) correspond to the location of perfusion deficits in PWI. We examined the association between the location of FHVs and perfusion deficits in PWI in 101 individuals with acute ischemic stroke, prior to the receipt of reperfusion therapies. FHVs and PWI lesions were scored as present/absent in six vascular regions (i.e., the ACA, PCA, and (four sub-regions of) the MCA territories). Chi-square analyses showed a significant relationship between the two imaging techniques for five vascular regions (the relationship in the ACA territory was underpowered). These results suggest that for most areas of the brain, the general location of FHVs corresponds to hypoperfusion in those same vascular territories in PWI. In conjunction with prior work, results support the use of estimating the amount and location of hypoperfusion using FLAIR imaging when perfusion imaging is not available. Full article

Vascular-disrupting agents (VDAs) have shown a preliminary anti-cancer effect in extracranial tumors; however, the therapeutic potential of VDAs in intracranial metastatic lesions remains unclear. Simultaneous intracranial and extracranial tumors were induced by the implantation of rhabdomyosarcoma in 15 WAG/Rij rats. Pre-treatment characterizations were performed at a 3.0 T clinical magnet including a T2 relaxation map, T1 relaxation map, diffusion-weighted imaging (DWI), and perfusion-weighted imaging (PWI). Shortly afterward, a VDA was intravenously given and MRI scans at 1 h, 8 h, and 24 h after treatment were performed. In vivo findings were further confirmed by postmortem angiography and histopathology staining with H&E, Ki67, and CD31. Before VDA treatment, better perfusion (AUC30: 0.067 vs. 0.058, p < 0.05) and AUC300 value (0.193 vs. 0.063, p < 0.001) were observed in extracranial lesions, compared with intracranial lesions. After VDA treatment, more significant and persistent perfusion deficiency measured by PWI (AUC30: 0.067 vs. 0.008, p < 0.0001) and a T1 map (T1 ratio: 0.429 vs. 0.587, p < 0.05) were observed in extracranial tumors, in contrast to the intracranial tumor (AUC30: 0.058 vs. 0.049, p > 0.05, T1 ratio: 0.497 vs. 0.625, p < 0.05). Additionally, significant changes in the T2 value and apparent diffusion coefficient (ADC) value were observed in extracranial lesions, instead of intracranial lesions. Postmortem angiography and pathology showed a significantly larger H&E-stained area of necrosis (86.2% vs. 18.3%, p < 0.0001), lower CD31 level (42.7% vs. 54.3%, p < 0.05), and lower Ki67 level (12.2% vs. 32.3%, p < 0.01) in extracranial tumors, compared with intracranial lesions. The BBB functioned as a barrier against the delivery of VDA into intracranial tumors and multiparametric MRI may predict the efficacy of VDAs on craniofacial tumors. Full article

Accurate and reliable outcome predictions can help evaluate the functional recovery of ischemic stroke patients and assist in making treatment plans. Given that recovery factors may be hidden in the whole-brain features, this study aims to validate the role of dynamic radiomics features (DRFs) in the whole brain, DRFs in local ischemic lesions, and their combination in predicting functional outcomes of ischemic stroke patients. First, the DRFs in the whole brain and the DRFs in local lesions of dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) images are calculated. Second, the least absolute shrinkage and selection operator (Lasso) is used to generate four groups of DRFs, including the outstanding DRFs in the whole brain (Lasso (WB)), the outstanding DRFs in local lesions (Lasso (LL)), the combination of them (combined DRFs), and the outstanding DRFs in the combined DRFs (Lasso (combined)). Then, the performance of the four groups of DRFs is evaluated to predict the functional recovery in three months. As a result, Lasso (combined) in the four groups achieves the best AUC score of 0.971, which improves the score by 8.9% compared with Lasso (WB), and by 3.5% compared with Lasso (WB) and combined DRFs. In conclusion, the outstanding combined DRFs generated from the outstanding DRFs in the whole brain and local lesions can predict functional outcomes in ischemic stroke patients better than the single DRFs in the whole brain or local lesions. Full article

In the event of an acute ischemic stroke, saving the penumbra is the most important aspect of early treatment. The rapid and accurate identification of ischemic penumbra plays a key role in its comprehensive treatment. At present, the identification method and evaluation standard of ischemic penumbra have not been unified. Numerous pieces of software identifying ischemic penumbra have been developed, such as rapid processing of perfusion and diffusion (RAPID), Sphere, Vitrea, and computed tomography perfusion+ (CTP+). The RAPID software, analyzing and integrating multi-mode image data (mainly based on perfusion weighted imaging (PWI) or computed tomography perfusion (CTP) images, shows good performance in identifying ischemic penumbra and has been utilized for the assessment of ischemic penumbra in many ischemic stroke clinical studies, achieving good outcomes and promoting the transition from “time window” to “tissue window” in the treatment of early stage AIS. To obtain a comprehensive understanding of the RAPID software and its accuracy in evaluating ischemic penumbra, this paper reviews the background and development of the RAPID software, summarizes the published acute cerebral infarction trials using the RAPID software, generalizes the threshold parameters in different time windows, and further discusses its application and limitations. Full article

Aim: In this comprehensive review we present an update on the most relevant studies evaluating the utility of amino acid PET radiotracers for the evaluation of glioma recurrence as compared to magnetic resonance imaging (MRI). Methods: A literature search extended until June 2020 on the PubMed/MEDLINE literature database was conducted using the terms “high-grade glioma”, “glioblastoma”, “brain tumors”, “positron emission tomography”, “PET”, “amino acid PET”, “[¹¹C]methyl-l-methionine”, “[¹⁸F]fluoroethyl-tyrosine”, “[¹⁸F]fluoro-l-dihydroxy-phenylalanine”, “MET”, “FET”, “DOPA”, “magnetic resonance imaging”, “MRI”, “advanced MRI”, “magnetic resonance spectroscopy”, “perfusion-weighted imaging”, “diffusion-weighted imaging”, “MRS”, “PWI”, “DWI”, “hybrid PET/MR”, “glioma recurrence”, “pseudoprogression”, “PSP”, “treatment-related change”, and “radiation necrosis” alone and in combination. Only original articles edited in English and about humans with at least 10 patients were included. Results: Forty-four articles were finally selected. Conventional amino acid PET tracers were demonstrated to be reliable diagnostic techniques in differentiating tumor recurrence thanks to their high uptake from tumor tissue and low background in normal grey matter, giving additional and early information to standard modalities. Among them, MET–PET seems to present the highest diagnostic value but its use is limited to on-site cyclotron facilities. [¹⁸F]labelled amino acids, such as FDOPA and FET, were developed to provide a more suitable PET tracer for routine clinical applications, and demonstrated similar diagnostic performance. When compared to the gold standard MRI, amino acid PET provides complementary and comparable information to standard modalities and seems to represent an essential tool in the differentiation between tumor recurrence and other entities such as pseudoprogression, radiation necrosis, and pseudoresponse. Conclusions: Despite the introduction of new advanced imaging techniques, the diagnosis of glioma recurrence remains challenging. In this scenario, the growing knowledge about imaging techniques and analysis, such as the combined PET/MRI and the application of artificial intelligence (AI) and machine learning (ML), could represent promising tools to face this difficult and debated clinical issue. Full article

We aimed to use quantitative values derived from perfusion and diffusion-weighted MR imaging (PWI and DWI) to differentiate radiation-induced necrosis (RIN) from tumor recurrence in Glioblastoma (GBM) and investigate the best parameters for improved diagnostic accuracy and clinical decision-making. Methods: A retrospective analysis of follow-up MRI with new enhancing observations was performed in histopathologically confirmed subjects of post-treated GBM, who underwent re-surgical exploration. Quantitative estimation of rCBV (relative cerebral blood volume) from PWI and three methods of apparent diffusion coefficient (ADC) estimation were performed, namely ADC R1 (whole cross-sectional area of tumor), ADC R2 (only solid enhancing lesion), and ADC R3 (central necrosis). ROC curve and logistic regression analysis was completed. A confusion matrix table created using Excel provided the best combination parameters to ameliorate false-positive and false-negative results. Results: Forty-four subjects with a mean age of 46 years (range, 19–70 years) underwent re-surgical exploration with RIN in 28 (67%) and recurrent tumor in 16 (33%) on histopathology. rCBV threshold of >3.4 had the best diagnostic accuracy (AUC = 0.93, 81% sensitivity and 89% specificity). A multiple logistic regression model showed significant contributions from rCBV (p < 0.001) and ADC R3 (p = 0.001). After analysis of confusion matrix ADC R3 > 2032 × 10⁻⁶ mm² achieved 100% specificity with gain in sensitivity (94% vs. 56%). Conclusions: A combination of parameters had better diagnostic performance, and a stepwise combination of rCBV and ADC R3 obviated unnecessary biopsies in 10% (3/28), leading to improved clinical decision-making. Full article

Background. With fast-growing evidence in literature for clinical applications of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), this prospective study aimed at applying amide proton transfer-weighted (APTw) CEST imaging in a clinical setting to assess its diagnostic potential in differentiation of intracranial tumors at 3 tesla (T). Methods. Using the asymmetry magnetization transfer ratio (MTRasym) analysis, CEST signals were quantitatively investigated in the tumor areas and in a similar sized region of the normal-appearing white matter (NAWM) on the contralateral hemisphere of 27 patients with intracranial tumors. Area under curve (AUC) analyses were used and results were compared to perfusion-weighted imaging (PWI). Results. Using APTw CEST, contrast-enhancing tumor areas showed significantly higher APTw CEST metrics than contralateral NAWM (AUC = 0.82; p < 0.01). In subgroup analyses of each tumor entity vs. NAWM, statistically significant effects were yielded for glioblastomas (AUC = 0.96; p < 0.01) and for meningiomas (AUC = 1.0; p < 0.01) but not for lymphomas as well as metastases (p > 0.05). PWI showed results comparable to APTw CEST in glioblastoma (p < 0.01). Conclusions. This prospective study confirmed the high diagnostic potential of APTw CEST imaging in a routine clinical setting to differentiate brain tumors. Full article