Multiparametric Magnetic Resonance Imaging Research Articles

Follow-up on patients with initial negative mpMRI target and systematic biopsy for PI-RADS ≥ 3 lesions - an EAU-YAU study enhancing prostate cancer detection.

To investigate the detection and predictors of prostate cancer (PCA) and clinically significant prostate cancer (csPCA) in patients with positive multiparametric MRI (mpMRI) followed by a negative MRI - guided target biopsy (TB) and systematic biopsy (SB). This retrospective multicenter study included 694 patients from 10 tertiary referral centers with an initial positive mpMRI (PI-RADS ≥ 3) and negative results on both MRI-TB and SB. Patients were classified into three groups based on follow-up: Group 1 (prostate re-biopsy without new mpMRI), Group 2 (standardized second prostate mpMRI and subsequent re-biopsy), and Group 3 (follow-up with mpMRIs and biopsy based on clinical and radiological triggers). The primary outcomes were the detection of any PCA and csPCA during follow up. Study groups were compared according to their probability of PCA and csPCA assessed with the ERSPC-MRI risk calculator. Statistical analysis included Kaplan - Meier analysis, Cox regression, and multivariable analysis for the detection of (cs)PCa. The overall detection of PCA and csPCA was 26.8% and 19.3%, respectively, with varying rates in different PI-RADS groups. Group 3 had the highest 2-year and 5-year PCA-free survival (94 and 84%) and csPCA - free survival (96 and 86%). Multivariable analysis revealed a significantly higher risk of PCA and csPCA in Group 1 and 2 compared to Group 3 (p < 0.01). Clinical and radiological predictors for PCA and csPCA included higher age, prostate volume, PI-RADS score, the presence of atypical small acinar proliferation (ASAP), and a smaller number of TB and SB performed during the initial biopsy. Study limitations, include the retrospective design and reliance on clinical and radiological triggers for follow-up decisions. Patients with positive mpMRI but negative TB and SB results exhibit varying rates of PCA and csPCA depending on the follow up scheme. Tailored follow-up strategies are essential for optimal management in this clinical scenario.

Osmotic demyelination syndrome: revisiting the diagnostic criteria through two fatal cases

BackgroundOsmotic Demyelination Syndrome (ODS) encompasses Central Pontine Myelinolysis and Extrapontine Myelinolysis, both of which are serious neurological conditions linked to the overly rapid correction of hyponatremia. Despite growing evidence, the exact etiology of ODS remains incompletely understood. The present paper describes two case studies, aiming to provide a comprehensive overview of the pathological findings and clinical outcomes associated with ODS.Case presentationCase #1. A 74-year-old woman was admitted to the emergency department following a head trauma caused by a loss of consciousness. Initial laboratory tests revealed severe hyponatremia (sodium level of 101 mmol/L) and hypokalemia (potassium level of 2.9 mmol/L). The patient underwent corrective therapy with saline and potassium chloride. Despite the correction of electrolyte imbalances, the patient developed a hyperintense lesion in the median portion of the pons on T2-fluid-attenuated inversion recovery (FLAIR) MRI sequence 14 days post-treatment, consistent with ODS. The patient’s condition deteriorated, leading to irreversible coma and status epilepticus, culminating in death 32 days after admission. Case #2. An 81-year-old woman with a medical history of hypothyroidism, hypertension, major depression, and stage 3 chronic kidney disease presented with mild gait disturbances. Subsequent testing revealed severe hyponatremia (sodium level of 100 mmol/L). Following an initial clinical improvement due to sodium correction, the patient’s condition worsened, with symptoms progressing to confusion, lethargy, and eventually, ODS. Dermatological manifestations, including blistering lesions and facial edema, appeared as the condition advanced. The patient succumbed to irreversible coma 47 days after admission.ConclusionODS traditionally carried a poor prognosis, with high mortality rates and diagnoses often made postmortem. However, recent advances in understanding the pathophysiology, along with improvements in diagnostic techniques such as MRI and intensive care treatments, have led to earlier identification, treatment, and recognition of milder forms of the syndrome. Despite these advancements, ODS remains a critical condition with significant risks, particularly following the rapid correction of severe hyponatremia.

Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences

ObjectivesRadiomics-based analyses encompass multiple steps, leading to ambiguity regarding the optimal approaches for enhancing model performance. This study compares the effect of several feature selection methods, machine learning (ML) classifiers, and sources of radiomic features, on models’ performance for the diagnosis of clinically significant prostate cancer (csPCa) from bi-parametric MRI.MethodsTwo multi-centric datasets, with 465 and 204 patients each, were used to extract 1246 radiomic features per patient and MRI sequence. Ten feature selection methods, such as Boruta, mRMRe, ReliefF, recursive feature elimination (RFE), random forest (RF) variable importance, L1-lasso, etc., four ML classifiers, namely SVM, RF, LASSO, and boosted generalized linear model (GLM), and three sets of radiomics features, derived from T2w images, ADC maps, and their combination, were used to develop predictive models of csPCa. Their performance was evaluated in a nested cross-validation and externally, using seven performance metrics.ResultsIn total, 480 models were developed. In nested cross-validation, the best model combined Boruta with Boosted GLM (AUC = 0.71, F1 = 0.76). In external validation, the best model combined L1-lasso with boosted GLM (AUC = 0.71, F1 = 0.47). Overall, Boruta, RFE, L1-lasso, and RF variable importance were the top-performing feature selection methods, while the choice of ML classifier didn’t significantly affect the results. The ADC-derived features showed the highest discriminatory power with T2w-derived features being less informative, while their combination did not lead to improved performance.ConclusionThe choice of feature selection method and the source of radiomic features have a profound effect on the models’ performance for csPCa diagnosis.Critical relevance statementThis work may guide future radiomic research, paving the way for the development of more effective and reliable radiomic models; not only for advancing prostate cancer diagnostic strategies, but also for informing broader applications of radiomics in different medical contexts.Key PointsRadiomics is a growing field that can still be optimized.Feature selection method impacts radiomics models’ performance more than ML algorithms.Best feature selection methods: RFE, LASSO, RF, and Boruta.ADC-derived radiomic features yield more robust models compared to T2w-derived radiomic features.Graphical

Prospective Assessment of VI-RADS with Muscle Invasion in Urinary Bladder Cancer and Its Implication on Re-Resection/Restaging TURBT Patients.

Bladder cancer (BCa) diagnosis relies on distinguishing muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC) forms. Transurethral resection of the bladder tumor (TURBT) is a standard procedure for initial staging and treatment. The Vesical Imaging-Reporting and Data System (VI-RADS) enhances diagnostic accuracy for muscle invasiveness through advanced imaging techniques, potentially reducing reliance on repeat TURBT and improving patient management. We aimed to evaluate the role of VI-RADS in predicting muscle invasiveness in BCa and its potential to predict adverse pathology in high-risk NMIBC to avoid unnecessary repeat TURBT procedures. In this prospective study, we included 62 patients over the age of 18years who underwent TURBT. In a secondary phase, patients selected for restaging TURBT (re-TURBT) were included, but those with T2 tumors or low-risk NMIBC were excluded. Multiparametric magnetic resonance imaging (MRI) examinations were scored by a radiologist using the VI-RADS 5 method, while a pathologist analyzed TURBT and re-TURBT samples for accurate staging. Statistical analysis evaluated the role of VI-RADS in BCa staging. The VI-RADS score was the only predictive factor for muscle invasion in multivariate analysis. Setting the VI-RADS score at >3 resulted in the highest sensitivity, specificity, and diagnostic accuracy, with values of 67.0%, 89.0%, and 78%, respectively. The receiver operating characteristic area under the curve score for VI-RADS for muscle invasion was 85% for stage Ta, 61% for stage T1, and 88% for stage T2, which shows the utility of VI-RADS in the predictiveness of MIBC/NMIBC. VI-RADS is effective in stratifying BCa patients by predicting muscle invasiveness and identifying NMIBC cases that may not need repeat TURBT.

Predicting cancer detection rates from multiparametric prostate MRI: Beyond the PI-RADS classification system.

Although the Prostate Imaging-Reporting and Data System (PI RADS) categorization represents the standard method for assessing the risk of prostate cancer using prostate magnetic resonance imaging (MRI), there exists wide variation in cancer detection rates (CDRs) in real-world practice. We therefore evaluated the association of clinical and radiographic features with CDRs and developed a predictive model to improve clinical management. We identified men aged 18-89 years with elevated prostate-specfic antigen (PSA) or on active surveillance for prostate cancer who underwent MRI-ultrasound (US) fusion biopsy or in-bore MRI-targeted biopsy. The associations of features with the per-lesion CDR (Gleason 6- 10) and clinically significant (cs) CDR (Gleason 7-10) were examined using logistic regression, and results were operationalized into a predictive model. Targeted biopsy was performed for 347 lesions in 281 patients. Overall, the CDR was 49.0% and the csCDR was 28.0%. On multivariable analysis, increasing PI-RADS category, no prior prostate biopsies, smaller prostate size, and increasing PSA density were independently associated with higher CDR, while 0-1 prior prostate biopsies, and a solitary PI-RADS 3-5 lesion were associated with higher csCDR. A predictive model provided a greater net benefit than a strategy of performing biopsy in all PI-RADS 3-5 lesions across a wide range of threshold probabilities. Several clinical and radiographic features are independently associated with the risk of prostate cancer in men undergoing MRI-targeted biopsy. A predictive model based on these features can improve clinical decisions regarding biopsy compared to the conventional strategy of performing biopsy for all PI-RADS 3-5 lesions.

Development of quantitative PET/MR imaging for measurements of hepatic portal vein input function: a phantom study

BackgroundAccurate pharmacokinetic modelling in PET necessitates measurements of an input function, which ideally is acquired non-invasively from image data. For hepatic pharmacokinetic modelling two input functions need to be considered, to account for the blood supply from the hepatic artery and portal vein. Image-derived measurements at the portal vein are challenging due to its small size and image artifacts caused by respiratory motion. In this work we seek to demonstrate, using phantom experiments, how a dedicated PET/MR protocol can tackle these challenges and potentially provide input function measurements of the portal vein in a clinical setup.MethodsA custom 3D printed PET/MR phantom was constructed to mimic the liver and portal vein. PET/MR acquisitions were made with emulated respiratory motion. The PET/MR imaging protocol consisted of high-resolution anatomical MR imaging of the portal vein, followed by a PET acquisition in parallel to a dedicated motion-tracking MR sequence. Motion tracking and deformation information were extracted from PET data and subsequently used in PET reconstruction to produce dynamic series of motion-free PET images. Anatomical MR images were used post PET reconstruction for partial volume correction of the input function measurements.ResultsReconstruction of dynamic PET data with motion-compensation provided nearly motion-free series of PET frame data, suitable for image derived input function measurements of the portal vein. After partial volume correction, the individual input function measurements were within a 16.1% error range from the true activity in the portal vein compartment at the time of PET acquisition.ConclusionThe proposed protocol demonstrates clinically feasible PET/MR imaging of the liver for pharmacokinetic studies with accurate quantification of the portal vein input function, including correction for respiratory motion and partial volume effects.

Aggressive bone tumours: What a radiologist can offer to the surgeon?

The complexity of aggressive bone tumours necessitates a comprehensive approach that combines radiological assessments with clinical and pathological findings. Radiologists offer valuable insights to surgeons throughout the diagnostic and therapeutic journey, enhancing the precision and efficacy of surgical interventions. Radiologists contribute to definitive diagnosis in the majority of benign and certain aggressive tumours, although the complexity of aggressive bone tumours often requires histopathological confirmation. They assist in characterizing tumours and evaluating their extension, providing critical information for treatment planning. Radiologists guide biopsy procedures, ensuring representative tissue samples while minimizing morbidity and the risk of tumour spread. In preoperative planning, radiologists construct detailed 3D reconstructions of tumours, aiding surgeons in strategizing surgical approaches and anticipating challenges. During surgery, radiologists offer intraoperative guidance through techniques like image fusion and intraoperative MRI, enhancing surgical precision. Post-surgical surveillance for tumour recurrence heavily relies on radiological imaging, with functional MR sequences providing valuable insights. Radiologists also play a significant role in image-guided therapeutic interventions for aggressive bone tumours, offering procedures like osteoplasty and ablation techniques for pain relief and tumour control. In conclusion, radiologists are indispensable members of the multidisciplinary team and offer expertise in diagnosis, biopsy guidance, preoperative planning, intraoperative guidance, post-surgical surveillance, and interventional therapy. Their collaborative efforts significantly optimize patient's outcome and quality of life.

Correlation of Prostate High-Resolution Micro-Ultrasound with Multiparametric Magnetic Resonance Imaging

ObjectiveTo assess the correlation between high-resolution micro-ultrasound (microUS) and multiparametric magnetic resonance imaging (MP-MRI) in clinically significant prostate cancer (csPCa) lesion identification. MethodsWe reviewed our prospectively maintained database of 267 consecutive patients who underwent MP-MRI and transperineal microUS-guided biopsy between February 2021 and April 2023. The Prostate Risk Identification using MicroUS (PRI-MUS) protocol was utilized to risk stratify prostate lesions, with PRI-MUS 3-5 defined as positive. MRI lesions were classified according to the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Clinicopathologic outcomes were analyzed. Spearman correlation testing was computed to assess the relationship between PRI-MUS and PI-RADS. ResultsA total of 161 patients met inclusion criteria. Mean ± standard deviation (SD) age was 65.6 ± 1.5 years and PSA was 7.6 ± 0.6 ng/mL. Ninety-two patients were found to have PIRADS 3-5 lesions. Spearman correlation analysis revealed a moderate positive correlation between PRI-MUS and PI-RADS (r = 0.40, P < 0.001). MicroUS-targeted cores detected higher grade disease than systematic and MRI-targeted cores in 8/161 (5.0%) patients. CsPCa would have been missed in 4/161 (2.5%) patients without microUS-targeted sampling. ConclusionsMicroUS/PRI-MUS demonstrates moderate positive correlation with MP-MRI/PI-RADS and offers improved csPCa detection compared to MRI-targeted biopsy alone. MicroUS may be useful in conjunction with MP-MRI or as an alternative imaging modality in MRI-ineligible patients.

A Histopathologic Correlation Study Evaluating Glymphatic Function in Brain Tumors by Multiparametric MRI.

This study aimed to elucidate the impact of brain tumors on cerebral edema and glymphatic drainage by leveraging advanced MRI techniques to explore the relationships among tumor characteristics, glymphatic function, and aquaporin-4 (AQP4) expression levels. In a prospective cohort from March 2022 to April 2023, patients with glioblastoma, brain metastases, and aggressive meningiomas, alongside age- and sex-matched healthy controls, underwent 3.0T MRI, including diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index and multiparametric MRI for quantitative brain mapping. Tumor and peritumor tissues were analyzed for AQP4 expression levels via immunofluorescence. Correlations among MRI parameters, glymphatic function (DTI-ALPS index), and AQP4 expression levels were statistically assessed. Among 84 patients (mean age: 55 ± 12 years; 38 males) and 59 controls (mean age: 54 ± 8 years; 23 males), patients with brain tumor exhibited significantly reduced glymphatic function (DTI-ALPS index: 2.315 vs. 2.879; P = 0.001) and increased cerebrospinal fluid volume (201.376 cm³ vs. 115.957 cm³; P = 0.001). A negative correlation was observed between tumor volume and the DTI-ALPS index (r: -0.715, P < 0.001), whereas AQP4 expression levels correlated positively with peritumoral brain edema volume (r: 0.989, P < 0.001) and negatively with proton density in peritumoral brain edema areas (ρ: -0.506, P < 0.001). Our findings highlight the interplay among tumor-induced compression, glymphatic dysfunction, and altered fluid dynamics, demonstrating the utility of DTI-ALPS and multiparametric MRI in understanding the pathophysiology of tumor-related cerebral edema. These insights provide a radiological foundation for further neuro-oncological investigations into the glymphatic system. See related commentary by Surov and Borggrefe, p. 4813.

Classification of Multi-Parametric Body MRI Series Using Deep Learning.

Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrect information due to the sheer diversity of protocols and occasional technologist errors. To address this, we present a deep learning-based classification model to classify 8 different body mpMRI series types so that radiologists read the exams efficiently. Using mpMRI data from various institutions, multiple deep learning-based classifiers of ResNet, EfficientNet, and DenseNet are trained to classify 8 different MRI series, and their performance is compared. Then, the best-performing classifier is identified, and its classification capability under the setting of different training data quantities is studied. Also, the model is evaluated on the out-of-training-distribution datasets. Moreover, the model is trained using mpMRI exams obtained from different scanners in two training strategies, and its performance is tested. Experimental results show that the DenseNet-121 model achieves the highest F1-score and accuracy of 0.966 and 0.972 over the other classification models with p-value 0.05. The model shows greater than 0.95 accuracy when trained with over 729 studies of the training data, whose performance improves as the training data quantities grow larger. On the external data with the DLDS and CPTAC-UCEC datasets, the model yields 0.872 and 0.810 accuracy for each. These results indicate that in both the internal and external datasets, the DenseNet-121 model attains high accuracy for the task of classifying 8 body MRI series types.

Optimizing Multiparametric MRI Protocols for Prostate Cancer Detection: A Comprehensive Assessment Aligned with PI-RADS Guidelines.

Multiparametric magnetic resonance imaging (mpMRI) is recognized as the most indicative method for diagnosing prostate cancer. The purpose of this narrative review is to provide a comprehensive evaluation aligned with the Prostate Imaging and Reporting Data System (PI-RADS) guidelines, offering an in-depth insight into the various MRI sequences used in a standard mpMRI protocol. Additionally, it outlines the critical technical requirements necessary to perform a standard mpMRI examination of the prostate, as defined by the PI-RADS specifications. European Society of Urogenital Radiology has released PI-RADS guideline detailing its suggestions aimed at improving the standards of the procedure. The purpose of this guideline is to establish a standard strategy for MRI protocols and image interpretation, aiming to prevent variability in each of the imaging and interpretation stages. A standard mpMRI protocol comprises morphological sequences and functional sequences. Morphological sequences which encompass T1- and T2-weighted images, and various functional sequences include diffusion-weighted imaging, and dynamic contrast-enhanced MRI. The PI-RADS recommendations assert that having a standard and uniform protocol for all MRI centers is imperative. Furthermore, the existence of a standardized checklist for interpreting MRI images can foster greater consensus in the process of diagnosing and treating patients. Standardized protocols and checklists for mpMRI interpretation are essential for achieving greater consensus among radiologists, ultimately leading to improved diagnostic outcomes in prostate cancer.

The Value of Second-look Ultrasound and Mammography for Assessment and Biopsy of MRI-detected Breast Lesions

Rationale and ObjectivesSuspicious lesions detected in multiparametric breast MRI can be further analyzed with second-look ultrasound (SLUS) and/or mammography. This study aims to assess the value of second-look imaging in selecting the appropriate biopsy method for different lesion characteristics. Materials and MethodsBetween January 2021 and December 2023, 212 women underwent contrast-enhanced multiparametric breast MRI at 3.0 Tesla. A total of 241 suspicious lesions (108 malignancies, 44.8%) were further assessed with SLUS and second-look mammography. Subsequent image-guided biopsy of each lesion was performed using the most suitable modality. Size-dependent lesion detection rates in SLUS and mammography were compared by means of the McNemar test. ResultsLesions referred to MRI-guided biopsy were predominantly ≤ 10 mm in size (52.8%). SLUS displayed higher detection rates than mammography for mass lesions (55.6% [95% confidence interval 46.4–64.4%] versus 16.7% [10.6–24.3%]; p<0.001) with a particularly high sensitivity for malignant mass lesions > 10 mm (88.5 % [69.9–97.6%]). In contrast, the detection rate for malignant non-mass lesions was lower in SLUS than in second-look mammography (22.0% [11.5–36.0%] versus 38.0% [24.7–52.8%]; p<0.001). The malignancy rates in ultrasound-, mammography-, and MRI-guided biopsies were 53.7%, 55.2%, and 35.0%, respectively. ConclusionSLUS is an excellent tool for further assessment and biopsy of suspicious mass lesions > 10 mm without associated calcifications. In contrast, supplemental ultrasound is of limited value in the evaluation and biopsy guidance of suspicious non-mass lesions compared to second-look mammography.

Multi-parameter MRI radiomics model in predicting postoperative progressive cerebral edema and hemorrhage after resection of meningioma

BackgroundPostoperative progressive cerebral edema and hemorrhage (PPCEH) are major complications after meningioma resection, yet their preoperative predictive studies are limited. The aim is to develop and validate a multiparametric MRI machine learning model to predict PPCEH after meningioma resection.MethodsThis retrospective study included 148 patients with meningioma. A stratified three-fold cross-validation was used to split the dataset into training and validation sets. Radiomics features from the tumor enhancement (TE) and peritumoral brain edema (PTBE) regions were extracted from T1WI, T2WI, and ADC maps. Support vector machine constructed different radiomics models, and logistic regression explored clinical risk factors. Prediction models, integrating clinical and radiomics features, were evaluated using the area under the curve (AUC), visualized in a nomogram.ResultsThe radiomics model based on TE and PTBE regions (training set mean AUC: 0.85 (95% CI: 0.78–0.93), validation set mean AUC: 0.77 (95%CI: 0.63–0.90)) outperformed the model with TE region solely (training set mean AUC: 0.83 (95% CI: 0.76–0.91), validation set mean AUC: 0.73 (95% CI: 0.58–0.87)). Furthermore, the combined model incorporating radiomics features, and clinical features of preoperative peritumoral edema and tumor boundary adhesion, had the best predictive performance, with AUC values of 0.87 (95% CI: 0.80–0.94) and 0.84 (95% CI: 0.72–0.95) for the training and validation set.ConclusionsWe developed a novel model based on clinical characteristics and multiparametric radiomics features derived from TE and PTBE regions, which can accurately and non-invasively predict PPCEH after meningioma resection. Additionally, our findings suggest the crucial role of PTBE radiomics features in understanding the potential mechanisms of PPCEH.

Hearing loss and vestibular dysfunction in congenital CMV infection: could it be due to endolymphatic pressure anomaly? A preliminary study

ObjectivesTo describe the inner ear sectors after an inner ear MRI protocol and search for the presence of endolymphatic pressure anomaly in patients presenting with a congenital CMV infection and audio-vestibular dysfunction. MethodsA 3D FLAIR MRI sequence, 4 hours after gadolinium injection, was performed in patients with sensory-neural hearing loss secondary to a congenital CMV infection in order to analyse the morphology of the endolymphatic space. ResultsTwo patients presented with a unilateral SNHL and 4 patients a bilateral SNHL. Seven ears with SNHL demonstrated an endolymphatic hydrops on MRI images and 2 showed a membranous labyrinth atelectasis. All ears but two had a marked enhancement in the perilymph of the basal turn of the cochlea. One ear, with a normal hearing threshold but altered vestibular function, demonstrated cochlear and saccular hydrops. Two ears with normal or near normal hearing and normal vestibular function were radiologically normal on the MRI. ConclusionThe compartmental endolymphatic study using delayed contrast-enhanced MRI sequences in children with cCMV infection suggests a relationship between inner ear involvement and endolymphatic pressure anomaly.

Use of Ultra-Short Echo Time MRI to Improve Temporal Bone Imaging.

The short T2 nature of cortical bone causes it to appear similar to air on MR, forcing clinicians to rely on computed tomography imaging, with its attendant ionizing radiation exposure, to define temporal bone structures. Through the use of novel MR sequences with ultra-short echo times (UTE), short T2 structures are now able to be visualized, allowing for improved understanding of anatomical relationships. Eight patients (50% female) undergoing MR imaging of the skull base for diagnostic purposes (62.5% for vestibular schwannoma surveillance) at a tertiary care center were enrolled to evaluate the safety and efficacy of UTE imaging. CT scans were completed in 37.5% of the patients as part of their workup and used for comparison purposes. The repetition time, short echo time, and long echo time for the UTE sequence were 11, 0.032, and 2.2 msec, respectively. The protocol added 6 min to the total scanning time, and all patients tolerated the sequence without issue. The ossicles, mastoid air cells, antrum, and epitympanum were able to be seen and had a high Dice similarity coefficient when compared to CT (>0.5). UTE allowed for clear delineation of all segments of the facial nerve with a signal-to-noise ratio of 35 (although the BRAVO sequences had a superior ratio of 140). Vestibular schwannomas were able to be distinguished from normal brain parenchyma. UTE is safe and effective for visualizing anatomic structures not normally seen on traditional MRI, potentially allowing for improved surgical planning in patients. 3 Laryngoscope, 134:4691-4696, 2024.

Advanced Quantitative MRI Unveils Microstructural Thalamic Changes Reflecting Disease Progression in Multiple Sclerosis.

In patients with multiple sclerosis (PwMS), thalamic atrophy occurs during the disease course. However, there is little understanding of the mechanisms leading to volume loss and of the relationship between microstructural thalamic pathology and disease progression. This cross-sectional and longitudinal study aimed to comprehensively characterize in vivo pathologic changes within thalamic microstructure in PwMS using advanced multiparametric quantitative MRI (qMRI). Thalamic microstructural integrity was evaluated using quantitative T1, magnetization transfer saturation, multishell diffusion, and quantitative susceptibility mapping (QSM) in 183 PwMS and 105 healthy controls (HCs). The same qMRI protocol was available for 127 PwMS and 73 HCs after a 2-year follow-up period. Inclusion criteria for PwMS encompassed either an active relapsing-remitting MS (RRMS) or inactive progressive MS (PMS) disease course. Thalamic alterations were compared between PwMS and HCs and among disease phenotypes. In addition, the study investigated the relationship between thalamic damage and clinical and conventional MRI measures of disease severity. Compared with HCs, PwMS exhibited substantial thalamic alterations, indicative of microstructural and macrostructural damage, demyelination, and disruption in iron homeostasis. These alterations extended beyond focal thalamic lesions, affecting normal-appearing thalamic tissue diffusely. Over the follow-up period, PwMS displayed an accelerated decrease in myelin volume fraction [mean difference in annualized percentage change (MD-ApC) = -1.50; p = 0.041] and increase in quantitative T1 (MD-ApC = 0.92; p < 0.0001) values, indicating heightened demyelinating and neurodegenerative processes. The observed differences between PwMS and HCs were substantially driven by the subgroup with PMS, wherein thalamic degeneration was significantly accelerated, even in comparison with patients with RRMS. Thalamic qMRI alterations showed extensive correlations with conventional MRI, clinical, and cognitive disease burden measures. Disability progression over follow-up was associated with accelerated thalamic degeneration, as reflected by enhanced diffusion (β = -0.067; p = 0.039) and QSM (β = -0.077; p = 0.027) changes. Thalamic qMRI metrics emerged as significant predictors of neurologic and cognitive disability even when accounting for other established markers including white matter lesion load and brain and thalamic atrophy. These findings offer deeper insights into thalamic pathology in PwMS, emphasizing the clinical relevance of thalamic damage and its link to disease progression. Advanced qMRI biomarkers show promising potential in guiding interventions aimed at mitigating thalamic neurodegenerative processes.

Evaluation of radiation induced brain injury in nasopharyngeal carcinoma patients based on multi-parameter quantitative MRI: A prospective longitudinal study

PurposeThree dimensional pulsed continuous arterial spin labeling (3D-pCASL) and incoherent movement within voxels (IVIM) imaging was combined to assess dynamic microscopic structure changes of the hippocampus and temporal lobe white matter (TLWM) of nasopharyngeal carcinoma (NPC) patients post intensity-modulated radiation therapy (IMRT). MethodsForty-six patients who were first diagnosed with NPC and underwent IMRT were prospectively enrolled. 3D-CASL and IVIM were performed pre-RT, within 1 week (1 W) post-RT, 3 months (3 M) post-RT, 6 months (6 M) post-RT, and 18 months (18 M) post-RT. Twenty-seven patients completed follow-ups for all time periods, and their data were analyzed. The cerebral flow (CBF) derived from ASL, and apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (F) derived from IVIM of hippocampus and TLWM were analyzed. The quantitative parameters were measured before RT as the baseline, and the corresponding parameter values and change rates at each time point post-RT were compared using the non-parametric Wilcoxon rank sum test. ResultsAt 1 W post-RT, CBF showed a significant increase and peaked in both the hippocampus and TLWM (p < 0.05) with change rate of 30.3 % and 24.1 %. In the hippocampus, both D and D* were significantly increased from pre-RT to 6 M post-RT with change rate of 6.66 % and 34.7 %, while D*-values remained significantly higher than pre-RT at 12 months post-RT with change rate of 41.2 %. In the TLWM, the F firstly increased and then decreased, and was significantly decreased from pre-RT to 6 M post-RT with change rate of 20.2 %. Conclusion3D-PCASL and IVIM can indirectly reflecting the developmental pattern and molecular mechanism of RT induced brain injury.

Diagnostic MRI Score to Differentiate Susac Syndrome from Primary Angiitis of the Central Nervous System and Multiple Sclerosis.

Susac syndrome (SuS), multiple sclerosis (MS), and primary angiitis of the central nervous system (PACNS) present diagnostic challenges due to overlapping clinical features. We aimed to enhance diagnostic precision by developing the SPAMS (SuS, PACNS, MS) score, a practical radiological tool. This multicenter study included 99 patients (43 SuS, 37 MS, 19 PACNS) from South American countries. Relevant MRI features were identified through an elastic-net model determined key variables. The SPAMS score assigned 2 points for snowball lesions, 1 point for spokes-like lesions, or if there are more than 4 lesions in the corpus callosum, corpus callosum involvement, or cerebellar involvement. It subtracted 1 point if gadolinium-enhancing lesions or 4 points if Dawson's fingers are present. Bootstrapping validated the optimal cutoff at 2 points, exhibiting a diagnostic performance of area under the curve = 0.931, sensitivity = 88%, specificity = 89%, positive predictive value = 88%, negative predictive value = 89%, and accuracy = 88%. When specific MRI findings coexisted, the SPAMS score differentiated SuS from MS and PACNS. Access to MRI and standard protocol sequences makes it a valuable tool for timely diagnosis and treatment, potentially preventing disability progression and severe clinical outcomes. ANN NEUROL 2024;96:846-854.

Comparison of the predictive value of multiparametric MRI and prostate-specific membrane antigen PET/CT for pelvic lymph node metastasis in prostate cancer

Objective: To compare the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI) and prostate-specific membrane antigen (PSMA) PET/CT in detecting pelvic lymph node metastasis in prostate cancer. Methods: This is a retrospective case series study. A retrospective analysis was conducted on the data of 115 prostate cancer patients who underwent both mpMRI and PSMA PET/CT before undergoing radical prostatectomy and extended pelvic lymph node dissection at the Department of Urology, Xiangya Hospital, Central South University, between March 2020 and September 2023. The age (M(IQR)) was 67(10) years (range: 45 to 84 years), and the body mass index was 24(4) kg/m2 (range: 18 to 30 kg/m2). Pathological and imaging data were obtained from the patients. Lymph node pathology results were used as the gold standard to evaluate the diagnostic performance of mpMRI and PSMA PET/CT for detecting pelvic lymph node metastasis in PCa through diagnostic evaluation tests. Comparisons between groups were performed using independent samples t-test, Mann-Whitney U test, or χ2 test. Results: The positive rate for detecting pelvic lymph node metastasis was 18.3% (21/115) with mpMRI and 25.2% (29/115) with PSMA PET/CT. The pathological positive rate for lymph nodes was 28.7% (33/115). In patient-based analysis, the diagnostic sensitivity of PSMA PET/CT was significantly higher than that of mpMRI (63.6% vs. 30.3%, χ2=7.36, P=0.007). In lesion-based analysis, both the sensitivity and positive predictive value of PSMA PET/CT were significantly higher than those of mpMRI (sensitivity: 68.0% vs. 21.6%, χ2=42.20, P<0.01; positive predictive value: 50.0% vs. 23.1%, χ2=7.54, P=0.006). Conclusions: PSMA PET/CT and mpMRI both demonstrates good specificity in predicting pelvic lymph node metastasis in prostate cancer. However, PSMA PET/CT is significantly superior to mpMRI in terms of sensitivity and the detection rate of pathologically positive lymph nodes.

P231 Validation of multiparametric magnetic resonance imaging prior to transurethral resection of bladder tumor. Preliminary results of a protocol established in a tertiary hospital

P231 Validation of multiparametric magnetic resonance imaging prior to transurethral resection of bladder tumor. Preliminary results of a protocol established in a tertiary hospital