Improved Diffusion-Weighted Hyperpolarized 129Xe Lung MRI with Patch-Based Higher-Order, Singular Value Decomposition Denoising.

RATIONALE AND OBJECTIVES: Hyperpolarized xenon (129Xe) MRI is a noninvasive method to assess pulmonary structure and function. To measure lung microstructure, diffusion-weighted imaging-commonly the apparent diffusion coefficient (ADC)-can be employed to map changes in alveolar-airspace size resulting from normal aging and pulmonary disease. However, low signal-to-noise ratio (SNR) decreases ADC measurement certainty, and biases ADC to spuriously low values. Further, these challenges are most severe in regions of the lung where alveolar simplification or emphysematous remodeling generate abnormally high ADCs. Here, we apply Global Local Higher Order Singular Value Decomposition (GLHOSVD) denoising to enhance image SNR, thereby reducing uncertainty and bias in diffusion measurements. MATERIALS AND METHODS: GLHOSVD denoising was employed in simulated images and gas phantoms with known diffusion coefficients to validate its effectiveness and optimize parameters for analysis of diffusion-weighted 129Xe MRI. GLHOSVD was applied to data from 120 subjects (34 control, 39 cystic fibrosis (CF), 27 lymphangioleiomyomatosis (LAM), and 20 asthma). Image SNR, ADC, and distributed diffusivity coefficient (DDC) were compared before and after denoising using Wilcoxon signed-rank analysis for all images. RESULTS: Denoising significantly increased SNR in simulated, phantom, and in-vivo images, showing a greater than 2-fold increase (p < 0.001) across diffusion-weighted images. Although mean ADC and DDC remained unchanged (p > 0.05), ADC and DDC standard deviation decreased significantly in denoised images (p < 0.001). CONCLUSION: When applied to diffusion-weighted 129Xe images, GLHOSVD improved image quality and allowed airspace size to be quantified in high-diffusion regions of the lungs that were previously inaccessible to measurement due to prohibitively low SNR, thus providing insights into disease pathology.

Image quality of whole-body diffusion MR images comparing deep-learning accelerated and conventional sequences.

OBJECTIVES: To compare the image quality of deep learning accelerated whole-body (WB) with conventional diffusion sequences. METHODS: Fifty consecutive patients with bone marrow cancer underwent WB-MRI. Two experts compared axial b900 s/mm2 and the corresponding maximum intensity projections (MIP) of deep resolve boost (DRB) accelerated diffusion-weighted imaging (DWI) sequences (time of acquisition: 6:42 min) against conventional sequences (time of acquisition: 14 min). Readers assessed paired images for noise, artefacts, signal fat suppression, and lesion conspicuity using Likert scales, also expressing their overall subjective preference. Signal-to-noise and contrast-to-noise ratios (SNR and CNR) and the apparent diffusion coefficient (ADC) values of normal tissues and cancer lesions were statistically compared. RESULTS: Overall, radiologists preferred either axial DRB b900 and/or corresponding MIP images in almost 80% of the patients, particularly in patients with a high body-mass index (BMI > 25 kg/m2). In qualitative assessments, axial DRB images were preferred (preferred/strongly preferred) in 56-100% of cases, whereas DRB MIP images were favoured in 52-96% of cases. DRB-SNR/CNR was higher in all normal tissues (p < 0.05). For cancer lesions, the DRB-SNR was higher (p < 0.001), but the CNR was not different. DRB-ADC values were significantly higher for the brain and psoas muscles, but not for cancer lesions (mean difference: + 53 µm2/s). Inter-class correlation coefficient analysis showed good to excellent agreement (95% CI 0.75-0.93). CONCLUSION: DRB sequences produce higher-quality axial DWI, resulting in improved MIPs and significantly reduced acquisition times. However, differences in the ADC values of normal tissues need to be considered. CLINICAL RELEVANCE STATEMENT: Deep learning accelerated diffusion sequences produce high-quality axial images and MIP at reduced acquisition times. This advancement could enable the increased adoption of Whole Body-MRI for the evaluation of patients with bone marrow cancer. KEY POINTS: Deep learning reconstruction enables a more than 50% reduction in acquisition time for WB diffusion sequences. DRB images were preferred by radiologists in almost 80% of cases due to fewer artefacts, improved background signal suppression, higher signal-to-noise ratio, and increased lesion conspicuity in patients with higher body mass index. Cancer lesion diffusivity from DRB images was not different from conventional sequences.

Diffusion weighted MRI and apparent diffusion coefficient as a prognostic biomarker in evaluating chemotherapy-antiangiogenic treated stage IV non-small cell lung cancer: A prospective, single-arm, open-label, clinical trial (BevMar).

PURPOSE: When treating Lung Cancer, it is necessary to identify early treatment failure to enable timely therapeutic adjustments. The Aim of this study was to investigate whether changes in tumor diffusion during treatment with chemotherapy and bevacizumab could serve as a predictor of treatment failure. MATERIAL AND METHODS: A prospective single-arm, open-label, clinical trial was conducted between September 2014 and December 2020, enrolling patients with stage IV non-small cell lung cancer (NSCLC). The patients were treated with chemotherapy-antiangiogenic combination. Diffusion weighted magnetic resonance imaging (DW-MRI) was performed at baseline, two, four, and sixteen weeks after initiating treatment. The differences in apparent diffusion coefficient (ADC) values between pre- and post-treatment MRIs were recorded as Delta values (ΔADC). We assessed whether ΔADC could serve as a prognostic biomarker for overall survival (OS), with a five year follow up. RESULTS: 18 patients were included in the final analysis. Patients with a ΔADC value ≥ -3 demonstrated a significantly longer OS with an HR of 0.12 (95 % CI; 0.03- 0.61; p = 0.003) The median OS in patients with a ΔADC value ≥ -3 was 18 months, (95 % C.I; 7-46) compared to 7 months (95 % C.I; 5-9) in those with a ΔADC value < -3. CONCLUSION: Our findings suggest that early changes in tumor ADC values, may be indicative of a longer OS. Therefore, DW-MRI could serve as an early biomarker for assessing treatment response in patients receiving chemotherapy combined with antiangiogenic therapy.

Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis: insights from structural connectome graph theoretical network analysis.

BACKGROUND: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis. METHODS: Structural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome. RESULTS: Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001). CONCLUSIONS: Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.

Total Tumor ADC Histogram Analysis: A New Tool for Predicting High-Risk Cytogenetic Abnormalities in Multiple Myeloma Patients.

RATIONALE AND OBJECTIVES: We explored the feasibility of using total tumor apparent diffusion coefficient (ttADC) histogram parameters to predict high-risk cytogenetic abnormalities (HRCA) in patients with multiple myeloma (MM) and compared the performance of an image prediction model based on these parameters with that of a combined prediction model based on these parameters and clinical indicators. METHODS: We retrospectively analyzed the parameters of the ttADC histogram based on whole-body diffusion-weighted images(WB-DWI) and clinical indicators in 92 patients with MM. The patients were divided into HRCA and non-HRCA groups according to the results of the fluorescence in situ hybridization. Logistic regression analysis was used to construct the image prediction and combined prediction models. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the performance of the models to identify HRCA. The DeLong test was used to compare the AUC differences of each prediction model. RESULTS: Logistic regression analysis results revealed that the ttADC histogram parameter, ttADC entropy < 7.959 (OR: 39.167; 95% confidence interval [CI]: 3.891-394.208; P < 0.05), was an independent risk factor for HRCA. The image prediction model consisted of ttADC entropy and ttADC SD. The combined prediction model included ttADC entropy along with patient clinical indicators such as biological sex and M protein percentage. The AUCs of the image prediction and combined prediction models were 0.739 and 0.811, respectively (P < .05). The image prediction model showed a sensitivity of 73.9% and a specificity of 68.1%. The combined prediction model showed 82.6% sensitivity and 72.5% specificity. CONCLUSIONS: Using ttADC histogram parameters based on WB-DWI images to predict HRCA in patients with MM is feasible, and combining ttADC parameters with clinical indicators can achieve better predictive performance.

MRI free water mediates the association between water exchange rate across the blood brain barrier and executive function among older adults.

Vascular risk factors contribute to cognitive aging, with one such risk factor being dysfunction of the blood brain barrier (BBB). Studies using non-invasive magnetic resonance imaging (MRI) techniques, such as diffusion prepared arterial spin labeling (DP-ASL), can estimate BBB function by measuring water exchange rate (kw). DP-ASL kw has been associated with cognition, but the directionality and strength of the relationship is still under investigation. An additional variable that measures water in extracellular space and impacts cognition, MRI free water (FW), may help explain prior findings. A total of 94 older adults without dementia (Mean age = 74.17 years, 59.6% female) underwent MRI (DP-ASL, diffusion weighted imaging (DWI)) and cognitive assessment. Mean kw was computed across the whole brain (WB), and mean white matter FW was computed across all white matter. The relationship between kw and three cognitive domains (executive function, processing speed, memory) was tested using multiple linear regression. FW was tested as a mediator of the kw-cognitive relationship using the PROCESS macro. A positive association was found between WB kw and executive function [F(4,85) = 7.81, p < .001, R2= 0.269; ß = .245, p = .014]. Further, this effect was qualified by subsequent results showing that FW was a mediator of the WB kw-executive function relationship (indirect effect results: standardized effect = .060, bootstrap confidence interval = .0006 to .1411). Results suggest that lower water exchange rate (kw) may contribute to greater total white matter (WM) FW which, in turn, may disrupt executive function. Taken together, proper fluid clearance at the BBB contributes to higher-order cognitive abilities.

Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer.

BACKGROUND: High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa. METHODS: One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). RESULTS: Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. CONCLUSION: sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Diffusion-weighted imaging in addition to contrast-enhanced MRI in identifying complete response in HER2-positive breast cancer.

OBJECTIVES: The aim of this study is to investigate the added value of diffusion-weighted imaging (DWI) to dynamic-contrast enhanced (DCE)-MRI to identify a pathological complete response (pCR) in patients with HER2-positive breast cancer and radiological complete response (rCR). MATERIALS AND METHODS: This is a single-center observational study of 102 patients with stage I-III HER2-positive breast cancer and real-world documented rCR on DCE-MRI. Patients were treated between 2015 and 2019. Both 1.5 T/3.0 T single-shot diffusion-weighted echo-planar sequence were used. Post neoadjuvant systemic treatment (NST) diffusion-weighted images were reviewed by two readers for visual evaluation and ADCmean. Discordant cases were resolved in a consensus meeting. pCR of the breast (ypT0/is) was used to calculate the negative predictive value (NPV). Breast pCR-percentages were tested with Fisher's exact test. ADCmean and ∆ADCmean(%) for patients with and without pCR were compared using a Mann-Whitney U-test. RESULTS: The NPV for DWI added to DCE is 86% compared to 87% for DCE alone in hormone receptor (HR)-/HER2-positive and 67% compared to 64% in HR-positive/HER2-positive breast cancer. Twenty-seven of 39 non-rCR DWI cases were false positives. In HR-negative/HER2-positive breast cancer the NPV for DCE MRI differs between MRI field strength (1.5 T: 50% vs. 3 T: 81% [p = 0.02]). ADCmean at baseline, post-NST, and ∆ADCmean were similar between patients with and without pCR. CONCLUSION: DWI has no clinically relevant effect on the NPV of DCE alone to identify a pCR in early HER2-positive breast cancer. The added value of DWI in HR-positive/HER2-positive breast cancer should be further investigated taken MRI field strength into account. CLINICAL RELEVANCE STATEMENT: The residual signal on DWI after neoadjuvant systemic therapy in cases with early HER2-positive breast cancer and no residual pathologic enhancement on DCE-MRI breast should not (yet) be considered in assessing a complete radiologic response. KEY POINTS: Radiologic complete response is associated with a pathologic complete response (pCR) in HER2+ breast cancer but further improvement is warranted. No relevant increase in negative predictive value was observed when DWI was added to DCE. Residual signal on DW-images without pathologic enhancement on DCE-MRI, does not indicate a lower chance of pCR.

The diagnostic performance of T1 mapping in the assessment of breast lesions: A preliminary study.

PURPOSE: To assess T1 mapping performance in distinguishing between benign and malignant breast lesions and to explore its correlation with histopathologic features in breast cancer. METHODS: This study prospectively enrolled 103 participants with a total of 108 lesions, including 25 benign and 83 malignant lesions. T1 mapping, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) were performed. Two radiologists independently outlined the ROIs and analyzed T1 and apparent diffusion coefficient (ADC) values for each lesion, assessing interobserver reliability with the intraclass correlation coefficient (ICC). T1 and ADC values were compared between benign and malignant lesions, across different histopathological characteristics (histological grades, estrogen, progesterone and HER2 receptors expression, Ki67, N status). Receiver operating characteristic (ROC) analysis and Pearson correlation coefficient (ρ) were performed. RESULTS: T1 values showed statistically significant differences between benign and malignant groups (P < 0.001), with higher values in the malignant (1817.08 ms ± 126.64) compared to the benign group (1429.31 ms ± 167.66). In addition, T1 values significantly increased in the ER (-) group (P = 0.001). No significant differences were found in T1 values among HER2, Ki67, N status, and histological grades groups. Furthermore, T1 values exhibited a significant correlation (ρ) with ER (P < 0.01) and PR (P = 0.03). The AUC for T1 value in distinguishing benign from malignant lesions was 0.69 (95 % CI: 0.55 - 0.82, P = 0.005), and for evaluating ER status, it was 0.75 (95 % CI: 0.62 - 0.87, P = 0.002). CONCLUSIONS: T1 mapping holds the potential as an imaging biomarker to assist in the discrimination of benign and malignant breast lesions and assessing the ER expression status in breast cancer.

Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts.

BACKGROUND: Early Psychosis patients (EP, within 3 years after psychosis onset) show significant variability, making outcome predictions challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, limiting the development of early interventions. METHODS: A data-driven approach, Partial Least Squares (PLS) correlation, was used across two independent datasets to examine multivariate relationships between white matter (WM) properties and symptomatology, to identify stable and generalizable signatures in EP. The primary cohort included EP patients from the Human Connectome Project-Early Psychosis (n=124). The replication cohort included EP patients from the Feinstein Institute for Medical Research (n=78). Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. RESULTS: In both cohorts, a significant latent component (LC) corresponded to a symptom profile combining negative symptoms, primarily diminished expression, with specific somatic symptoms. Both LCs captured comprehensive features of WM disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the PLS model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. CONCLUSIONS: This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural WM alterations in EP, across diagnoses and datasets, showing a strong covariance of these alterations with a unique profile of negative and somatic symptoms. This finding suggests the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

Insulin Resistance and White Matter Microstructural Abnormalities in Nondiabetic Adult: A Population-Based Study.

BACKGROUND: Insulin resistance (IR) is of growing concern yet its association with white matter integrity remains controversial. We aimed to investigate the association between IR and white matter integrity in nondiabetic adults. METHODS: This cross-sectional analysis was conducted based on the PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study. A total of 1709 Nondiabetic community-dwelling adults with available diffusion weighted imaging based on brain magnetic resonance imaging and completed oral glucose tolerance test were included. IR was measured non-invasively by insulin sensitivity indices (ISI), including ISIcomposite and ISI0,120, as well as homeostasis model assessment of insulin resistance (HOMA-IR). White matter microstructure abnormalities were identified by diffusion weighted imaging along with tract-based spatial statistics analysis to compare diffusion metrics between groups. The multivariable linear regression models were applied to measure the association between white matter microstructure abnormalities and IR. RESULTS: A total of 1709 nondiabetic individuals with a mean age of 60.8±6.4 years and 53.5% female were included. We found that IR was associated with a significant increase in mean diffusivity, axial diffusivity, and radial diffusivity extensively in cerebral white matter in regions such as the anterior corona radiata, superior corona radiata, anterior limb of internal capsule, external capsule, and body of corpus callosum. The pattern of associations was more marked for ISIcomposite and ISI0,120. However, the effect of insulin resistance on white matter integrity was attenuated after additionally adjustment for history of hypertension and cardiovascular disease and antihypertensive medication use. CONCLUSION: Our findings indicate a significant association between IR and white matter microstructural abnormalities in nondiabetic middle-aged community residents, while these associations were greatly influenced by the history of hypertension and cardiovascular disease, and antihypertensive medication use. Further investigation is needed to clarify the role of IR in white matter integrity, whereas prophylactic strategies of maintaining a low IR status may ameliorate disturbances in white matter integrity.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling.

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Correlation between DWI-ASPECTS Score, Ischemic Stroke Volume on DWI, Clinical Severity and Short-Term Prognosis: A Single-Center Study.

Ischemic stroke is a significant public health concern, with its incidence expected to double over the next 40 years, particularly among individuals over 75 years old. Previous studies, such as the DAWN trial, have highlighted the importance of correlating clinical severity with ischemic stroke volume to optimize patient management. Our study aimed to correlate the clinical severity of ischemic stroke, as assessed by the NIHSS score, with ischemic stroke volume measured using DWI, and short-term prognosis quantified by the mRS score at discharge. Conducted at the largest hospital in Gorj County from January 2023 to December 2023, this study enrolled 43 consecutive patients with acute ischemic stroke. In our patient cohort, we observed a strong positive correlation between NIHSS score and ischemic stroke volume (Spearman correlation coefficient = 0.982, p < 0.01), and a strong negative correlation between ASPECTS-DWI score and mRS score (Spearman correlation coefficient = -0.952, p < 0.01). Multiple linear regression analysis revealed a significant collective relationship between ASPECTS score, ischemic stroke volume, and NIHSS score (F(1, 41) = 600.28, p < 0.001, R2 = 0.94, R2adj = 0.93). These findings underscore the importance of DWI in assessing ischemic stroke severity and prognosis, warranting further investigation for its integration into clinical practice.

Liver fibrosis detected by diffusion-weighted magnetic resonance imaging and its functional correlates in Fontan patients.

OBJECTIVES: The evaluation of Fontan-associated liver disease is often challenging. Diffusion-weighted magnetic resonance imaging can detect hepatic fibrosis from capillary perfusion and diffusion abnormalities from extracellular matrix accumulation. This study investigated its role in the evaluation of liver disease in Fontan patients and explored possible diagnostic methods for early detection of advanced liver fibrosis. METHODS: Stable adult Fontan patients who could safely be examined with magnetic resonance imaging were enrolled, and blood biomarkers, transient elastography were also examined. RESULTS: Forty-six patients received diffusion-weighted imaging; and 58.7% were diagnosed with advanced liver fibrosis (severe liver fibrosis, 37.0%, and cirrhosis 21.7%). Two parameters of hepatic dysfunction, platelet counts (Spearman's ρ: -0.456, P = 0.001) and cholesterol levels (Spearman's ρ: -0.383, P = 0.009), decreased with increasing severity of fibrosis. Using transient elastography, a cut-off value of 14.2 kPa predicted the presence of advanced liver fibrosis, but with a low positive predictive value. When we included platelet count, cholesterol, post-Fontan years and transient elastography values as a composite, the capability of predicting advanced liver fibrosis was the most satisfactory (C statistic 0.817 ± 0.071, P < 0.001). A cut-off value of 5.0 revealed a sensitivity of 78% and a specificity of 82%. CONCLUSIONS: In Fontan patients, diffusion-weighted imaging was helpful in detecting liver fibrosis that was correlated with hepatic dysfunction. A simple score was proposed for long-term surveillance and early detection of advanced liver disease in adult Fontan patients. For adult Fontan patients with a calculated score > 5.0, we may consider timely diffusion-weight imaging and early management for liver complications.

Breast Cancer: Multi-b-Value Diffusion Weighted Habitat Imaging in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy.

RATIONALE AND OBJECTIVES: The aim of this study was to ascertain whether the utilization of multiple b-value diffusion-weighted habitat imaging, a technique that depicts tumor heterogeneity, could aid in identifying breast cancer patients who would derive substantial benefit from neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: This prospective study enrolled 143 women (II-III breast cancer), who underwent multi-b-value diffusion-weighted imaging (DWI) in 3-T magnetic resonance (MR) before NAC. The patient cohort was partitioned into a training set (consisting of 100 patients, of which 36 demonstrated a pathologic complete response [pCR]) and a test set (featuring 43 patients, 16 of whom exhibited pCR). Utilizing the training set, predictive models for pCR, were constructed using different parameters: whole-tumor radiomics (ModelWH), diffusion-weighted habitat-imaging (ModelHabitats), conventional MRI features (ModelCF), along with combined models ModelHabitats+CF. The performance of these models was assessed based on the area under the receiver operating characteristic curve (AUC) and calibration slope. RESULTS: In the prediction of pCR, ModelWH, ModelHabitats, ModelCF, and ModelHabitats+CF achieved AUCs of 0.733, 0.722, 0.705, and 0.756 respectively, within the training set. These scores corresponded to AUCs of 0.625, 0.801, 0.700, and 0.824 respectively in the test set. The DeLong test revealed no significant difference between ModelWH and ModelHabitats (P = 0.182), between ModelHabitats and ModelHabitats+CF (P = 0.113). CONCLUSION: The habitat model we developed, incorporating first-order features along with conventional MRI features, has demonstrated accurate predication of pCR prior to NAC. This model holds the potential to augment decision-making processes in personalized treatment strategies for breast cancer.

Diffusion-Weighted Magnetic Resonance Imaging (dMRI) and Cochlear Implant Outcomes in Axonal Auditory Neuropathy: A Case Report.

BACKGROUND: Progressive auditory dysfunction is common in patients with generalized neurodegenerative conditions, but clinicians currently lack the diagnostic tools to determine the location/degree of the pathology and, hence, to provide appropriate intervention. In this study, we present the white-matter microstructure measurements derived from a novel diffusion-weighted magnetic resonance imaging (dMRI) technique in a patient with axonal auditory neuropathy and consider the findings in relation to the auditory intervention outcomes. METHODS: We tracked the hearing changes in an adolescent with Riboflavin Transporter Deficiency (Type 2), evaluating the sound detection/discrimination, auditory evoked potentials, and both structural- and diffusion-weighted MRI findings over a 3-year period. In addition, we explored the effect of bilateral cochlear implantation in this individual. RESULTS: Between the ages of 15 years and 18 years, the patient showed a complete loss of functional hearing ability. The auditory brainstem response testing indicated an auditory neuropathy with evidence of normal cochlear function but disrupted auditory neural activity. While three structural MRI assessments across this period showed a clinically normal cochleovestibular anatomy, the dMRI evaluation revealed a significant loss of fiber density consistent with axonopathy. The subsequent cochlear implant function was affected with the high levels of current required to elicit auditory sensations and concomitant vestibular and facial nerve stimulation issues. CONCLUSIONS: The case study demonstrates the ability of dMRI technologies to identify the subtle white-matter microstructure changes in the auditory pathway, which may disrupt the neural function in patients with auditory axonopathy.

Non-Gaussian diffusion metrics with whole-tumor histogram analysis for bladder cancer diagnosis: muscle invasion and histological grade.

PURPOSE: To investigate the performance of histogram features of non-Gaussian diffusion metrics for diagnosing muscle invasion and histological grade in bladder cancer (BCa). METHODS: Patients were prospectively allocated to MR scanner1 (training cohort) or MR2 (testing cohort) for conventional diffusion-weighted imaging (DWIconv) and multi-b-value DWI. Metrics of continuous time random walk (CTRW), diffusion kurtosis imaging (DKI), fractional-order calculus (FROC), intravoxel incoherent motion (IVIM), and stretched exponential model (SEM) were simultaneously calculated using multi-b-value DWI. Whole-tumor histogram features were extracted from DWIconv and non-Gaussian diffusion metrics for logistic regression analysis to develop diffusion models diagnosing muscle invasion and histological grade. The models' performances were quantified by area under the receiver operating characteristic curve (AUC). RESULTS: MR1 included 267 pathologically-confirmed BCa patients (median age, 67 years [IQR, 46-82], 222 men) and MR2 included 83 (median age, 65 years [IQR, 31-82], 73 men). For discriminating muscle invasion, CTRW achieved the highest testing AUC of 0.915, higher than DWIconv's 0.805 (p = 0.014), and similar to the combined diffusion model's AUC of 0.885 (p = 0.076). For differentiating histological grade of non-muscle-invasion bladder cancer, IVIM outperformed a testing AUC of 0.897, higher than DWIconv's 0.694 (p = 0.020), and similar to the combined diffusion model's AUC of 0.917 (p = 0.650). In both tasks, DKI, FROC, and SEM failed to show diagnostic superiority over DWIconv (p > 0.05). CONCLUSION: CTRW and IVIM are two potential non-Gaussian diffusion models to improve the MRI application in assessing muscle invasion and histological grade of BCa, respectively. CRITICAL RELEVANCE STATEMENT: Our study validates non-Gaussian diffusion imaging as a reliable, non-invasive technique for early assessment of muscle invasion and histological grade in BCa, enhancing accuracy in diagnosis and improving MRI application in BCa diagnostic procedures. KEY POINTS: Muscular invasion largely determines bladder salvageability in bladder cancer patients. Evaluated non-Gaussian diffusion metrics surpassed DWIconv in BCa muscle invasion and histological grade diagnosis. Non-Gaussian diffusion imaging improved MRI application in preoperative diagnosis of BCa.

Comparison of the monoexponential and biexponential models of diffusion-weighted magnetic imaging in grading clear-cell renal cell carcinoma: a case-control study.

Background: An accurate and noninvasive method to determine the preoperative clear-cell renal cell carcinoma (ccRCC) pathological grade is of great significance for surgical program selection and prognosis assessment. Previous studies have shown that diffusion-weighted imaging (DWI) has moderate value in grading ccRCC. But DWI cannot reflect the diffusion of tissue accurately because it is calculated using a monoexponential model. Intravoxel incoherent motion (IVIM) is the biexponential model of DWI. Only a few studies have examined the value of IVIM in grading ccRCC yet with inconsistent results. This study aimed to compare the value of DWI and IVIM in grading ccRCC. Methods: In this study, 96 patients with pathologically confirmed ccRCC were evaluated by DWI and IVIM on a 3-T scanner. According to the World Health Organization/International Society of Urological Pathology (WHO/ISUP) classification system, these patients were divided into two groups: low-grade (grade I and II) and high-grade (grade III and IV) ccRCC. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction of pseudodiffusion (f) values were calculated. The Mann-Whitney test, receiver-operating characteristic (ROC) analysis, and the Delong test were used for statistical evaluations. Results: (I) According to the WHO/ISUP nuclear grading system, 96 patients were divided into low-grade (grade I and II, 45 patients) and high-grade (grade III and IV, 51 patients) groups. (II) Compared with patients of low-grade ccRCC, the ADC and D values of those with high-grade ccRCC decreased while the D* and f values increased (P<0.05). (III) The cutoff value of the ADC, D, D*, and f in distinguishing low-grade from high-grade ccRCC was 1.50×10-3 mm2/s, 1.12×10-3 mm2/s, and 33.19×10-3 mm2/s, 0.31, respectively; the area under the curve (AUC) for the ADC, D, D*, and f values was 0.871, 0.942, 0.621, and 0.894, respectively, with the AUC of the D value being the highest; the sensitivity for the ADC, D, D*, and f values was 94.12%, 92.16%, 47.06%, and 92.16%, respectively; and the specificity for the ADC, D, D*, and f values was 66.67%, 91.11%, 77.78%, and 73.33%, respectively. (IV) Based on the Delong test, AUCD was significantly higher than AUCADC (P=0.02) and AUCD* (P<0.001), but there was no significant difference between AUCD and AUC f (P=0.18). Conclusions: Compared with the monoexponential model DWI, the biexponential model IVIM was more accurate in grading ccRCC.

Role of MRI in Evaluation of Tongue and Hypopharyngeal Lesions.

Tongue is a complex, principally muscular structure extending from oral cavity to oropharynx. Hypopharynx extends from the level of hyoid bone and to the level of inferior margin of cricoid cartilage and is divided into pyriform sinus, posterior cricoid region and posterior pharyngeal wall. Lesions that can affect the tongue and hypopharynx include neoplastic, congenital, vascular and infectious etiologies. Imaging provides crucial details for diagnosis and the appropriate management of these lesions. To evaluate the role of MRI in characterisation of benign and malignant lesions of tongue, malignant lesions of hypopharynx and staging the neoplastic lesions. The study was performed on 60 patients suspected of tongue and hypopharyngeal lesions in Dr Ram Manohar Lohia Hospital, New Delhi from 1st January 2021 to 31st May 2022. The study was done on SEIMENS skyra MRI scanner. Radiological characteristics, clinical features were studied and statistical inference was interrogated. Out of 60 patients, 32 were of tongue cancer, 10 of base of tongue cancer, 8 of hypopharyngeal cancer, 8 of hemangioma tongue and 2 of thyroglossal cyst. The mean age of our study population was 42.87 years. The qualitative analysis between diffusion restriction and histopathological examination shows a strong and substantial agreement between the two variables and a p value of 0.0014. The overall diagnostic accuracy of MRI was 85.5% and for CT was 82.5%. MRI plays an important role in differentiation of benign from malignant lesions of tongue and hypopharynx and staging of the malignant lesions. The correlation between MRI and CT findings of malignant lesions of tongue and hypopharynx indicated that both CECT and MRI have high diagnostic accuracy in diagnosing and staging but MRI is better for T and N staging of the malignant lesions with a diagnostic accuracy of 85.5% which was higher than the diagnostic accuracy of CT (82.5%). Thus, in conclusion MRI has a remarkable role in characterization and staging of benign and malignant lesions of tongue and hypopharynx. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-024-04532-y.