Diffusion-weighted Imaging Research Articles

Quantitative MRI in children with Crohn's disease - where do we stand?

Crohn's disease (CD) is a chronic inflammatory condition that affects the gastrointestinal tract, particularly the ileum and colon. This disease is characterized by recurrent bouts of intestinal inflammation with subsequent bowel wall damage, including scarring (i.e., fibrosis) and abnormal smooth muscle proliferation. MR enterography, an MRI examination tailored to assess the small bowel, is a first-line diagnostic tool for diagnosing CD in children, characterization and monitoring of disease severity and extent, and assessment of disease-related complications. To date, such MRI evaluations have been mostly qualitative, which can adversely impact diagnostic performance and inter-radiologist agreement. Quantitative MRI methods have been shown to aid in the evaluation of a variety of medical conditions and have been increasingly investigated in children and adults with CD. In CD, such objective techniques have been used to assist with diagnosis, assess treatment response, and characterize bowel wall histologic abnormalities. In the current work, we will review quantitative MRI methods for detecting and measuring intestinal active inflammation (MRI-based scoring systems, T1 relaxation mapping, diffusion-weighted imaging, intra-voxel incoherent motion, mesenteric phase contrast), bowel wall damage (magnetization transfer), and motility (quantitative cine imaging) in small bowel CD, with an emphasis on the pediatric population.

Reconstruction of intra- and extra-neurite conductivity tensors via conductivity at Larmor frequency and DWI data patterns.

The developed magnetic resonance electrical properties tomography (MREPT) techniques visualize the internal conductivity distribution at Larmor frequency by measuring the B1 transceive phase data. In biological tissues, electrical conductivity is influenced by ion concentrations and mobility. To visualize the anisotropic conductivity tensor of biological tissues, we use the Einstein-Smoluchowski equation, which links the diffusion coefficient to particle mobility. By assuming a correlation between ion mobility and water diffusivity, we aim to decompose the internal isotropic conductivity at Larmor frequency into anisotropic conductivity tensors within the intra- and extra-neurite compartments. The multi-compartment spherical mean technique (MC-SMT), utilizing both high and low b-value diffusion-weighted imaging (DWI) data, characterizes the diffusion of water molecules within and across the intra- and extra-neurite compartments by analyzing the microstructural intricacies and the foundational architectural arrangement of the brain's tissues. By analyzing the relationships between the measured DWI data, the microscopic diffusion signal, and the fiber orientation distribution function, we predict the DWI data for the intra- and extra-neurite compartments using spherical harmonic decomposition. Using the predicted DWI data for the intra- and extra-neurite compartments, we develop a conductivity tensor imaging method that operates specifically within the separated compartments. Human brain experiments, involving four healthy volunteers and a brain tumor patient, were performed to assess and confirm the reliability of the proposed method.

Human Claustrum Connections: Robust In Vivo Detection by DWI-Based Tractography in Two Large Samples.

Despite substantial neuroscience research in the last decade revealing the claustrum's prominent role in mammalian forebrain organization, as evidenced by its extraordinarily widespread connectivity pattern, claustrum studies in humans are rare. This is particularly true for studies focusing on claustrum connections. Two primary reasons may account for this situation: First, the intricate anatomy of the human claustrum located between the external and extreme capsule hinders straightforward and reliable structural delineation. In addition, the few studies that used diffusion-weighted-imaging (DWI)-based tractography could not clarify whether in vivo tractography consistently and reliably identifies claustrum connections in humans across different subjects, cohorts, imaging methods, and connectivity metrics. To address these issues, we combined a recently developed deep-learning-based claustrum segmentation tool with DWI-based tractography in two large adult cohorts: 81 healthy young adults from the human connectome project and 81 further healthy young participants from the Bavarian longitudinal study. Tracts between the claustrum and 13 cortical and 9 subcortical regions were reconstructed in each subject using probabilistic tractography. Probabilistic group average maps and different connectivity metrics were generated to assess the claustrum's connectivity profile as well as consistency and replicability of tractography. We found, across individuals, cohorts, DWI-protocols, and measures, consistent and replicable cortical and subcortical ipsi- and contralateral claustrum connections. This result demonstrates robust in vivo tractography of claustrum connections in humans, providing a base for further examinations of claustrum connectivity in health and disease.

Hypothalamus Connectivity in Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disabling illness of unknown etiology. Increasing evidence suggests hypothalamic involvement in ME/CFS pathophysiology, which has rarely been explored using magnetic resonance imaging (MRI)in the condition. This work aimed to use MRI to examine hypothalamus connectivity in adolescents with ME/CFS and explore how this relates to fatigue severity and illness duration. 25 adolescents with ME/CFS and 23 healthy controls completed a neuroimaging protocol consisting of structural and multishell diffusion-weighted imaging sequences, in addition to the PedsQL Multidimensional Fatigue Scale to assess fatigue severity. Information about illness duration was acquired at diagnosis. Preprocessing and streamlines tractography was performed using QSIPrep combined with a custom parcellation scheme to create structural networks. The number (degree) and weight (strength) of connections between lateralized hypothalamus regions and cortical and subcortical nodes were extracted, and relationships between connectivity measures, fatigue severity, and illness duration were performed using Bayesian regression models. We observed weak-to-moderate evidence of increased degree, but not strength, of connections from the bilateral anterior-inferior (left: pd [%] = 99.18, median [95% CI] = -22.68[-40.96 to 4.45]; right: pd [%] = 99.86, median [95% CI] = -23.35[-38.47 to 8.20]), left anterior-superior (pd [%] = 99.33, median [95% CI] = -18.83[-33.45 to 4.07]) and total left hypothalamus (pd [%] = 99.44, median [95% CI] = -47.18[-83.74 to 11.03]) in the ME/CFS group compared with controls. Conversely, bilateral posterior hypothalamus degree decreased with increasing ME/CFS illness duration (left: pd [%] = 98.13, median [95% CI]: -0.47[-0.89 to 0.03]; right: pd [%] = 98.50, median [95% CI]:-0.43[-0.82 to 0.05]). Finally, a weak relationship between right intermediate hypothalamus connectivity strength and fatigue severity was identified in the ME/CFS group (pd [%] = 99.35, median [95% CI] = -0.28[-0.51 to 0.06]), which was absent in controls. These findings suggest changes in hypothalamus connectivity may occur in adolescents with ME/CFS, warranting further investigation.

Specific clinical and radiological characteristics of anti-NMDA receptor autoimmune encephalitis following herpes encephalitis.

Herpes simplex virus encephalitis (HSE) frequently triggers secondary anti-N-methyl-D-aspartate receptor encephalitis (NMDARE), but markers predicting the occurrence of this entity (HSE-NMDARE) are lacking. We conducted a retrospective description of patients with HSE-NMDARE diagnosed between July 2014 and August 2022 and compared them to both patients with regular forms of HSE and NMDARE. Among the 375 patients with NMDARE, 13 HSE-NMDARE were included. The median age was 19years (0.5-73), 4/13 (31%) were children < 4years old, and 7/13 (54%) were male. The median time between HSE and NMDARE onset was 30days (21-46). During NMDARE, symptoms differed from HSE, including increased behavioral changes (92% vs 23%, p = 0.008), movements disorders (62% vs 0%, p = 0.013), and dysautonomia (54% vs 0%, p = 0.041). Compared to 21 patients with regular HSE, patients with HSE-NMDARE more often achieved severity-associated criteria on initial MRIs, with extensive lesions (11/11, 100% vs 10/21, 48%, p = 0.005) and bilateral diffusion-weighted imaging sequence abnormalities (9/10, 90% vs 6/21, 29%, p = 0.002). Compared to 198 patients with regular NMDARE, patients with HSE-NMDARE were more frequently males (7/13, 54% vs 43/198, 22%; p = 0.015) and children < 4 (4/13, 31% vs 14/198, 7%; p = 0.016), with a worse 12-month mRS (2[1-6] vs 1[0-6], p = 0.023). Herein, patients with HSE-NMDARE have a poorer long-term prognosis than patients with regular NMDARE. We report a greater rate of severity-associated criteria on initial MRIs for HSE-NMDARE compared to regular HSE, which may help identify patients with higher risk of HSE-NMDARE.

Time-Dependent Diffusion MRI Helps Predict Molecular Subtypes and Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Time-dependent diffusion MRI has the potential to help characterize tumor cell properties; however, to the knowledge of the authors, its usefulness for breast cancer diagnosis and prognostic evaluation is unknown. Purpose To investigate the clinical value of time-dependent diffusion MRI-based microstructural mapping for noninvasive prediction of molecular subtypes and pathologic complete response (pCR) in participants with breast cancer. Materials and Methods Participants with invasive breast cancer who underwent pretreatment with time-dependent diffusion MRI between February 2021 and May 2023 were prospectively enrolled. Four microstructural parameters were estimated using the IMPULSED method (a form of time-dependent diffusion MRI), along with three apparent diffusion coefficient (ADC) measurements and a relative ADC diffusion-weighted imaging parameter. Multivariable logistic regression analysis was used to identify parameters associated with each molecular subtype and pCR. A predictive model based on associated parameters was constructed, and its performance was assessed using the area under the receiver operating characteristic curve (AUC) and compared by using the DeLong test. The time-dependent diffusion MRI parameters were validated based on correlation with pathologic measurements. Results The analysis included 408 participants with breast cancer (mean age, 51.9 years ± 9.1 [SD]). Of these, 221 participants were administered neoadjuvant chemotherapy and 54 (24.4%) achieved pCR. The time-dependent diffusion MRI parameters showed reasonable performance in helping to identify luminal A (AUC, 0.70), luminal B (AUC, 0.78), and triple-negative breast cancer (AUC, 0.72) subtypes and high performance for human epidermal growth factor receptor 2 (HER2)-enriched breast cancer (AUC, 0.85), outperforming ADC measurements (all P < .05). Progesterone receptor status (odds ratio [OR], 0.08; P = .02), HER2 status (OR, 3.36; P = .009), and the cellularity index (OR, 0.01; P = .02) were independently associated with the odds of achieving pCR. The combined model showed high performance for predicting pCR (AUC, 0.88), outperforming ADC measurements and the clinical-pathologic model (AUC, 0.73 and 0.79, respectively; P < .001). The time-dependent diffusion MRI-estimated parameters correlated well with the pathologic measurements (n = 100; r = 0.67-0.81; P < .001). Conclusion Time-dependent diffusion MRI-based microstructural mapping was an effective method for helping to predict molecular subtypes and pCR to neoadjuvant chemotherapy in participants with breast cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Partridge and Xu in this issue.

The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker.

The apparent diffusion coefficient (ADC) provides a quantitative measure of water mobility that can be used to probe alterations in tissue microstructure due to disease or treatment. Establishment of the accepted level of variance in ADC measurements for each clinical application is critical for its successful implementation. The Diffusion-Weighted Imaging Biomarker Committee of the Quantitative Imaging Biomarkers Alliance (QIBA) has recently advanced the ADC Profile from the consensus to clinically feasible stage for the brain, liver, prostate, and breast. This profile distills multiple studies on ADC repeatability and describes detailed procedures to achieve stated performance claims on an observed ADC change within acceptable confidence limits. In addition to reviewing the current ADC Profile claims, this report has used recent literature to develop proposed updates for establishing metrology benchmarks for mean lesion ADC change that account for measurement variance. Specifically, changes in mean ADC exceeding 8% for brain lesions, 27% for liver lesions, 27% for prostate lesions, and 15% for breast lesions are claimed to represent true changes with 95% confidence. This report also discusses the development of the ADC Profile, highlighting its various stages, and describes the workflow essential to achieving a standardized implementation of advanced quantitative diffusion-weighted MRI in the clinic. The presented QIBA ADC Profile guidelines should enable successful clinical application of ADC as a quantitative imaging biomarker and ensure reproducible ADC measurements that can be used to confidently evaluate longitudinal changes and treatment response for individual patients.

MR staging of rectal cancer: Comparison between the 2012 and 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) Guidelines

PurposeTo compare the adherence of the interpretation and reporting staging system, respectively proposed in the 2012 and 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) Guidelines for Magnetic Resonance Imaging (MRI) staging of rectal cancer, focusing on the improvement offered by the criteria introduced by 2016 ESGAR guidelines. MethodFifty-six patients affected by rectal cancer were included; 25/56 patients underwent upfront surgery; 31 underwent to neo-adjuvant chemo-radiotherapy before surgery. All patients underwent 3 T MRI examination for local staging. All MR exams were evaluated by two radiologists with 20- and 4-years’ experience, who were blinded to each other; the T and N stages, the Mesorectal Fascia (MRF) status and the Extramural Vascular Invasion (EMVI) were assessed according to both 2012 and 2016 ESGAR guidelines. The correlation between radiological and pathological findings, as well as the MRI staging were evaluated. ResultsAs to the expert reviewer, no significant differences were found by comparing the MR T and N stages, T and N restaging, MRF status and EMVI according to 2012 and 2016 ESGAR guidelines. As to the 4-years’ experience radiologist the MR staging agreement between 2012 and 2016 guidelines was “moderate” in N-stage evaluation and “fair” in T-restaging evaluation. No significant discrepancies were found for other parameters. ConclusionsMRI is a reliable method in rectal cancer staging/restaging. The assessment of T-restaging is improved by adopting the 2016 ESGAR guidelines, especially for non-expert readers; this result could be justified by the introduction of diffusion-weighted imaging. On the contrary, the newest guidelines do not improve the diagnostic performance in assessing nodal staging and restaging.

MRI-based radiomics for stratifying recurrence risk of early-onset rectal cancer: a multicenter study

Early-onset rectal cancer (EORC) is characterized by a unique disease process with different clinicopathological features compared with late-onset rectal cancer (LORC). Research on the risk of recurrence in EORC patients, however, is limited. We aim to develop a predictive model to accurately predict EORC recurrence risk. Rectal cancer patients who underwent radical surgery and T2-weighted imaging and diffusion-weighted imaging magnetic resonance imaging (MRI) were retrospectively enrolled from three medical institutions from November 2012 to November 2018. Differences in clinicopathological characteristics between EORC and LORC were compared. Five prediction models for disease-free survival were constructed based on clinicopathological variables and five radiomic features from pretreatment MRI of the EORC. A fixed cut-off value calculated in the training set was used to stratify EORC patients into high-risk and low-risk groups of post-operative recurrence. Model performance was evaluated by concordance index (C-index) and receiver operating characteristic curve. A total of 264 EORC patients (median age, 43 years, 163 males) and 778 LORC patients (median age, 62 years, 520 males) were enrolled. Pretreatment positive carcinoembryonic antigen [hazard ratio (HR)= 2.84, P= 0.006], pathological positive lymph node status (pN positive) [HR= 2.86, P= 0.011] and MRI-based radiomics score [HR= 2.72, P < 0.001] are independent risk factors for disease-free survival in EORC patients. The EORC-ClinPathRadiom model, constructed by integrating the clinicopathological characteristics and MRI-based radiomics features of EORC, showed C-index of 0.82, 0.82, and 0.81 in the training, internal, and external test sets, respectively. This model effectively stratified EORC patients into high risk and low risk of recurrence (HRs for the training, internal, and external test sets were 8.96, 6.81, and 7.46, respectively). The EORC-ClinPathRadiom model can effectively predict and stratify the risk of post-operative recurrence in EORC patients.

Role of diffusion weighted imaging in assessment of anterior cruciate ligament pathology

Background. The anterior cruciate ligament (ACL) is a structure that is vital to preserving the knee's normal stability. However, because the ACL is the ligament that sustains injuries the most frequently, it is essential to distinguish between complete and incomplete tears in order to treat patients with incomplete tears without surgery. To diagnose cruciate ligament tears, knee joint magnetic resonance imaging (MRI) is frequently used. But sometimes it's difficult because edema may hide the ligament fibers. ADC mapping may be useful to confirm whether or not the ligament is continuous for an appropriate diagnosis of incomplete tears because it has been demonstrated that ligament fibers are better visible on diffusion weighted imaging (DWI) and ADC mapping. Objective. To ascertain how anterior cruciate ligament (ACL) tears are diagnosed and classified as partial or complete using diffusion-weighted (DW) magnetic resonance imaging (MRI) and to compare it with conventional MRI sequences. Results. For partial tears, 10 cases (50%) were identified using arthroscopy/follow-up, while observer 1 identified 12 cases (60%) and observer 2 identified 9 cases (45%) using DWI/ADC. For complete tears, 10 cases (50%) were identified using arthroscopy/follow-up, while observer 1 identified 8 cases (40%) and observer 2 identified 11 cases (55%) using DWI/ADC. Conclusions. DWI and ADC are useful tools for diagnosing tears, particularly complete tears, but that caution should be exercised when using these techniques to diagnose partial tears.

Characterization of Classic Meningioma with Use of Conventional Magnetic Resonance and Diffusion Tensor Imaging

Introduction: The conventional magnetic resonance imaging (MRI) method is widely considered ‘with limited success’ in differentiating the meningioma types but may fail to localize the tumor occupation of white-matter fiber bundles accurately. Diffusion tensor imaging (DTI) is considered as an imaging modality that may elucidate the microstructure of brain tumors. We provide characteristics of meningioma using DTI-based-three-dimensional tracing of white matter to portray meningioma in a noninvasive approach and its structural contact to contiguous tumors and elucidate the influence of occupying lesions on white-matter fiber bundles. Case Presentation: A 28-year-old female presented with visuospatial disturbances and persistent headaches for 2 years. Conventional and advanced MRI studies were performed. Diffusion-weighted Images (DWI) and Apparent Diffusion Coefficient (ADC) values were measured in the lesion using routine MRI sequences. Advanced MRI using DTI was also performed. Conventional MRI outcomes showed tumor parenchyma, peritumoral edema, and compression on the circumnavigated brain tissue. There was hyperintense on DW trace image and isointense on ADC map. On T2-weighted image (T2WI) and Fluid-Attenuated Inversion Recovery (FLAIR) images, there was an increased signal intensity that demonstrated an extra-axial lesion, while T1-weighted imaging signals showed hypointensity. DTI fractional anisotropy (FA) marker is an unclear optic radiation in the concerned area, indicating the shift or destruction of the optic radiation. The mean FA values of solid-enhancing areas of meningioma were 0.28 ± 0.17. Mean ADC values (103 mm2/s) were 0.764 ± 0.172. Conclusions: Classic meningioma in this case has low intratumoral FA and high ADC. DTI displayed that intratumoral microscopic water motion is disorganized.

Association Between Stroke Lesion Size and Atrial Fibrillation Detected After Stroke: An Observational Cohort Study.

Atrial fibrillation detected after stroke (AFDAS) is considered to be a distinct entity influenced by cardiogenic and neurogenic factors. We hypothesized that patients with AFDAS have larger stroke lesions than patients without atrial fibrillation (AF) and with known AF (KAF). Consecutive patients with magnetic resonance imaging-confirmed acute ischemic stroke admitted to a university hospital between October 2020 and January 2023 were prospectively registered. We categorized patients as AFDAS, no AF or KAF upon hospital discharge. We manually segmented diffusion-weighted imaging lesions to determine lesion volume. We analyzed 1420 patients (median age, 78; 47.2% women, median National Institutes of Health Stroke Scale score, 3; median hospital stay, 5 days). Of these, 81 had AFDAS (5.7%), 329 had KAF (23.2%) and 1010 had no AF (71.1%). Lesion volume was larger in patients with AFDAS (median, 5.4 mL [interquartile range, 1.0-21.6]) compared with patients with no AF and KAF (median, 0.7 [interquartile range,0.2-4.4] and 2.0 [interquartile range,0.3-11.1] mL, respectively; both P<0.001). Lesion volume was independently associated with AFDAS compared with no AF (adjusted odds ratio, 1.37 [95% CI, 1.20-1.58] per log mL) and KAF (adjusted odds ratio, 1.22 [95% CI, 1.07-1.41] per log mL). Patients in the highest lesion volume quartile (>6.5 mL) were more likely to be diagnosed with AFDAS compared with the lowest quartile (<0.22 mL, 13.6% versus 2.1%; adjusted odds ratio, 5.88 [95% CI, 2.30-17.40]). These associations were more pronounced when excluding 151 patients with nonembolic lesion pattern and similar when excluding 199 patients with KAF on oral anticoagulation. Larger stroke lesions were independently associated with AFDAS diagnosis during index stroke hospitalization highlighting a potential neurogenic contribution to AFDAS pathogenesis.

Glymphatic dysfunction in multiple sclerosis and its association with disease pathology and disability.

The role of the glymphatic system in multiple sclerosis (MS)-related disability remains underexplored. Diffusion-tensor image analysis along the perivascular space (DTI-ALPS) offers a non-invasive method to assess glymphatic function. To evaluate glymphatic function in MS patients with lower and higher disability. This study included 118 MS patients who underwent structural, diffusion-weighted imaging, and clinical assessment. The participants were divided into lower (MS-L, n = 57) and higher disability (MS-H, n = 61) subgroups. Brain parenchymal fraction (BPF), lesion load (LL), and DTI-ALPS index were measured. Subgroup differences and correlations between DTI-ALPS index and other measures were explored. Logistic regression was performed to evaluate BPF, LL, and DTI-ALPS index in classifying lower and higher disability patients. Significant differences in DTI-ALPS index between MS-H and MS-L (d = -0.71, false discovery rate-corrected p-value (p-FDR) = 0.001) were found. The DTI-ALPS index correlated significantly with disease duration (rp = -0.29, p-FDR = 0.002) and EDSS (rsp = -0.35, p-FDR = 0.0002). It also showed significant correlations with BPF and LL. DTI-ALPS index and LL were significant predictors of disability subgroup (DTI-ALPS: odds ratio (OR) = 1.77, p = 0.04, LL: OR = 0.94, p = 0.02). Our findings highlight DTI-ALPS index as an imaging biomarker in MS, suggesting the involvement of glymphatic impairment in MS pathology, although further research is needed to elucidate its role in contributing to MS-related disability.

Role of diffusion-weighted imaging in the diagnosis of pituitary region tumors.

This study aimed to assess the role of Diffusion-Weighted Imaging (DWI) in routine pituitary Magnetic Resonance Imaging (MRI) protocols for distinguishing sellar and parasellar tumors, addressing the lack of clear guidelines in contemporary literature. A retrospective analysis of 242 pituitary MRI scans with DWI sequences was conducted in a single-center study using a 1.5T scanner and standard DWI sequence parameters. Measurements of both absolute and relative mean apparent diffusion coefficient (ADC) values, along with minimal ADC values within tumors, were performed. The adopted region of interest (ROI) based method used for these measurements was validated. Invasive pituitary adenomas exhibited significantly lower min ADC and min rADC than meningiomas, with optimal cut-off points of 0.64 (sensitivity 73%, specificity 82%) and 0.78 (sensitivity 73%, specificity 89%), respectively. Post-hemorrhagic pituitary adenomas demonstrated lower ADC values than adamantinomatous craniopharyngiomas, with an AUC of 0.893 for min rADC = 1.07, and Rathke's Cleft Cysts with mucous content, AUC 0.8 for min rADC = 1.01. Specific differentiation with high sensitivity and specificity based on diffusion parameters was observed for these tumor groups. Cystic pituitary non-functional adenomas obtained significantly lower ADC values compared to the adamantinomatous type of craniopharyngiomas and serous Rathke's Cleft Cysts (AUC up to 0.942). The study concludes that integrating DWI into routine pituitary MRI protocols enhances diagnostic accuracy in distinguishing sellar and parasellar tumors. The short scan time of one minute makes DWI a valuable and precise tool, supporting its recommendation as a standard component of pituitary MRI examinations.

Midlife dynamics of white matter architecture in lexical production

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53–54. Middle-aged adults may initially adopt a “semantic strategy” to compensate for lexical production challenges, but this strategy seems compromised later (ages 55–60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

Advancing gastrointestinal stromal tumor management: The role of imagomics features in precision risk assessment.

Gastrointestinal stromal tumors (GISTs) vary widely in prognosis, and traditional pathological assessments often lack precision in risk stratification. Advanced imaging techniques, especially magnetic resonance imaging (MRI), offer potential improvements. This study investigates how MRI imagomics can enhance risk assessment and support personalized treatment for GIST patients. To assess the effectiveness of MRI imagomics in improving GIST risk stratification, addressing the limitations of traditional pathological assessments. Analyzed clinical and MRI data from 132 GIST patients, categorizing them by tumor specifics and dividing into risk groups. Employed dimension reduction for optimal imagomics feature selection from diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), and contrast enhanced T1WI with fat saturation (CE-T1WI) fat suppress (fs) sequences. Age, lesion diameter, and mitotic figures significantly correlated with GIST risk, with DWI sequence features like sphericity and regional entropy showing high predictive accuracy. The combined T1WI and CE-T1WI fs model had the best predictive efficacy. In the test group, the DWI sequence model demonstrated an area under the curve (AUC) value of 0.960 with a sensitivity of 80.0% and a specificity of 100.0%. On the other hand, the combined performance of the T1WI and CE-T1WI fs models in the test group was the most robust, exhibiting an AUC value of 0.834, a sensitivity of 70.4%, and a specificity of 85.2%. MRI imagomics, particularly DWI and combined T1WI/CE-T1WI fs models, significantly enhance GIST risk stratification, supporting precise preoperative patient assessment and personalized treatment plans. The clinical implications are profound, enabling more accurate surgical strategy formulation and optimized treatment selection, thereby improving patient outcomes. Future research should focus on multicenter studies to validate these findings, integrate advanced imaging technologies like PET/MRI, and incorporate genetic factors to achieve a more comprehensive risk assessment.

Can combined tomosynthesis with unenhanced MRI be used as a predictive tool for lymphovascular invasion?

BackgroundThe presence of lymphovascular invasion (LVI) in cases with breast cancer is considered a bad prognostic sign. The purpose of this study is to compare the efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) versus unenhanced magnetic resonance imaging (UE-MRI + DBT) in predicting LVI in women with pathologically confirmed breast cancer.MethodsThis prospective self-controlled study enrolled a total of 70 cases of pathologically proven breast cancer. All the patients underwent tomosynthesis, non-contrast, and post-contrast MRI. Depending on the broken halo sign seen in tomosynthesis, peritumoral edema, dark rim diffusion at diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) values evaluated in MRI.ResultsThe accuracy of LVI detection by tomosynthesis was 58%; unenhanced and enhanced MRI had the same results at 60%. The accuracy of detecting LVI was raised to 64% by combining the tomosynthesis results with unenhanced MRI.ConclusionsTomosynthesis parameters are promising tools in detecting LVI in breast cancer with better diagnostic accuracy in combination with unenhanced MRI.

Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI

BackgroundPhysiologic MRI-based tumor habitat analysis has the potential to predict patient outcomes by identifying the spatiotemporal habitats of glioblastoma. This study aims to prospectively validate the cut-off for tumor progression obtained from tumor habitat analysis based on physiologic MRI in ascertaining time-to-progression (TTP) and the site of progression in glioblastoma patients following concurrent chemoradiotherapy (CCRT).MethodsIn this prospective study (ClinicalTrials.gov ID: NCT02613988), we will recruit patients with IDH-wild type glioblastoma who underwent CCRT and obtained immediate post-operative and three serial post-CCRT MRI scans within a three-month interval, conducted using diffusion-weighted imaging and dynamic susceptibility contrast imaging. Voxels from cerebral blood volume and apparent diffusion coefficient maps will be grouped using k-means clustering into three spatial habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue). The spatiotemporal habitats of the tumor will be evaluated by comparing changes in each habitat between the serial MRI scans (post-operative and post-CCRT #1, #2, and #3). Associations between spatiotemporal habitats and TTP will be analyzed using cox proportional hazard modeling. The site of progression will be matched with spatiotemporal habitats.DiscussionThe perfusion- and diffusion-derived tumor habitat in glioblastoma is expected to stratify TTP and may serve as an early predictor for tumor progression in patients with IDH wild-type glioblastoma.Trial registrationClinicalTrials.gov ID: NCT02613988.

Fotemustine in recurrent high‑grade glioma: MRI neuro‑radiological findings.

The use of fotemustine (FTM) has been authorized in certain countries for the treatment of recurrent high-grade gliomas (HGG) after Stupp therapy. However, to the best of our knowledge, no studies have assessed changes in magnetic resonance imaging (MRI) during treatment with FTM monotherapy. The aim of the present study was to assess the neuroradiological findings in a cohort of patients with recurrent HGG treated with FTM monotherapy. Patients with HGG already undergoing the Stupp protocol were retrospectively included. MRIs (pre- and post-FTM treatment) were analyzed by two neuroradiologists in consensus: Volume and diffusion values of the contrast-enhanced component were measured on T1-weighted volumetric sequences after gadolinium injection and on apparent diffusion coefficient (ADC) maps, respectively. A total of 19 patients [median age, 49 years; interquartile range (IQR), 43-57 years] were included, 17 of whom had glioblastoma and 2 had astrocytoma isocitrate dehydrogenase-mutated grade 4. The median duration of FTM therapy was 4 months (IQR, 2-6 months). The median tumor volume measured on the contrast-enhanced component was 2,216 mm3 (IQR, 768-13,169 mm3) at baseline and 9,217 mm3 (IQR, 3,455-16,697 mm3) at the end of treatment, with a median change of +38% (IQR, -45-+574%). A total of seven patients showed a volume decrease. ADC value analysis of the enhancement area demonstrated no significant difference between the pre- and the post-FTM treatment periods (P=0.36); however, in three patients, the decreases in ADC levels were particularly marked. In conclusion, the present study described a series of patients with recurrent HGG treated with FTM in monotherapy, demonstrating a prevalent increase in lesion enhancement and three cases of marked restrictions on diffusion-weighted imaging. Further prospective studies are required to corroborate such preliminary results.

Multi-sequence MRI-based radiomics model to preoperatively predict the WHO/ISUP grade of clear Cell Renal Cell Carcinoma: a two-center study

ObjectivesTo develop radiomics models based on multi-sequence MRI from two centers for the preoperative prediction of the WHO/ISUP grade of Clear Cell Renal Cell Carcinoma (ccRCC).MethodsThis retrospective study included 334 ccRCC patients from two centers. Significant clinical factors were identified through univariate and multivariate analyses. MRI sequences included Dynamic contrast-enhanced MRI, axial fat-suppressed T2-weighted imaging, diffusion-weighted imaging, and in-phase/out-of-phase images. Feature selection methods and logistic regression (LR) were used to construct clinical and radiomics models, and a combined model was developed using the Rad-score and significant clinical factors. Additionally, seven classifiers were used to construct the combined model and different folds LR was used to construct the combined model to evaluate its performance. Models were evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC), and decision curve analysis (DCA). The Delong test compared ROC performance, with p < 0.050 considered significant.ResultsMultivariate analysis identified intra-tumoral vessels as an independent predictor of high-grade ccRCC. In the external validation set, the radiomics model (AUC = 0.834) outperformed the clinical model (AUC = 0.762), with the combined model achieving the highest AUC (0.855) and significantly outperforming the clinical model (p = 0.003). DCA showed that the combined model had a higher net benefit within the 0.04–0.54 risk threshold range than clinical model. Additionally, the combined model constructed using logistic regression has a higher priority compared to other classifiers. Additionally, 10-fold cross-validation with LR for the combined model showed consistent AUC values (0.849–0.856) across different folds.ConclusionThe radiomics models based on multi-sequence MRI might be a noninvasive and effective tool, demonstrating good efficacy in preoperatively predicting the WHO/ISUP grade of ccRCC.