Diffusion-weighted Magnetic Resonance Imaging Research Articles

Quantitative evaluation of placental microvascular blood flow and microstructure in fetal growth restriction with IVIM MRI.

Intravoxel incoherent motion (IVIM) MRI uses diffusion-weighted (DW) MRI acquisitions to evaluate the microvascular and cellular environments of tissue. Due to these properties, IVIM has been increasingly utilized to evaluate abnormal placentation. Our primary objective was to compare IVIM parameters in the placenta of patients with fetal growth restriction and appropriate for gestational age controls across gestational ages. Our secondary aim was to quantify IVIM parameters in fetal versus maternal placental aspects to evaluate microvascular and parenchymal differences. With IRB approval, pregnant individuals with a diagnosis of fetal growth restriction (n=24) and controls (n=22) were retrospectively analyzed. DW-MRI data were collected at 1.5 T with nine b-values (range, 0 s/mm2 to 1,000 s/mm2). Data were processed by one non-blinded reader to obtain mean perfusion fraction (f), pseudo-diffusion coefficient (D*), their product fD*, and diffusion coefficient (D) in maternal and fetal aspects of the placenta, defined by bisecting the thickness of the placenta. Repeated measures of two-way ANOVAs were used to compare IVIM parameters in fetal and maternal placental aspects between participant groups. Correlations between IVIM parameters and gestational age were also evaluated in both groups. The average gestational age at MRI was 27±4 weeks for both groups. The percentile estimated fetal weight was 5.4±5.9% for the fetal growth restriction group and 42.8±28.5% for controls (P<0.001). The parameters D* and fD*, related to microvascular blood flow and tissue perfusion, were significantly lower in participants with fetal growth restriction compared to controls (D*, 40.5 vs. 52.4×10-3 mm2/s, P=0.043; fD*, 14.7 vs. 21.0×10-3 mm2/s, P=0.019). No other differences were observed, nor associations between gestational age and IVIM parameters in either group. Our results suggest reduced microvascular flow in placentas of patients with fetal growth restriction compared to controls.

Diffusion weighted imaging to predict longer term response in Crohn's disease patients commencing biological therapy: Results from the MOTILITY Trial.

Predicting longer term response to biological therapy for small bowel Crohn's disease (SBCD) is an unmet clinical need. Diffusion-weighted MR imaging (DWI) may indicate disease activity, but its predictive ability, if any, is unknown. We investigated the prognostic value of DWI for one year response or remission (RoR) in SBCD patients commencing biologic therapy, including incremental value over C-reactive protein (CRP) and faecal calprotectin (FC). A subset of participants in a prospective, multicentre study investigating the predictive ability of motility MRI for one-year RoR in patients starting biologic therapy for active SBCD, underwent additional DWI at baseline and post-induction (12-30 weeks). CRP and FC were collected in a subgroup. RoR at one year was evaluated using clinical and morphological MRE parameters. We calculated sensitivity and specificity to predict RoR and Quality of life (QoL) at one year, comparing apparent diffusion coefficient (ADC) value, Clermont score and CRP using multivariable logistic regression. 25 participants were included (mean 36.9 years, 32% female). ADC changes and Clermont score had poor sensitivity (30.0% [95%CI: 6.7-65.2] and 40.0% [95%CI: 12.2-73.8] respectively) and poor-to-modest specificity (50.0 [95%CI: 27.2-72.8] and 65.0% [95%CI: 40.8-84.6]) for RoR. None of Clermont score, CRP or FC predicted QoL. DWI has inadequate sensitivity and specificity for RoR at one year. There is no significant incremental prognostic value of DWI over CRP and FC to predict RoR and/or QoL at one year. Early post-induction DWI has no prognostic value for RoR at one year.

Co-occurrence of exercise-induced acute kidney injury and rhabdomyolysis in a holding cell at a police station: a case report.

We present a rare case of a patient with co-occurring exercise-induced acute kidney injury(AKI) and rhabdomyolysis. A 67-year-old man was referred to our department with AKI. Five days before referral, the patient had sudden-onset loin pain while banging and kicking on a door in a holding cell at a police station. Diffusion-weighted magnetic resonance imaging showed wedge-shaped areas of signal hyperintensity in both kidneys. Serum and urinary myoglobin levels were mildly elevated. Kidney biopsy showed cellular injury of the tubular epithelial cells and myoglobin casts in the tubules. The patient was diagnosed with exercise-inducedAKI and mild rhabdomyolysis and was treated conservatively. His kidney function improved gradually withno need for hemodialysis. This case report exhibits a unique presentation of the co-occurrence of exercise-induced AKIand rhabdomyolysis after intense anaerobic and aerobic exercise. To the best of our knowledge, this is the first report to pathologically demonstrate co-occurring exercise-induced AKI and rhabdomyolysis.

Clinical study of colorViz fusion image vascular grading based on multi-phase CTA reconstruction in acute ischemic stroke

ObjectiveThis study aimed to evaluate the diagnostic value of ColorViz fused images from multi-phase computed tomography angiography (mCTA) using GE Healthcare’s FastStroke software for newly diagnosed cerebral infarctions in patients with acute ischemic stroke (AIS).MethodsA total of 106 AIS patients with unilateral anterior circulation occlusion were prospectively enrolled. All patients underwent mCTA scans during the arterial peak phase, venous peak phase, and venous late phase. The vascular information from these mCTA phases was combined into a time-varying color-coded image using GE Healthcare’s FastStroke software. All participants also underwent magnetic resonance diffusion-weighted imaging (MR-DWI) within three days. The diagnostic capability of the mCTA ColorViz fusion images for identifying newly diagnosed intracranial infarction was assessed using MR-DWI as the gold standard, focusing on the degree of delayed vascular perfusion and the number of visible blood vessels.ResultsThe mCTA ColorViz fusion images revealed ischemic changes in brain tissue, demonstrating a sensitivity of 88.7% for superficial infarctions and 48.5% for deep infarctions. Additionally, the subjective vascular grading score of the mCTA ColorViz fusion images showed a strong negative correlation with the infarct area identified by MR-DWI (r = − 0.6, P < 0.001).ConclusionThe mCTA ColorViz fusion images produced by FastStroke software provide valuable diagnostic insights for newly diagnosed cerebral infarction in AIS patients. The sensitivity of these images is notably higher for superficial infarctions compared to deep ones. This technique allows for relatively accurate detection of the ischemic extent and the likelihood of infarction in the superficial regions where lesions are located.

Longitudinal investigation of neurobiological changes across pregnancy

Pregnancy is a period of profound biological transformation. However, we know remarkably little about pregnancy-related brain changes. To address this gap, we chart longitudinal changes in brain structure during pregnancy and explore potential mechanisms driving these changes. Ten participants (Mean age = 28.97 years) are assessed 1–6 times (median = 3) during their pregnancy. Each visit includes anatomical and diffusion-weighted MRI, and assessments of waking salivary hormones, hair hormones, and inflammatory cytokines. Here we observe a reduction in gray matter volume and an increase in neurite density index (NDI), a proxy of axon density, in white matter tracts across pregnancy. Progesterone levels are associated with reductions in brain volumetric measurements, and both progesterone and estradiol levels are linked to increases in NDI in white matter tracts. This study highlights the profound neurobiological changes experienced by pregnant individuals and provides insights into neuroplasticity in adulthood.

Immune checkpoint inhibitor-related diabetes mellitus associated with high signal intensity in diffusion-weighted magnetic resonance imaging of the pancreas at an early clinical stage.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment but can give rise to immune-related adverse events such as ICI-related diabetes mellitus (DM). We herein present the case of a 59-year-old Japanese man with malignant melanoma who developed ICI-related DM after 18 months of nivolumab treatment. He experienced marked hyperglycemia and diabetic ketoacidosis without a personal or family history of diabetes. Laboratory findings revealed initial preservation of insulin secretion but a rapid decline in C-peptide levels in the absence of islet autoantibodies. He was therefore diagnosed with ICI-related DM. This case fulfilled the criteria for fulminant type 1 DM but lacked the typical human leukocyte antigen alleles associated with conventional type 1 diabetes. No metastasis or morphological changes were apparent on CT scans of the pancreas, and magnetic resonance cholangiopancreatography did not show dilation or interruption of the main pancreatic duct. However, diffusion-weighted magnetic resonance imaging revealed high signal intensity with low apparent diffusion coefficient values in the pancreas, likely indicative of fibrosis or infiltration of inflammatory cells. This case underscores that ICI-related DM should be considered a potential immune-related adverse event as well as pointing to the benefit of diffusion-weighted imaging for assessment of pancreatic involvement at an early stage of the disease.

Topographic Axes of Wiring Space Converge to Genetic Topography in Shaping Human Cortical Layout.

Genetic information is involved in the gradual emergence of cortical areas since the neural tube begins to form, shaping the heterogeneous functions of neural circuits in the human brain. Informed by invasive tract-tracing measurements, the cortex exhibits marked interareal variation in connectivity profiles, revealing the heterogeneity across cortical areas. However, it remains unclear about the organizing principles possibly shared by genetics and cortical wiring to manifest the spatial heterogeneity across cortex. Instead of considering a complex one-to-one mapping between genetic coding and interareal connectivity, we hypothesized the existence of a more efficient way that the organizing principles are embedded in genetic profiles to underpin the cortical wiring space. Leveraging vertex-wise tractography in diffusion-weighted MRI, we derived the global connectopies in both female and male to reliably index the organizing principles of interareal connectivity variation in a low-dimensional space, which captured three dominant topographic patterns along the dorsoventral, rostrocaudal, and mediolateral axes of the cortex. More importantly, we demonstrated that the global connectopies converge with the gradients of a vertex-by-vertex genetic correlation matrix on the phenotype of cortical morphology and the cortex-wide spatiomolecular gradients. By diving into the genetic profiles, we found that the critical role of genes scaffolding the global connectopies was related to brain morphogenesis and enriched in radial glial cells before birth and excitatory neurons after birth. Taken together, our findings demonstrated the existence of a genetically determined space that encodes the interareal connectivity variation, which may give new insights into the links between cortical connections and arealization.Significance Statement Genetic factors have involved the gradual emergence of cortical areas since the neural tube begins to form, shaping the specialization of neural circuitry in the human brain. However, the mechanisms through which genetics encode the complex interareal connectivity remain a pivotal and unanswered question in the field of neuroscience. Here, we hypothesized that a genetically determined space encoding the interareal connectivity variation exists, which may give new insights into the links between cortical connections and arealization. We combined diffusion tractography with a dimension reduction framework to unravel the underlying global topographic principle revealed by the anatomical connections.

Plasma proteomic biomarkers as mediators or moderators for the association between poor cardiovascular health and white matter microstructural integrity: The UK Biobank study.

The plasma proteome's mediating or moderating roles in the association between poor cardiovascular health (CVH) and brain white matter (WM) microstructural integrity are largely unknown. Data from 3953 UK Biobank participants were used (40-70 years, 2006-2010), with a neuroimaging visit between 2014 and 2021. Poor CVH was determined using Life's Essential 8 (LE8) and reversing standardized z-scores (LE8z _rev). The plasma proteome was examined as a potential mediator or moderator of LE8z _rev's effects on quantitative diffusion-weighted magnetic resonance imaging (dMRI) metrics. LE8z_rev was significantly associated with deteriorated WM microstructural integrity, as reflected by lower tract-averaged fractional anisotropy (dMRI-FAmean), (β±standared error (SE): -0.00152±0.0003, p<0.001) and higher tract-averaged orientation dispersion (dMRI-ODmean), (β±SE:+0.00081±0.00017, p<0.001). Ten strongly mediating plasma proteins of 1463 were identified, with leptin as the principal driver. Poor CVH is linked to poor WM microstructural integrity measures (lower FAmean and higher ODmean), mostly mediated through leptin. Up to 3953 UK Biobank participants were selected for this study. Poor cardiovascular health (CVH) was determined using Life's Essential 8. The plasma proteome was examined as a potential mediator or moderator of poor CVH's effect on dMRI metrics. Ten plasma proteins were identified with strong mediating effects, with leptin being the principal driver.

Age-Trajectories of Higher-Order Diffusion Properties of Major Brain Metabolites in Cerebral and Cerebellar Gray Matter Using InVivo Diffusion-Weighted MR Spectroscopy at 3T.

Healthy brain aging involves changes in both brain structure and function, including alterations in cellular composition and microstructure across brain regions. Unlike diffusion-weighted MRI (dMRI), diffusion-weighted MR spectroscopy (dMRS) can assess cell-type specific microstructural changes, providing indirect information on both cell composition and microstructure through the quantification and interpretation of metabolites' diffusion properties. This work investigates age-related changes in the higher-order diffusion properties of total N-Acetyl-aspartate (neuronal biomarker), total choline (glial biomarker), and total creatine (both neuronal and glial biomarker) beyond the classical apparent diffusion coefficient in cerebral and cerebellar gray matter of healthy human brain. Twenty-five subjects were recruited and scanned using a diffusion-weighted semi-LASER sequence in two brain regions-of-interest (ROI) at 3T: posterior-cingulate (PCC) and cerebellar cortices. Metabolites' diffusion was characterized by quantifying metrics from both Gaussian and non-Gaussian signal representations and biophysical models. All studied metabolites exhibited lower apparent diffusivities and higher apparent kurtosis values in the cerebellum compared to the PCC, likely stemming from the higher microstructural complexity of cellular composition in the cerebellum. Multivariate regression analysis (accounting for ROI tissue composition as a covariate) showed slight decrease (or no change) of all metabolites' diffusivities and slight increase of all metabolites' kurtosis with age, none of which statistically significant (p > 0.05). The proposed age-trajectories provide benchmarks for identifying anomalies in the diffusion properties of major brain metabolites which could be related to pathological mechanisms altering both the brain microstructure and cellular composition.

Diffusion-weighted MRI of advanced gastric cancer: correlations of the apparent diffusion coefficient with Borrmann classification, proliferation and aggressiveness.

This study aimed to compare apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) of different Borrmann types of advanced gastric cancer (AGC) and correlate these ADC values with Ki-67 expression and serum CEA levels in AGC. A total of 84 patients with AGC who underwent DWI of the upper abdomen before tumor resection in our hospital between June 2014 and July 2018 were included in the present study. DWI was obtained with a single-shot echo planar imaging sequence in the axial plane (b values: 0, 100, 700 and 1000s/mm2). Mean ADC values were calculated from tumor regions. Postoperatively, specimens were used to determine Borrmann type (1-4). Then, ADC values for AGCs categorized by Borrmann type were compared by one-way analysis of variance with Bonferroni correction for multiple comparisons. Subsequently, associations between ADC values and Ki-67 expression and serum CEA levels were evaluated by Spearman's correlation analysis. The mean ADC value for Borrmann type 3 AGC was significantly lower compared to the mean ADC value for Borrmann type 2 AGC (p < 0.01). There were significant negative correlations between ADC values and Ki-67 scores (r = -0.639, p < 0.001), and between ADC values and serum CEA levels (r = -0.575, p < 0.001). DWI can help characterize Borrmann types of AGC. ADC values may reflect Ki-67 expression and serum CEA levels in patients with AGC, and have utility as a non-invasive indicator for evaluating the aggressiveness and prognosis of AGC.

Soma and neurite density abnormalities of paramagnetic rim lesions and core-sign lesions in multiple sclerosis.

In multiple sclerosis (MS), susceptibility-weighted imaging (SWI) may reveal white matter lesions (WML) with a paramagnetic rim ("paramagnetic rim lesions" [PRLs]) or diffuse hypointensity ("core-sign lesions"), reflecting different stages of WML evolution. Using thesoma and neurite density imaging (SANDI) model on diffusion-weighted magnetic resonance imaging (MRI), we characterized microstructural abnormalities of MS PRLs and core-sign lesions and their clinical relevance. Forty MS patients and 20 healthy controls (HC) underwent a 3T brain MRI. Using SANDI, the fractions of neurite (fneurite) and soma (fsoma) and size of soma (rsoma) were quantified in PRLs (including their core and rim separately), and core-sign lesions identified on SWI-phase. Among 1811 WMLs, 122 (6.7%) core-sign lesions and 97 (5.4%) PRLs were identified. Compared to HC and MS normal-appearing white matter, all MS WML showed significantly lower fneurite and fsoma and higher rsoma (FDR-p < 0.001). Compared to SWI-isointense WML, core-sign lesions showed a significantly higher fneurite, and lower fsoma and rsoma (FDR-p ≤ 0.005). Compared to SWI-isointense WML and core-sign lesions, PRLs showed a significantly lower fneurite, higher fsoma, and higher rsoma (FDR-p ≤ 0.001). The PRL-core showed significantly lower fneurite, and higher rsoma than PRL-rim (FDR-p < 0.001). Lower PRL fneurite (β ≤ -0.006, FDR-p ≤ 0.015) and higher rsoma (β ≥ 0.032, FDR-p ≤ 0.024) were significantly associated with a longer disease duration and more severe disability. In PRLs, the significant and clinically relevant neurite loss and increased soma fraction and size possibly reflect increased astrogliosis and activated microglia. Core-sign lesions exhibit milder axonal loss, microglia density and astrogliosis, supporting their less destructive nature.

Audiovisual Breathing Guidance for Improved Image Quality and Scan Efficiency of T2- and Diffusion-Weighted Liver MRI

Objectives Impaired image quality and long scan times frequently occur in respiratory-triggered sequences in liver magnetic resonance imaging (MRI). We evaluated the impact of an in-bore active breathing guidance (BG) application on image quality and scan time of respiratory-triggered T2-weighted (T2) and diffusion-weighted imaging (DWI) by comparing sequences with standard triggering (T2S and DWIS) and with BG (T2BG and DWIBG). Materials and Methods In this prospective study, random patients with clinical indications for liver MRI underwent 3 T MRI with standard and BG acquisitions. The audiovisual BG application received the respiratory signal from the scanner, and animated breathing instructions were displayed using a mirror and screen behind the MRI bore. Prior to the DWIBG and T2BG acquisition, patients received a short video instruction about MRI with BG. Suitable parameters for desired breathing pattern for T2BG and DWIBG were set individually for each patient based on the patient's physical respiratory ability (ie, 4 seconds breathing followed by 4.5 seconds breath holding). Artifacts, sharpness, lesion conspicuity, and overall image quality were assessed using a Likert scale from 1 (nondiagnostic) to 5 (excellent). Scan time, apparent contrast-to-noise ratio, and apparent signal-to-noise ratio (aSNR) for all sequences were analyzed. Paired t test and Wilcoxon test were used for statistical analysis. Results Thirty-two patients (mean age: 55 ± 13 years, 13 female) were included. T2BG showed less artifacts (4.5 ± 0.7 vs 4.1 ± 0.8, P &lt; 0.001) and better sharpness, lesion conspicuity, and overall image quality (eg, overall image quality 4.6 ± 0.7 vs 4.4 ± 0.7, P = 0.004) compared with T2S. DWIBG demonstrated improved image quality in all categories compared with DWIS (eg, overall image quality 4.5 ± 0.5 vs 4.3 ± 0.5, P = 0.005) and less artifacts (4.1 ± 0.5 vs 3.8 ± 0.7, P = 0.007). Scan times of T2BG (286 ± 23 vs 345 ± 68 seconds, P &lt; 0.001) and DWIBG (160 ± 4 vs 252 ± 70 seconds, P &lt; 0.001) were reduced by 17% and 37%, respectively. aSNR and apparent contrast-to-noise ratio (eg, aSNR: 23.45 ± 11.31 [T2BG] vs 25.84 ± 10.76 [T2S]; P = 0.079) were similar for both sequences for both approaches. Conclusions Active BG for respiratory-triggered liver T2w and DWI sequences led to significant reduction of breathing artifacts, improved image quality, and shorter scan time compared with standard acquisitions.

Predictive Value of Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging and Diffusion-Weighted Imaging Findings for Sentinel Lymph Node Metastasis in Early-Stage Invasive Breast Cancer.

This retrospective study aimed to evaluate the predictive value of the preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) findings of mass lesions for predicting sentinel lymph node (SLN) metastasis in early breast cancer. A total of 310 patients with suspicious mass lesions detected in preoperative MRI who subsequently underwent surgery and SLN biopsy (SLNB) between September 2015 and September 2022 were analyzed. The relationship between DCE-MRI and DWI findings and SLNB positivity was analyzed. SLNB was positive for SLN metastasis in 108 of 310 lesions. Younger age (p = 0.001) and larger lesion size (p < 0.001) were found to be associated with SLNB positivity. Findings associated with SLN metastasis included peritumoral edema in 53%, adjacent vessel sign (AVS) in 81%, and increased whole-breast vascularity (WBV) in 58% of patients with positive SLNB (p < 0.001). The SLNB positivity rate was higher in mass lesions with DCE-MRI findings of heterogenous enhancement pattern (p = 0.003), medium or rapid initial phase enhancement (p = 0.001), and washout delayed phase kinetic curve (p = 0.001). It was found that lower tumoral apparent diffusion coefficient (ADC) values (p = 0.003) and higher peritumoral/tumoral ADC ratios (p = 0.018) increased the probability of encountering SLN metastasis. Patient age, presence of peritumoral edema, presence of AVS, increased WBV, and initial phase kinetic curve of the lesions on MRI were found to be associated with SLN metastasis. We found that younger age and MR findings obtained from the perilesional area of breast cancer may be helpful in the preoperative prediction of SLN metastasis.

Joint k-b space diffusion-weighted image reconstruction and apparent diffusion coefficient fitting for diffusion-weighted turbo-spin-echo imaging.

Diffusion-weighted (DW) turbo-spin-echo (TSE) imaging offers improved geometric fidelity compared to single-shot echo-planar-imaging (EPI). However, it suffers from low signal-to-noise ratio (SNR) and prolonged acquisition times, thereby restricting its applications in diagnosis and MRI-guided radiotherapy (MRgRT). To develop a joint k-b space reconstruction algorithm for concurrent reconstruction of DW-TSE images and the apparent diffusion coefficient (ADC) map with enhanced image quality and more accurate quantitative measurements. The joint k-b reconstruction model was formulated as an optimization problem subject to a self-consistency condition comprising the exponential decay relationship between DW images and the ADC map. The objective function included a data fidelity term confirming an agreement between the reconstructed images and measured k-space data, incorporating the mono-exponential decay relationship between DW images and ADC map as a constraint, along with spatial regularization terms on both amplitude and phase images. The optimization problem was solved using the alternating-direction method of multipliers (ADMM). We evaluated the performance of the joint reconstruction (JR) algorithm for DW-TSE in a phantom study and patient studies on five brain and head/neck cancer patients. Image distortion, accuracy, and repeatability of ADC measurements were assessed and compared with those from conventional Fourier-transformed (FFT)-based reconstruction and magnitude-based ADC fitting methods, as well as with the clinically used DW-EPI technique. The proposed joint k-b reconstruction method demonstrated improved SNR and enhanced accuracy of ADC measurements in DW-TSE compared to the conventional method. Additionally, JR-DW-TSE with fewer averages at high b-values provided better image quality than the conventional FFT-reconstructed DW-TSE with full averages. The proposed joint k-b reconstruction method for DW-TSE has the potential to deliver distortion-robust diffusion-weighted MRI (DWI) for clinical applications, which is particularly crucial for MRgRT.

Diffusion-weighted MRI-Derived ADC and tumor volume as predictive imaging markers for neoadjuvant chemotherapy response in muscle-invasive bladder cancer

BackgroundThis prospective study tested the hypothesis that the apparent diffusion coefficient (ADC) value and tumor volume (TV) measured in diffusion-weighted magnetic resonance imaging (DW-MRI) before, during, and after the treatment are quantitative imaging markers to assess tumor response in muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemotherapy (NAC).MethodsMulti-parametric MRI was prospectively done for MIBC patients at 3 time points. Pre-treatment ADC value, pre-treatment TV, as well as, percent of changes (ΔADC%, and ΔTV%) in these parameters at mid- and post-treatment relative to baseline were calculated and compared between the patients with and without clinical complete response (CR). Also, further analysis was carried out based on the groups of patients with and without overall response (OR). Two different methods of ADC estimation including single-slice ADC measurement (ADCsingle-slice) and whole-lesion ADC measurement (ADCwhole-lesion) were used.ResultsA total of 50 eligible patients were included in the analysis. Of these, 20 patients (40%) showed clinical CR to treatment, while 30 (60%) did not. Our results showed that although there was no significant difference between the two groups of patients with and without CR in terms of mid-treatment ΔADC% and mid-treatment ΔTV%, significant differences were observed in terms of the pre-treatment ADC (p < 0.01), pre-treatment TV (p < 0.001), post-treatment ΔADC% (p < 0.05), and post-treatment ΔTV% (p < 0.05). The results of the OR-based analysis were in line with the CR-based results. There was also a strong and significant correlation between ADCsingle-slice and ADCwhole-lesion measurements (r > 0.9, P < 0.001).ConclusionPre-treatment ADC, pre-treatment TV, post-treatment ΔADC%, and post-treatment ΔTV% could be considered as promising quantitative imaging markers of tumor response in MIBC patients undergoing NAC. Moreover, mid-treatment ΔADC% and mid-treatment ΔTV% should not be used as predictors of tumor response in these patients. Further larger studies are required to confirm these results.

Deep Learning to Simulate Contrast-Enhanced MRI for Evaluating Suspected Prostate Cancer.

Background Multiparametric MRI, including contrast-enhanced sequences, is recommended for evaluating suspected prostate cancer, but concerns have been raised regarding potential contrast agent accumulation and toxicity. Purpose To evaluate the feasibility of generating simulated contrast-enhanced MRI from noncontrast MRI sequences using deep learning and to explore their potential value for assessing clinically significant prostate cancer using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Materials and Methods Male patients with suspected prostate cancer who underwent multiparametric MRI were retrospectively included from three centers from April 2020 to April 2023. A deep learning model (pix2pix algorithm) was trained to synthesize contrast-enhanced MRI scans from four noncontrast MRI sequences (T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, and apparent diffusion coefficient maps) and then tested on an internal and two external datasets. The reference standard for model training was the second postcontrast phase of the dynamic contrast-enhanced sequence. Similarity between simulated and acquired contrast-enhanced images was evaluated using the multiscale structural similarity index. Three radiologists independently scored T2-weighted and diffusion-weighted MRI with either simulated or acquired contrast-enhanced images using PI-RADS, version 2.1; agreement was assessed with Cohen κ. Results A total of 567 male patients (mean age, 66 years ± 11 [SD]) were divided into a training test set (n = 244), internal test set (n = 104), external test set 1 (n = 143), and external test set 2 (n = 76). Simulated and acquired contrast-enhanced images demonstrated high similarity (multiscale structural similarity index: 0.82, 0.71, and 0.69 for internal test set, external test set 1, and external test set 2, respectively) with excellent reader agreement of PI-RADS scores (Cohen κ, 0.96; 95% CI: 0.94, 0.98). When simulated contrast-enhanced imaging was added to biparametric MRI, 34 of 323 (10.5%) patients were upgraded to PI-RADS 4 from PI-RADS 3. Conclusion It was feasible to generate simulated contrast-enhanced prostate MRI using deep learning. The simulated and acquired contrast-enhanced MRI scans exhibited high similarity and demonstrated excellent agreement in assessing clinically significant prostate cancer based on PI-RADS, version 2.1. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Neji and Goh in this issue.

Left posterior superior temporal gyrus and its structural connectivity in schizophrenia.

The left posterior superior temporal gyrus (pSTG) is thought to be involved in the pathophysiology and core symptoms of schizophrenia, although its structural connectivity has not yet been systematically investigated. Here, we aimed to evaluate its white matter (WM) connectivity with Broca's area, the thalamus, and the right pSTG. Eighty-three patients with schizophrenia and 141 healthy controls underwent diffusion-weighted imaging and T1-weighted three-dimensional magnetic resonance imaging. Probabilistic tractography was performed from the left pSTG to the Broca area, the left thalamus, and the right pSTG. Group comparison of WM fractional anisotropy (FA) in these pathways, as well as its correlations with the pSTG volume and clinical characteristics in the patient group, were examined. Patients showed significantly lower FA in the left pSTG-Broca and left-right pSTG pathways, but not in the left pSTG-thalamus pathway. Patients also revealed a trend toward a smaller left pSTG volume. Significant negative correlations were found in patients between FA in the left-right pSTG pathway and the left pSTG volume, and between FA in the left pSTG-Broca pathway and positive symptom severity. The present results suggest fiber-specific alterations in structural connectivity linked to the left pSTG, possibly supporting the "inner speech" and "interhemispheric disconnection" hypotheses of schizophrenia.

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience.

Large diffusion-weighted brain MRI (dMRI) studies in neonates are crucial for developmental neuroscience. Our aim was to investigate the utility of ComBat, an empirical Bayes tool for multisite harmonization, in removing site effects from white matter (WM) dMRI measures in healthy infants born at 37 gestational weeks+ 0 days-42 weeks+ 6 days from the Theirworld Edinburgh Birth Cohort (n = 86) and Developing Human Connectome Project (n = 287). Skeletonized fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AD, RD) maps were harmonized. Differences between voxel-wise metrics, skeleton means and histogram widths (5th-95th percentile) were assessed before and after harmonization, as well as variance associated with gestational age at birth and scan. Before harmonization, large cohort differences were observed. Harmonization removed all voxel-wise differences from MD maps and all metric means and histogram widths, however small voxel-wise differences (<1.5 % of voxels) remained in FA, AD and RD. We detected significant relationships between GA at birth and all metrics. When comparing single site and multisite harmonized datasets of equal sample sizes, harmonized data resulted in smaller standardized regression coefficients. ComBat could enable unprecedented sample sizes in developmental neuroscience, offering new horizons for biomarker discovery and validation, understanding typical and atypical brain development, and assessing neuroprotective therapies.

Evolving Evidence Practices in Acute Stroke Care

Acute ischemic stroke care is experiencing a transformative shift, driven by emerging evidence supporting optimized thrombolytic strategies, extended treatment windows, and advanced imaging protocols. Recent clinical trials have demonstrated the non-inferiority—and, in certain aspects, superiority—of tenecteplase over alteplase. With its simplified single bolus administration, enhanced fibrin specificity, and potential for improved recanalization rates, tenecteplase is increasingly recognized as a preferred first-line thrombolytic agent in many treatment algorithms. Additionally, streamlined treatment protocols have contributed to reduced door-in and door-out times for patients requiring transfer to higher-level centers for endovascular stroke interventions. The conventional 4.5-hour thrombolysis window is also being redefined. Advanced imaging techniques, such as CT perfusion and diffusion-weighted MRI, now enable the identification of salvageable brain tissue beyond standard time constraints. These technologies have facilitated the safe and effective administration of thrombolytics in carefully selected patients, extending the treatment window to as much as 9 hours post-symptom onset. Wake-up stroke, historically excluded from thrombolytic treatment due to uncertainty around symptom onset time, is now being successfully addressed through imaging-based protocols. Landmark trials, including WAKE-UP and EXTEND, have demonstrated the efficacy and safety of IV thrombolysis in patients showing imaging evidence of salvageable brain tissue, even without a known onset time. Further advancements include the integration of innovative tools, such as electronic fundoscopy, which has improved the timely detection and management of central retinal artery occlusion, ensuring faster intervention and better outcomes for these high-risk patients. Despite these significant advancements, challenges persist in translating evidence into practice. Barriers such as equitable access to advanced imaging, variability in protocol adoption, and healthcare system preparedness continue to impact stroke care delivery. This presentation will synthesize the latest evidence, share clinical insights, and outline practical strategies derived from the experience of an integrated healthcare system in Northern California, comprising 21 stroke centers. Key focus areas include the adoption of tenecteplase over alteplase, leveraging tele-stroke technology for real-time acute care consultation, extending thrombolysis treatment windows, implementing electronic fundoscopy, and optimizing wake-up stroke management protocols.

Microstructural mapping of neural pathways in Alzheimer's disease using macrostructure-informed normative tractometry.

Diffusion-weighted magnetic resonance imaging (dMRI) is sensitive to the microstructural properties of brain tissues and shows great promise in detecting the effects of degenerative diseases. However, many approaches analyze single measures averaged over regions of interest without considering the underlying fiber geometry. We propose a novel macrostructure-informed normative tractometry (MINT) framework to investigate how white matter (WM) microstructure and macrostructure are jointly altered in mild cognitive impairment (MCI) and dementia. We compared MINT-derived metrics with univariate diffusion tensor imaging (DTI) metrics to examine how fiber geometry may impact the interpretation of microstructure. In two multisite cohorts from North America and India, we find consistent patterns of microstructural and macrostructural anomalies implicated in MCI and dementia; we also rank diffusion metrics' sensitivity to dementia. We show that MINT, by jointly modeling tract shape and microstructure, has the potential to disentangle and better interpret the effects of degenerative disease on the brain's neural pathways. Changes in diffusion tensor imaging metrics may be due to macroscopic changes. Normative models encode normal variability of diffusion metrics in healthy controls. Variational autoencoder applied on tractography can learn patterns of fiber geometry. WM microstructure and macrostructure are modeled with multivariate methods. Transfer learning uses pretraining and fine-tuning for increased efficiency.