Diffusion-weighted Magnetic Resonance Imaging Research Articles

Preoperative prediction of IDH genotypes and prognosis in adult-type diffuse gliomas: intratumor heterogeneity habitat analysis using dynamic contrast-enhanced MRI and diffusion-weighted imaging

BackgroundIntratumor heterogeneity (ITH) is a key biological characteristic of gliomas. This study aimed to characterize ITH in adult-type diffuse gliomas and assess the feasibility of using habitat imaging based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) to preoperatively predict isocitrate dehydrogenase (IDH) genotypes and prognosis.MethodsSixty-three adult-type diffuse gliomas with known IDH genotypes were enrolled. Volume transfer constant (Ktrans) and apparent diffusion coefficient (ADC) maps were acquired from DCE-MRI and DWI, respectively. After tumor segmentation, the k-means algorithm clustered Ktrans and ADC image voxels to generate spatial habitats and extract quantitative image features. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to evaluate IDH predictive performance. Multivariable logistic regression models were constructed and validated using leave-one-out cross-validation, and the contrast-enhanced subgroup was analyzed independently. Kaplan-Meier and Cox proportional hazards regression analyses were used to investigate the relationship between tumor habitats and progression-free survival (PFS) in the two IDH groups.ResultsThree habitats were identified: Habitat 1 (hypo-vasopermeability and hyper-cellularity), Habitat 2 (hypo-vasopermeability and hypo-cellularity), and Habitat 3 (hyper-vasopermeability). Compared to the IDH wild-type group, the IDH mutant group exhibited lower mean Ktrans values in Habitats 1 and 2 (both P < 0.001), higher volume (P < 0.05) and volume percentage (pVol, P < 0.01) of Habitat 2, and lower volume and pVol of Habitat 3 (both P < 0.001). The optimal logistic regression model for IDH prediction yielded an AUC of 0.940 (95% confidence interval [CI]: 0.880–1.000), which improved to 0.948 (95% CI: 0.890–1.000) after cross-validation. Habitat 2 contributed the most to the model, consistent with the findings in the contrast-enhanced subgroup. In IDH wild-type group, pVol of Habitat 2 was identified as a significant risk factor for PFS (high- vs. low-pVol subgroup, hazard ratio = 2.204, 95% CI: 1.061–4.580, P = 0.034), with a value below 0.26 indicating a 5-month median survival benefit.ConclusionsHabitat imaging employing DCE-MRI and DWI may facilitate the characterization of ITH in adult-type diffuse gliomas and serve as a valuable adjunct in the preoperative prediction of IDH genotypes and prognosis.Clinical trial numberNot applicable.

Enhanced preoperative prediction of breast lesion pathology, prognostic biomarkers, and molecular subtypes using multiple models diffusion-weighted MR imaging

This study aims to comprehensively evaluate the clinical utility of five diffusion models, including conventional mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential (SEM), and continuous-time random-walk (CTRW), for preoperatively predicting of breast lesion pathology, prognostic biomarkers, and molecular subtypes. We retrospectively analyzed 132 patients with pathologically verified breast lesions (41 benign and 91 malignant) who underwent a full protocol preoperative breast MRI protocol, including a diffusion-weighted imaging (DWI) sequence with nine b values (0 to 2000 s/mm2) on a 3.0T MR scanner. The diffusion parameters from each model—Mono (ADC), IVIM (D, D*, f), DKI (MD, MK), SEM (DDC, α) and CTRW (Dm, α, β)—were quantitatively calculated and compared between benign and malignant breast lesions, as well as across different prognostic biomarker statuses in breast cancer, using Mann–Whitney U-tests. For molecular subtypes comparisons, we employed the Kruskal-Wallis test followed by Bonferroni. All parameters, except IVIM-D*, significantly differentiated benign from malignant lesions. Notably, IVIM-D and DKI-MK values were significantly different between estrogen receptor (ER)-positive and ER-negative tumors. Progesterone receptor (PR)-positive cancers exhibited lower Mono-ADC, IVIM-D, DKI-MD, SEM-DDC, CTRW-Dm, and CTRW-α values, alongside higher DKI-MK value compared to PR-negative cancers (p < 0.05). Significant differences in IVIM-D, IVIM-D*, and DKI-MK values were observed between human epidermal growth factor receptor 2 (HER2)-negative and HER2-positive tumors. Furthermore, higher SEM-α and CTRW-β values, along with lower DKI-MD and SEM-DDC values, were noted in the high Ki-67 expression group compared to the low Ki-67 group (p < 0.05). All five diffusion models proved valuable for breast cancer diagnosis, with the CTRW model exhibiting the highest diagnostic performance, although the difference was not statistically significant. The diffusion parameters derived from these models can effectively assist in distinguishing prognostic factors and molecular subtypes of breast cancer.

Multiparametric quantitative diffusion weighted magnetic resonance imaging can effectively predict the response to neoadjuvant therapy in borderline resectable pancreatic ductal adenocarcinoma.

To investigate whether multiparametric quantitative diffusion weighted magnetic resonance imaging (DWI) can effectively predict the neoadjuvant therapy (NAT) response in borderline resectable pancreatic ductal adenocarcinoma (BRPC). The clinicopathological data, including tumor size, location, and CA19-9 values, as well as DWI parameters(ADC, D, and f values) from 72 patients with BRPC, were analyzed. The differences and changes in these factors before and after NAT were compared to identify those most accurately reflect the response to NAT. ROC analysis was used to evaluate the diagnostic efficacy, and Kaplan-Meier survival analysis explored the relationship between DWI parameters and prognosis. Subgroup survival analysis to further identify populations potentially benefiting from NAT based on multiparametric DWI. After-NAT, the response group showed significantly higher ADC and D values and lower f values compared to the non-response group. The ΔADC (OR: 12.24, P=0.013) emerged as the most important independent factor for tumor response, demonstrating the highest diagnostic accuracy for NAT response with an AUC of 0.936. Kaplan-Meier showed the high ADC value group, high D value group and low f value group were associated with better prognosis after NAT; and the ΔADC≥0 group, ΔD≥0 group, and Δf<0 group was significantly associated with better prognosis. In addition, subgroup analysis suggested two groups of patients might potentially benefit from NAT. Multiparametric quantitative DWI may offer valuable insights into the efficacy and prognosis of NAT in BRPC. These findings have the potential to support the evaluation and decision-making process for patients undergoing NAT.

EORTC1527/JCOG1609INT/ESSO02: Diffusion-weighted magnetic resonance imaging (DW-MRI) assessment of initially unresectable liver metastasis to improve surgical planning (DREAM)—Primary analysis.

257 Background: Disappearing liver metastases (DLMs) diagnosed on post-chemotherapy (Cx) computed tomography (CT) is a favorable prognostic factor in patients (pts) with colorectal liver metastases (CRLM). However, the optimal treatment of DLMs - whether they should be resected or left behind - is controversial. This is a prospective, multi-centred, international study examining the added value of MRI (DWI, T1/T2 and contrast-enhanced) to that of CT alone in accurate assessment of the viability of DLMs. Methods: Pts with initially unresectable CRLM downstaged to a planned liver resection after Cx were enrolled, based on the obligatory decision of a multidisciplinary team. Pts were imaged by both CT and MRI at baseline and presurgical timepoints. DLMs were defined as disappeared lesions diagnosed by CT alone, while confirmed DLMs (cDLMs) were defined as lesions that disappeared on both CT and MRI. cDLMs were either resected or followed-up for 2 years if not resected. All imaging scans were collected centrally for quality assurance. The primary endpoint was the negative predictive value (NPV) of MRI and CT in confirming the status of cDLMs using either pathological complete response or the absence of a local recurrence at the site of cDLMs during the 2 year follow up. The study was aimed at excluding a NPV ≤0.85 with a 1-sided alfa of 5% and power of 90% under the alternative that the NPV ≥0.95. The planned sample size was 92 evaluable (resected or left behind) cDLMs, assuming a within-patient correlation between cDLMs of 0.2 and an average number of 2 cDLMs per pt. Results: 233 pts were registered at 22 participating centres, and 112 were enrolled for analysis. A median of 8 cycles of Cx was delivered, and pts had a median of 7 CRLMs at baseline. A total of 203 cDLMs were identified while the number of DLMs diagnosed by CT was 296. Of these, 152 cDLMs and 227 DLMs, respectively, were evaluable according to the imaging protocol. Intraoperative ultrasound was performed for 195 cDLMs and, of these, 59 (30.2%) were still detected. The rate of R0/R1 resection was 95.5%. The NPV of evaluable cDLMs either resected or left behind was 62.5 % (95/152, 95% CI:50.8-74.2), which was lower than the prespecified threshold. The NPV of DLMs was 52.9% (119/227, 95% CI:42.7, 63.0). The NPV of resected cDLMs, and those left behind were 56.8% (50/88, 95% CI: 44.2, 69.5) and 70.3% (45/64, 95% CI: 48.6 -92.0), respectively. For DLMs, the NPV of resected DLMs and those left behind were 45.6% (72/158, 95% CI: 35.4-55.7) and 69.6% (48/69, 95% CI: 47.7-91.5), respectively. Conclusions: For pts with initially unresectable CRLM, cDLMs diagnosed by both CT and MRI do not correspond to tumor viability, even after highly effective chemotherapy. Ongoing survival analysis (to be presented at the annual meeting) may impact the treatment strategy of pts with DLMs. Clinical trial information: NCT02781935 .

Image-guided patient-specific prediction of interstitial fluid flow and drug transport in solid tumors.

Tumor fluid dynamics and drug delivery simulations in solid tumors are highly relevant topics in clinical oncology. The current study introduces a novel method combining computational fluid dynamics (CFD) modeling, quantitative magnetic resonance imaging (MRI; including dynamic contrast-enhanced (DCE) MRI and diffusion-weighted (DW) MRI), and a novel ex-vivo protocol to generate patient-specific models of solid tumors in four patients with peritoneal metastases. DCE-MRI data were analyzed using the extended Tofts model to estimate the spatial distribution of tumor capillary permeability using the Ktrans parameter. DW-MRI data analysis provided a 3D representation of drug diffusivity, and DW-MRI coupled to an ex-vivo measurement protocol informed the spatial heterogeneity of the hydraulic conductivity of tumor tissue. The patient-specific data were subsequently incorporated into a computational fluid dynamics (CFD) model to simulate individualized tumor perfusion and drug transport maps. The results on interstitial fluid flow demonstrated noticeable heterogeneity of interstitial fluid pressure and velocity within the tumor, along with heterogeneous drug penetration profiles among different tumors, even with a similar drug administration regimen.

Co-stimulating the left vmPFC compensates for apathy after levodopa withdrawal in Parkinson's patients with STN DBS.

Subthalamic nucleus deep brain stimulation (STN DBS) improves motor symptoms of Parkinson's disease (PD), but its effect on motivation is controversial. Apathy, the lack of motivation, commonly occurs in PD and is often exacerbated after surgery and its concomitant levodopa reduction. Apathy and reward processing are associated with the ventromedial prefrontal cortex (vmPFC), which standard targeting strategies avoid by targeting the dorsolateral STN. Since apathy can be a levodopa-responsive PD symptom, levodopa withdrawal could unmask apathy without sufficient stimulation of non-motor pathways, similar to the persistence of motor symptoms when motor pathways are underengaged with DBS. Using an individualized tractography model, maximized left-sided vmPFC engagement following a DBS adjustment improved apathy in a case example. We, therefore, retrospectively investigated the moderating role of stimulation-related left-sided vmPFC connectivity and levodopa reduction on changes in apathy after STN DBS (N=28). We measured apathy (Starkstein Apathy Scale) and levodopa dose pre- and post-surgery. Stimulation-related connectivity was quantified using patient-specific diffusion-weighted MRI and probabilistic tractography to test the interaction with levodopa reduction. Effective DBS of the dorsolateral STN included prefrontal non-motor connections. We found a significant interaction between levodopa dose change and STN-connections to the left vmPFC. Apathy severity negatively correlated with stimulation-related connectivity to the left vmPFC in patients with greater levodopa reductions. Apathy change was unrelated to motor pathway connectivity. Insufficient stimulation of the left vmPFC and associated limbic fronto-subthalamic connections combined with high levodopa reduction contributed to DBS-related apathy in PD, which may inspire novel personalized non-motor targeting strategies.

Imaging biomarkers of cortical neurodegeneration underlying cognitive impairment in Parkinson's disease.

Imaging biomarkers bear great promise for improving the diagnosis and prognosis of cognitive impairment in Parkinson's disease (PD). We compared the ability of three commonly used neuroimaging modalities to detect cortical changes in PD patients with mild cognitive impairment (PD-MCI) and dementia (PDD). 53 cognitively normal PD patients (PD-CN), 32 PD-MCI, and 35 PDD underwent concurrent structural MRI (sMRI), diffusion-weighted MRI (dMRI), and [18F]FDG PET. We extracted grey matter volumes (sMRI), mean diffusivity (MD, dMRI), and standardized uptake value ratios ([18F]FDG PET) for 52 cortical regions included in a neuroanatomical atlas. We assessed group differences using ANCOVA models and further applied a cross-validated machine learning approach to identify the modality-specific brain regions that are most indicative of dementia status and assessed their diagnostic accuracy for group separation using receiver operating characteristic analyses. In sMRI, atrophy of temporal and posterior-parietal areas allowed separating PDD from PD-CN (AUC = 0.77 ± 0.07), but diagnostic accuracy was poor for separating PD-MCI from PD-CN (0.57 ± 0.10). dMRI showed most pronounced diffusivity changes in the medial temporal lobe, which provided excellent diagnostic performance for PDD (AUC = 0.87 ± 0.06), and a more modest but still significant performance for PD-MCI (AUC = 0.71 ± 0.09). Finally, [18F]FDG PET revealed pronounced hypometabolism in posterior-occipital regions, which provided the highest diagnostic accuracies for both PDD (AUC = 0.89 ± 0.05) and PD-MCI (AUC = 0.78 ± 0.05). In statistical comparisons, both [18F]FDG PET (p < 0.001) and dMRI (p < 0.031) outperformed sMRI for detecting PDD and PD-MCI. Among the tested modalities, [18F]FDG PET was most accurate for detecting cortical changes associated with cognitive impairment in PD, especially at early stages. Diffusion measurements may represent a promising MRI-based alternative.

The Role of Apparent Diffusion Coefficient (ADC) in Differentiating Between Benign and Malignant Breast Lesions in a Sample of Iranian Women

Background: Breast cancer is the most prevalent cancer among women, emphasizing the need for early detection and accurate diagnosis. This study investigates the role of the Apparent Diffusion Coefficient (ADC) in distinguishing between benign and malignant breast lesions using Magnetic Resonance Imaging (MRI) and Diffusion-Weighted Imaging (DWI). A retrospective cross-sectional study was conducted involving 96 patients with breast lesions who underwent MRI and DWI scans. Methods: Patients were selected from among those who had MRI and DWI scans with b-values of 0, 800, and 1000 s/mm². ADC values were calculated by plotting the Region of Interest (ROI) and extracting corresponding values. Histological evaluations confirmed the diagnosis of the lesions. Statistical analyses included calculating accuracy, sensitivity, and specificity, along with Receiver Operating Characteristic (ROC) curve analysis to determine the optimal cut-off value. Results: The ADC values demonstrated an accuracy of 92.5%, sensitivity of 93.2%, and specificity of 91.2% in differentiating between benign and malignant lesions. The ROC curve analysis established a cut-off value of 1.44 × 10⁻³ mm²/s for effective differentiation. Conclusion: ADC values can serve as a reliable biomarker for distinguishing breast lesions, potentially reducing unnecessary biopsies for benign cases and aiding clinicians in treatment decisions. The integration of ADC measurements into clinical practice could enhance patient management in breast cancer. Further research is warranted to validate these findings and explore additional markers to improve diagnostic accuracy in breast cancer management.

Effects of psilocybin on mouse brain microstructure.

There is surging interest in the therapeutic potential of psychedelic compounds like psilocybin in the treatment of psychiatric illnesses like major depressive disorder (MDD). Recent studies point to the rapid antidepressant effect of psilocybin; however, the biological mechanisms underlying these differences remain unknown. This study determines the feasibility of using diffusion MRI to characterize and define the potential spatiotemporal microstructural differences in the brain following psilocybin treatment in C57BL/6J male mice. 11-15 week-old C57BL/6J male mice were randomized to receive psilocybin, 6F-DET (6-fluoro-N,Ndiethyltryptamine), or saline and ex vivo imaged 24h (n=18) and 72h (n=18) post treatment. A one-way ANOVA with multiple comparison testing (Bonferroni correction) assessed diffusion metric differences (tractography, DTI, NODDI) between the three groups and was performed in the following regions of interest: amygdala, striatum, hippocampus, thalamus, primary visual cortex area, frontal association cortex, and medial prefrontal cortex at 24h and 72h post drug administration. Psilocybin treated mice demonstrated structural connectivity differences at 72h in the frontal association cortex (compared to saline, mean tract length increases, p=0.03). Psilocybin also induced microstructural differences at 24h post-injection in the primary visual cortex (compared to saline, MD increases, p=0.02) and 72h post-injection in the striatum (compared to saline; MD increases, p= 0.02, NDI decreases, p=0.02) and hippocampus (compared to saline; MD increases, p=0.04, NDI decreases, p=0.02). Diffusion microstructure imaging and white matter tractography are sensitive methods to detect and characterize the neural substrates and microstructural differences accompanying psilocybin treatment. These findings suggest the potential role for diffusion microstructure imaging to quantify the bioeffects of psychedelics like psilocybin on the brain, monitor treatment response, and identify salient clinical endpoints in an emerging therapeutic option for patients with MDD. dMRI= diffusion-weighted MRI; 6F-DET= 6-fluoro-N,N-diethyltryptamine; NODDI= neurite orientation dispersion and density imaging; DTI= diffusion tensor imaging; NDI= neurite density index; ODI= orientation dispersion index; FA= fractional anisotropy; MD= mean diffusivity; MTL= mean tract length; mPFC= medial prefrontal cortex.

Can Pain Neuroscience Education Combined with Cognition-Targeted Exercise Therapy Change White Matter Structure in People with Chronic Spinal Pain? A Randomized Controlled Trial

Background/Objectives: White matter (WM) structural changes have been found in patients with chronic spinal pain (CSP). In these patients, pain neuroscience education followed by cognition-targeted exercise therapy (i.e., the Modern Pain Neuroscience Approach (MPNA)) was shown to be more effective than biomedically-focused education followed by symptom-contingent exercise therapy for improving clinical outcomes. The present study examined whether an MPNA, compared to biomedically-focused treatment, can change WM structure in regions of interest and whether potential WM structural changes are associated with clinical improvements in patients with CSP. Methods: Patients with CSP were randomized into an experimental (MPNA) or control (biomedically-focused) treatment group. Diffusion-weighted Magnetic Resonance Images were acquired pre-treatment, post-treatment, and at 1-year follow-up. WM structure was assessed using diffusion tensor imaging in 8 WM regions of interest, and linear mixed models assessed differences between groups in response to treatment. Results: No significant treatment x time interaction effects were found; however, significant main effects of time were found in 7 WM tracts. Significant main effects of time revealed increased fractional anisotropy (FA), decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in the cingulum hippocampus, and decreased RD and MD in the superior cerebellar peduncle at 1-year follow-up compared to baseline. In contrast, decreased FA and/or increased MD, AD, or RD values were found in other WM tracts (e.g., anterior corona radiata) from pre-treatment to 1-year follow-up. Greater reduction in kinesiophobia was moderately correlated with a smaller decrease in RD in the superior cerebellar peduncle at 1-year follow-up compared to baseline. No other significant associations were found between WM structural changes and clinical improvements. Conclusions: In conclusion, in patients with CSP, regional WM structure changed over time irrespective of prescribed treatment (timespan of 12 months). Further research, including Neurite Orientation Dispersion and Density Imaging and a healthy control group, allowing for a more specific examination of WM microstructural changes in response to multimodal treatment in patients with CSP, is warranted.

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.