Diffusion-weighted Research Articles

Robust multishot diffusion-weighted imaging of the abdomen with region-based shot rejection.

Diffusion-weighted (DW) imaging provides a useful clinical contrast, but is susceptible to motion-induced dephasing caused by the application of strong diffusion gradients. Phase navigators are commonly used to resolve shot-to-shot motion-induced phase in multishot reconstructions, but poor phase estimates result in signal dropout and Apparent Diffusion Coefficient (ADC) overestimation. These artifacts are prominent in the abdomen, a region prone to involuntary cardiac and respiratory motion. To improve the robustness of DW imaging in the abdomen, region-based shot rejection schemes that selectively weight regions where the shot-to-shot phase is poorly estimated were evaluated. Spatially varying weights for each shot, reflecting both the accuracy of the estimated phase and the degree of subvoxel dephasing, were estimated from the phase navigator magnitude images. The weighting was integrated into a multishot reconstruction using different formulations and phase navigator resolutions and tested with different phase navigator resolutions in multishot DW-echo Planar Imaging acquisitions of the liver and pancreas, using conventional monopolar and velocity-compensated diffusion encoding. Reconstructed images and ADC estimates were compared qualitatively. The proposed region-based shot rejection reduces banding and signal dropout artifacts caused by physiological motion in the liver and pancreas. Shot rejection allows conventional monopolar diffusion encoding to achieve median ADCs in the pancreas comparable to motion-compensated diffusion encoding, albeit with a greater spread of ADCs. Region-based shot rejection is a linear reconstruction that improves the motion robustness of multi-shot DWI and requires no sequence modifications.

Affinity of structural white matter tracts between infant and adult pig

BackgroundThe piglet brain has been increasingly used as an excellent surrogate for investigation of pediatric neurodevelopment, nutrition, and traumatic brain injuries. This study intends to establish a piglet brain’s structural connectivity model and compare it with the adult pig, enhancing its application for structurally guided functional analysis. MethodsIn this study, diffusion-weighted (DW)-MRI data from piglets (n=11, 3-week-old) was used to establish piglet model and compare with adult pigs. We employed a data-driven independent component analysis (ICA) method to derive piglet-specific tracts. Pearson correlations and Kullback-Leibler (KL) divergences was employed to identify common tracts and unique tracts for piglet. Common tracts were then used in a blueprint connectome study to highlight differences in regions of interest (ROI). ResultsThe data-driven approach applied to piglet brains revealed 17 common tracts, showing high similarity with adult pigs' white matter (WM) tracts, and identified 3 tracts unique to piglets and 10 negative marker tracts. Additionally, the study highlighted notable differences in 3 ROIs associated with blueprint connectome. Comparing with existing methodsThis study marks a significant shift from surface-based to voxel-based methodologies in analyzing pig brain structural connectivity and generating connectome blueprints. Additionally, it sheds light on the use of the piglet model for developmental studies, offering new perspectives in this area. ConclusionThis study established a piglet brain tract model and conducts a comparative analysis of adult pig’s and piglet’s structural connectivity. These findings underscore the potential use of the piglet brain model in employing piglet model for developmental studies.

Nonlinear Gradient Field Estimation in Diffusion MRI Tensor Simulation.

Gradient nonlinearities not only induce spatial distortion in magnetic resonance imaging (MRI), but also introduce discrepancies between intended and acquired diffusion sensitization in diffusion weighted (DW) MRI. Advances in scanner performance have increased the importance of correcting gradient nonlinearities. The most common approaches for gradient nonlinear field estimations rely on phantom calibration field maps which are not always feasible, especially on retrospective data. Here, we derive a quadratic minimization problem for the complete gradient nonlinear field (L(r)). This approach starts with corrupt diffusion signal and estimates the L(r) in two scenarios: (1) the true diffusion tensor known and (2) the true diffusion tensor unknown (i.e., diffusion tensor is estimated). We show the validity of this mathematical approach, both theoretically and through tensor simulation. The estimated field is assessed through diffusion tensor metrics: mean diffusivity (MD), fractional anisotropy (FA), and principal eigenvector (V1). In simulation with 300 diffusion tensors, the study shows the mathematical model is not ill-posed and remains stable. We find when the true diffusion tensor is known (1) the change in determinant of the estimated L(r) field and the true field is near zero and (2) the median difference in estimated L(r) corrected diffusion metrics to true values is near zero. We find the results of L(r) estimation are dependent on the level of L(r) corruption. This work provides an approach to estimate gradient field without the need for additional calibration scans. To the best of our knowledge, the mathematical derivation presented here is novel.

Magnetic resonance imaging short protocols for intraductal papillary mucinous neoplasm (IPMN) surveillance: The time has come

Background/ObjectivesTo analyze the diagnostic performance of three short magnetic resonance imaging (MRI) protocols for the follow-up of pancratic intraductal papillary mucinous neoplasms (IPMN). MethodsFollow-up MRI examinations of 287 patients with IPMN performed in two centers were retrospectively retrieved. Four MRI protocols were identified as follows: T1-weighted (T1w), T2-weighted (T2w), and MRCP sequences (protocol 1); T1w, T2w, MRCP, and diffusion-weighted (DWI) sequences (protocol 2); T1w, T2w, MRCP, and post-contrast T1w-sequences (protocol 3); and a comprehensive protocol including all previous sequences (protocol 4). Three radiologists with different experience in abdominal imaging expressed their opinion upon the optimal patient's management upon the evaluation of each protocol. Intra-and inter-observer agreement and concordance with the clinical decision expressed by a pancreatic surgeon were calculated with Cohen's kappa test. Results223 patients were included (66±10 years; 92 men, 131 women). 143 patients had branch-duct-IPMNs, 25 main-duct-IPMNs and 55 mixed-type-IPMNs. 79 patients underwent surgery, resulting in 52 high-grade dysplasia (HGD) and 27 low-grade dysplasia (LGD). Concordance for the expert reader between protocols 1, 2 and 3 and the actual clinical decision were 0.63, 0.72, and 0.74 respectively (95% CI, 0.53–0.73, 0.63–0.81, and 0.65–0.83). Inter-observer agreement between reader 1 and reader 2, reader 1 and reader 3, and reader 2 and reader 3 were: 0.71, 0.50, and 0.75 for protocol 1 (95% CI, 0.63–0.81, 0.40–0.60, and 0.66–0.84);0.68, 0.54, and 0.84 for protocol 2 (95% CI, 0.59–0.77, 0.44–0.64, and 0.76–0.91); and 0.77, 0.65, and 0.86 for protocol 3 (95% CI, 0.69–0.86, 0.55–0.74, and 0.80–0.93). ConclusionsShort MRI protocol is suitable for IPMN surveillance.

Motion-induced phase-corrected homodyne reconstruction for partial Fourier single-shot diffusion-weighted echo planar imaging of the liver.

Partial Fourier encoding is popular in single-shot (ss) diffusion-weighted (DW) echo planar imaging (EPI) because it enables a shorter echo time (TE) and, hence, improves the signal-to-noise-ratio. Motion during diffusion encoding causes k-space shifting and dispersion, which compromises the quality of the homodyne reconstruction. This work provides a comprehensive understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data in the presence of motion-induced phase and proposes the motion-induced phase-corrected homodyne (mpc-hdyne) reconstruction method to ameliorate these artifacts. Simulations with different types of motion-induced phase were performed to provide an understanding of the potential artifacts that occur in the homodyne reconstruction of partial Fourier ss-DW-EPI data. To correct for the artifacts, the mpc-hdyne reconstruction is proposed. The algorithm recenters k-space, updates the partial Fourier factor according to detected global k-space shifts, and removes low-resolution nonlinear phase before the conventional homodyne reconstruction. The mpc-hdyne reconstruction is tested on both simulation and in vivo data. Motion-induced phase can cause signal overestimation, worm artifacts, and signal loss in partial Fourier ss-DW-EPI data with the conventional homodyne reconstruction. Simulation and in vivo data showed that the proposed mpc-hdyne reconstruction ameliorated artifacts, yielding higher quality DW images compared with conventional homodyne reconstruction. Based on the understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data, the mpc-hdyne reconstruction was proposed and showed superior performance compared with the conventional homodyne reconstruction on both simulation and in vivo data.

MRI-guided dynamic risk assessment in cervical cancer based on tumor hypoxia at diagnosis and volume response at brachytherapy

Background and purposeImprovements in treatment outcome for patients with locally advanced cervical cancer (LACC) require a better classification of patients according to their risk of recurrence. We investigated whether an imaging-based approach, combining pretreatment hypoxia and tumor response during therapy, could improve risk classification. Material and methodsNinety-three LACC patients with T2-weigthed (T2W)-, dynamic contrast enhanced (DCE)- and diffusion weighted (DW)-magnetic resonance (MR) images acquired before treatment, and T2W- and, for 64 patients, DW-MR images, acquired at brachytherapy, were collected. Pretreatment hypoxic fraction (HFpre) was determined from DCE- and DW-MR images using the consumption and supply-based hypoxia (CSH)-imaging method. Volume regression at brachytherapy was assessed from T2W-MR images and combined with HFpre. In 17 patients with adequate DW-MR images at brachytherapy, the apparent diffusion coefficient (ADC), reflecting tumor cell density, was calculated. Change in ADC during therapy was combined with volume regression yielding functional regression as explorative response measure. Endpoint was disease free survival (DFS). ResultsHFpre was the strongest predictor of DFS, but a significant correlation with outcome was found also for volume regression. The combination of HFpre and volume regression showed a stronger association with DFS than HFpre alone. Patients with disease recurrence were selected to either the intermediate- or high-risk group with a 100 % accuracy. Functional regression showed a stronger correlation to HFpre than volume regression. ConclusionThe combination of pretreatment hypoxia and volume regression at brachytherapy improved patient risk classification. Integration of ADC with volume regression showed promise as a new tumor response parameter.

Enhanced amygdala-anterior cingulate white matter structural connectivity in Sahaja Yoga Meditators.

To study the white matter connections between anterior cingulate cortex, anterior insula and amygdala as key regions of the frontal-limbic network that have been related to meditation. Twenty experienced practitioners of Sahaja Yoga Meditation and twenty nonmeditators matched on age, gender and education level, were scanned using Diffusion Weighted Imaging, using a 3T scanner, and their white matter connectivity was compared using diffusion tensor imaging analyses. There were five white matter fiber paths in which meditators showed a larger number of tracts, two of them connecting the same area in both hemispheres: the left and right amygdalae and the left and right anterior insula; and the other three connecting left anterior cingulate with the right anterior insula, the right amygdala and the left amygdala. On the other hand, non-meditators showed larger number of tracts in two paths connecting the left anterior insula with the left amygdala, and the left anterior insula with the left anterior cingulate. The study shows that long-term practice of Sahaja Yoga Meditation is associated with larger white matter tracts strengthening interhemispheric connections between limbic regions and connections between cingulo-amygdalar and cingulo-insular brain regions related to top-down attentional and emotional processes as well as between top-down control functions that could potentially be related to the witness state perceived through the state of mental silence promoted with this meditation. On the other hand, reduced connectivity strength in left anterior insula in the meditation group could be associated to reduced emotional processing affecting top-down processes.

Variation of b Value for Axial DWI Prostate MR Imaging in Cancer: Which b Value is Optimal?

Background: Diffusion Weighted Imaging (DWI) is a technique that visualizes the movement of water molecules from areas of higher to lower concentration. In DWI sequences, the b-value parameter affects the signal intensity in the images. The objective of this study is to describe the differences in anatomical image information between b-value variations of 1500s/mm2, 2000s/mm2, and 2500s/mm2 in MRI prostate case cancer and to determine the most optimal b-value. Method: This study used a pre-exeachimental approach with a 1.5T Philips MRI machine at a private hospital in South Jakarta from March to April 2023. The sample consisted of 12 Prostate MRI images with DWI sequences and different b-values. Visual grading assessment was eachformed by three radiology specialists, and the data were analyzed using the Friedman test in SPSS. Results: The results showed a significant difference in anatomical image information based on the b-value variations used, with a p-value of 0.05 (0.02). The highest mean rank was obtained from the Friedman test for the b-value of 2000s/mm2. Conclusion: The significant difference in anatomical image information occurred due to differences in signal intensity and noise levels. Prostate cancer tissues appeared more hyperintense with lower noise in images with higher b-values, and vice versa. Additionally, the b-value of 2000s/mm2 resulted in the most optimal signal intensity and noise level. In conclusion, the use of b-value variations in axial DWI images of prostate cancer Prostate MRI to differences in anatomical image information, with the most optimal image information observed at a b-value of 2000s/mm2.

Characterization of renal masses with MRI-based radiomics: assessment of inter-package and inter-observer reproducibility in a prospective pilot study.

To evaluate radiomics features' reproducibility using inter-package/inter-observer measurement analysis in renal masses (RMs) based on MRI and to employ machine learning (ML) models for RM characterization. 32 Patients (23M/9F; age 61.8 ± 10.6years) with RMs (25 renal cell carcinomas (RCC)/7 benign masses; mean size, 3.43 ± 1.73cm) undergoing resection were prospectively recruited. All patients underwent 1.5T MRI with T2-weighted (T2-WI), diffusion-weighted (DWI)/apparent diffusion coefficient (ADC), and pre-/post-contrast-enhanced T1-weighted imaging (T1-WI). RMs were manually segmented using volume of interest (VOI) on T2-WI, DWI/ADC, and T1-WI pre-/post-contrast imaging (1-min, 3-min post-injection) by two independent observers using two radiomics software packages for inter-package and inter-observer assessments of shape/histogram/texture features common to both packages (104 features; n = 26 patients). Intra-class correlation coefficients (ICCs) were calculated to assess inter-observer and inter-package reproducibility of radiomics measurements [good (ICC ≥ 0.8)/moderate (ICC = 0.5-0.8)/poor (ICC < 0.5)]. ML models were employed using reproducible features (between observers and packages, ICC > 0.8) to distinguish RCC from benign RM. Inter-package comparisons demonstrated that radiomics features from T1-WI-post-contrast had the highest proportion of good/moderate ICCs (54.8-58.6% for T1-WI-1min), while most features extracted from T2-WI, T1-WI-pre-contrast, and ADC exhibited poor ICCs. Inter-observer comparisons found that radiomics measurements from T1-WI pre/post-contrast and T2-WI had the greatest proportion of features with good/moderate ICCs (95.3-99.1% T1-WI-post-contrast 1-min), while ADC measurements yielded mostly poor ICCs. ML models generated an AUC of 0.71 [95% confidence interval = 0.67-0.75] for diagnosis of RCC vs. benign RM. Radiomics features extracted from T1-WI-post-contrast demonstrated greater inter-package and inter-observer reproducibility compared to ADC, with fair accuracy for distinguishing RCC from benign RM. Knowledge of reproducibility of MRI radiomics features obtained on renal masses will aid in future study design and may enhance the diagnostic utility of radiomics models for renal mass characterization.

Normal bone marrow signal characteristics in whole-body diffusion-weighted images of amateur marathon runners.

Marathon training can reverse bone marrow conversion; however, little is known about the normal bone marrow whole-body diffusion-weighted imaging (WB-DWI) signal characteristics of amateur marathon runners. If marathon training can cause diffuse hyperintensity of bone marrow on WB-DWI is essential for correctly interpreting the diffusion-weighted (DW) images. This study sought to evaluate the WB-DWI signal characteristics of normal bone marrow in amateur marathon runners. In this prospective cross-sectional study, 30 amateur marathon runners who had trained for over 3 years for regular or half-marathon races and had a running frequency of more than 20 days a month at a distance of more than 100 km per month from the Chengde Marathon Outdoor Sports Association in Hebei, China, and 30 age- and gender-matched, healthy volunteers (the control group) who had no long-term heavy-load sports history were recruited between April 2021 to September 2021. All the subjects underwent WB-DWI (b-value: 0, 800 s/mm2) and lumbar vertebral transverse relaxation time (T2) mapping. The bone marrow WB-DWI signal characteristics were analyzed visually and statistically by chi-square (χ2) tests. The apparent diffusion coefficient (ADC), DWI signal intensity, and T2 values of the bone marrow were quantitatively and statistically analyzed by the independent sample t-test and Mann-Whitney U test. No subjects were excluded from the study. The bone marrow of 30 of the 60 subjects (aged 30-50 years) showed diffuse hyperintensity in the DW images. However, in all 60 subjects, the humeral heads, femoral heads, and great trochanters had low signals. The frequency of diffuse bone marrow DWI hyperintensity was significantly higher in the male amateur marathon runners (50%) than the male controls (5%, P=0.003), but no such significant difference was found between the female amateur marathon runners (100%) and female controls (90%, P>0.99). The DW signal intensity ratios of bone marrow to muscle (SIRBM-muscle) were significantly higher in the male amateur marathon runners than the male controls in the thoracic vertebrae (4.68 vs. 3.57, P=0.021), lumbar vertebrae (4.49 vs. 3.01, P<0.001), sacrum (3.67 vs. 2.62, P=0.002), and hip (3.45 vs. 2.50, P=0.002), but were only significantly higher in the female amateur marathon runners than the female controls in the thoracic vertebrae (7.69 vs. 5.87, P=0.029) and hip (4.76 vs. 3.92, P=0.004). The mean T2 values of the lumbar vertebrae were significantly higher in the male amateur marathon runners than the male controls (116.76 vs. 97.63 ms, P=0.001), but no such significant difference was observed between the female amateur marathon runners and the corresponding controls (118.58 vs. 124.10 ms, P=0.386). Marathon training resulted in diffuse hyperintensity in the bone marrow based on WB-DWI in 50% of the male amateur marathon runners aged 30-50 years. Thus, when WB-DWI is used for bone marrow disease screening, marathon training history should be considered to avoid false-positive diagnoses.

Gait impairment-related axonal degeneration in Parkinson's disease by neurite orientation dispersion and density imaging.

Microstructural alterations in the brain networks of Parkinson's disease (PD) patients are correlated with gait impairments. Evaluate microstructural alterations in the white matter (WM) fiber bundle tracts using neurite orientation dispersion and density imaging (NODDI) technique in PD versus healthy controls (HC). In this study, 24 PD patients and 29 HC were recruited. NODDI and high-resolution 3D structural images were acquired for each participant. The NODDI indicators, including the intracellular neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISO), were compared between the two groups. Diffusion-weighted (DW) images were preprocessed using MRtrix 3.0 software and the orientation distribution function to trace the main nerve fiber tracts in PD patients. Quantitative gait and clinical assessment scales were used to compare the medication "ON" and "OFF" states of PD patients. The NDI, ODI, and ISO values of the WM fiber bundles were significantly higher in PD patients compared to HC. Fiber bundles, including the anterior thalamic radiation, corticospinal tract, superior longitudinal fasciculus, forceps major, cingulum, and inferior longitudinal fasciculus, were found to be significantly affected in PD. The NDI changes of PD patients were well correlated with stride lengths in the "ON" state; ODI changes were correlated with the stride time in the "ON" and "OFF" states and ISO changes were correlated with the stride time and cadence in the "ON" state. In conclusion, combination of NODDI technique and gait parameters can help detect gait impairment in PD patients early and accurately.

Cardiac DTI using short-axis PROPELLER: A feasibility study.

We aimed to develop a free-breathing (FB) cardiac DTI (cDTI) method based on short-axis PROPELLER (SAP) and M2 motion compensated spin-echo EPI (SAP-M2-EPI) to mitigate geometric distortion and eliminate aliasing in acquired diffusion-weighted (DW) images, particularly in patients with a higher body mass index (BMI). The study involved 10 healthy volunteers whose BMI values fell into specific categories: BMI <25 (4 volunteers), 25< BMI <28 (5 volunteers), and BMI >30 (1 volunteer). We compared DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and helix angle transmurality (HAT), between SAP-M2-EPI and M2-ssEPI. To evaluate the performance of SAP-M2-EPI in reducing geometric distortions in the left ventricle (LV) compared to CINE and M2-ssEPI, we utilized the DICE similarity coefficient (DSC) and assessed misregistration area. In all volunteers, SAP-M2-EPI yielded high-quality LV DWIs without aliasing, demonstrating significantly reduced geometric distortion (with an average DSC of 0.92 and average misregistration area of 90 mm2) and diminished signal loss due to bulk motion when compared to M2-ssEPI. DTI parameter maps exhibited consistent patterns across slices without motion related artifacts. SAP-M2-EPI facilitates free-breathing cDTI of the entire LV, effectively eliminating aliasing and minimizing geometric distortion compared to M2-ssEPI. Furthermore, it preserves accurate quantification of myocardial microstructure.

Abstract TP234: A Predictive Model for Early Neurologic Deterioration in Small Subcortical Infarcts

Introduction: Roughly a quarter of patients with an acute small subcortical infarct may develop early neurologic deterioration (END) hallmarked by progressive or stuttering neurologic deficits. Importantly, END results in worse short- and long-term functional outcomes. However, despite its importance, there is an inability to identify those at risk for END, thereby creating a barrier to designing future treatment and preventative trials. We aimed to generate a simple predictive scoring model for END in patients with an acute SSI. Methods: We performed a retrospective chart review of all adult patients admitted to Rhode Island Hospital with an acute SSI between 2015 and 2022. Clinical and demographic data were extracted. Radiographic variables included: 1)infarct signal intensity ratio ≤ 1.15 (analogous to the MR-WITNESS trial), 2) infarct morphology, and 3) infarct size. The primary outcome was END, defined as a ≥ 2-point increase in NIHSS or progressive disabling stroke-related deficits while hospitalized attributed to the index acute SSI. Standard descriptive statistical techniques were used. We then employed a backward stepwise logistic regression with a 0.05 threshold to discern factors associated with END, with each factor contributing one point to the model. An external validation cohort was ascertained from Columbia University. The area under the curve (AUC) was used to assess the utility of the predictive model. Results: A total of 252 patients met inclusion criteria. Demographic and clinical histories did not differ amongst the primary or validation cohorts. A signal intensity ratio ≤ 1.15, “finger-like” SSI morphology, and the presence of SSI on &gt; 3 axial diffusion weighted imaging slices were predictive of END. Allocating one point for each domain (minimum 0, maximum 3) yielded an AUC of 0.88. A score of 2 points captured 91.6% of all END cases. Applying this model to the external validation cohort (n=43) yielded an AUC of 0.68. Conclusion: In sum, we found that a radiographic ordinal model including signal intensity ratio ≤ 1.15, “finger-like” SSI morphology, and infarct presence on &gt; 3 axial diffusion weight imaging slices was helpful in predicting END. Future studies are needed to expand the external cohort size to test this model’s validity.

Abstract TP126: Diffusion Weighted Image Lesion Dynamics in Acute Ischemic Stroke and Functional Recovery: Application of an Automated Software to 7000 Cases

Introduction: The change in DWI lesion volume in acute ischemic stroke has not been investigated in detail. We aimed to investigate the effect of DWI lesion growth or regression within seven days of onset on functional recovery after ischemic stroke. Methods: From a prospective stroke registry, we retrieved acute ischemic stroke cases who had more than two DWIs during in-hospital care between 2005 and 2022. The DWI lesion volume was automatically measured using JBS-01K (JLK Inc., South Korea), a fully automated and validated deep learning algorithm using 3D U-net. The association between categorized DWI lesion volume change (10, 25, 50, and 75 percentiles corresponding to -45%, 0%, 57%, and 220% of volume change) and functional recovery was assessed using multivariable ordinal logistic regression analysis taking lower modified Rankin scale (mRS) as a dependent variable, adjusting for relevant covariates. Results: A total of 7308 patients with ischemic stroke who underwent follow-up DWIs were included. A male was 62%, mean age of 67.5±13.5, and a median of initial NIHSS 4 [IQR 1-7]. The median of interval between the initial and follow-up DWI was 90 hours [IQR 68.25 - 112.20]. The median of the initial DW lesion volume was 1.00 ml [IQR 0.27-5.98], and the median of the follow-up DW lesion volume was 2.05 ml [IQR 0.27-5.98]. DWI lesion volume was regressed in 1844 cases (25%); 136 cases (13%) of EVT and 1708 cases (27%) of non-EVT cases. Compared with patients with 25-50 percentile strata, the adjusted odds ratios (OR) of having favorable functional recovery for &lt; 10th, 10-25th, 50-75th, and ≥75th percentile were 1.25 [95% CI 1.05 - 1.48], 0.96 [0.83 - 1.11], 0.67 [0.59 - 0.76], and 0.63 [0.55 - 0.72], respectively (Figure). Conclusions: We found that approximately a quarter of patients with ischemic stroke had an interval regression of infarct volume on DWI, which is independently associated with favorable functional recovery.

Novel advanced imaging techniques for cerebral oedema.

Cerebral oedema following acute ischemic infarction has been correlated with poor functional outcomes and is the driving mechanism of malignant infarction. Measurements of midline shift and qualitative assessment for herniation are currently the main CT indicators for cerebral oedema but have limited sensitivity for small cortical infarcts and are typically a delayed sign. In contrast, diffusion-weighted (DWI) or T2-weighted magnetic resonance imaging (MRI) are highly sensitive but are significantly less accessible. Due to the need for early quantification of cerebral oedema, several novel imaging biomarkers have been proposed. Based on neuroanatomical shift secondary to space-occupying oedema, measures such as relative hemispheric volume and cerebrospinal fluid displacement are correlated with poor outcomes. In contrast, other imaging biometrics, such as net water uptake, T2 relaxometry and blood brain barrier permeability, reflect intrinsic tissue changes from the influx of fluid into the ischemic region. This review aims to discuss quantification of cerebral oedema using current and developing advanced imaging techniques, and their role in predicting clinical outcomes.

Abstract A098: Quantitative MRI metrics capture pancreatic cancer and stroma responses to novel KRAS inhibitor

Abstract Introduction Pancreatic ductal adenocarcinoma (PDA) is a deadly cancer with limited treatment options. Oncogene KRAS mutations found in majority of PDA patients with KRAS(G12D) mutation being the most common. A new KRAS(G12D) specific inhibitor, MRTX1133 has been shown to induce rapid tumor regression in PDA models while the effect on stroma is only revealed by postmortem analyses of tumor specimens, making it hard to assess the dynamics of stroma remodeling. Furthermore, in clinical testing of KRAS(G12C) inhibitor, only ~50% of patients responded to the treatment despite the presence of correct genetic mutation in biopsy specimens, therefore, early and accurate assessment of the drug-target engagement is important in clinical setting. Our study was designed to test the hypothesis that multimetric MRI captures early responses to KRAS(G12D) inhibitor beyond the change of tumor size in a PDA model. Especially, changes in apparent diffusion coefficient (ADC) from diffusion weighted (DW) MRI, Ktrans from dynamic contrast enhanced (DCE) MRI, and magnetization transfer ratio (MTR). Methods A genetically engineered model of PDA bearing KRAS(G12D) and Trp53 mutation referred to as KPC was used. Male and female mice were enrolled to receive MRTX1133 at 30mg/kg BID or PBS via i.p injection. Murine PDA cells bearing KRAS(G12C) mutation were inoculated in the flank of C57BL/6 mice to grow subcutaneous tumors. In vivo DW- and DCE-MRI were obtained on a 9.4T Bruker system employing pulse sequences insensitive to respiratory motion. Results In KPC mice, striking increase of tumor ADC were detected as early as 48h after treatment initiation and was confirmed by statistical analyses at 48h and day7 accompanied by decrease of tumor size, in contrast to a trend of increased tumor size and decreased ADC in PBS-treated mice. H&amp;E section revealed gross necrosis and extensive cell death. A clear increase of Ktrans suggesting an increase of capillary permeability and/or perfusion was detected at 48h, persisting to day7; while CD31 did not change significantly, capillary lumen area appeared enlarged at 48h, consistent with reduced interstitial fluid pressure resulted from clearance of stromal hyaluronic acid. A remarkable reduction of MTR at 48h clearly captured the stromal effect of MRTX1133 whereas no change observed in PBS-treated mice. Consistently, Sirius red (SR) staining for collagen revealed a high degree of heterogeneity where regions of depletion versus dense SR staining coexist. Lack of tumor regression and ADC change in KRAS(G12C) tumors confirmed the specificity of MRTX1133 to G12D however, a reduction of MTR was revealed, suggesting stromal impact as off-target effect of MRTX1133. Conclusion To our knowledge, this represents the first MRI study of the new KRAS inhibitor. The multimetric MRI approach is novel and significant because it captured MRTX1133-induced cancer cell death and stroma change over time. With further validation, these translatable imaging metrics can provide biological mechanism underneath tumor size change in the clinical setting. Citation Format: Mamta Gupta, Hoon Choi, Emma E. Furth, Miguel Joaquim, Stephen Pickup, Cynthia Clendenin, Margo Orlen, Thomas Karasic, Hee Kwon Song, Yong Fan, Peter O’Dwyer, Robert H. Vonderheide, Mark Rosen, Ben Z. Stanger, Rong Zhou. Quantitative MRI metrics capture pancreatic cancer and stroma responses to novel KRAS inhibitor [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A098.

Abstract A089: Quantitative MRI metrics and single cell transcriptome reveal effects of stroma-directed drug and chemotherapy in a GEM model of pancreatic cancer

Abstract Hypothesis: The dense stroma present in pancreatic ductal adenocarcinoma (PDA) harbors a unique tumor microenvironment (TME) that is immune suppressive and underlies the chemo-resistance of PDA. We have evaluated synthetic vitamin D combined with chemoimmunotherapy in a pilot clinical study (NCT03519308). To elucidate the underlying mechanisms of this treatment, we designed a matched study in a genetically engineered mouse model of PDA (KPC mice) to test the hypothesis that synthetic vitamin D enhances the effect of chemotherapy with or without immune checkpoint inhibition. To detect changes in TME, we have integrated diffusion weighted (DW) and dynamic contrast enhanced (DCE) MRI with immunohistochemistry (IHC) and single cell RNA sequencing (scRNAseq). Methods: KPC mice were randomly assigned to one of four groups: 1) Control (untreated); 2) Nab-paclitaxel + gemcitabine + cisplatin (Chemo); 3) Chemo + synthetic vitamin D (calcipotriol, Cal); 4) Chemo + Cal + PD-L1. The treatment lasted for 14 days followed by euthanasia and tumor collection for IHC and scRNAseq. Respiratory motion-robust DW- and DCE-MRI were performed on treatment days 0, 7 and 14. Results: Compared to consistent tumor growth (measured by MRI) in the Control group, both progression and regression were observed in groups 2) - 4), suggesting that the KPC model captured the varied treatment responses observed in the clinic. Capillary perfusion/permeability of the tumor measured by Ktrans (a DCE-MRI metric) was reduced at day 7 in the Chemo group (P&amp;lt;0.05), whereas Chemo+Cal reversed the reduction of Ktrans. Chemo-induced Ktrans reduction was corroborated with a significant reduction of microvascular density by IHC of CD31 compared to the Control. Addition of PD-L1 did not appear to enhance the tumor growth delay by Chemo+Cal. scRNAseq analysis revealed that while Chemo significantly delayed the tumor growth compared to the Control, it increased the portion of mesenchymal cells in the tumor and upregulated epithelial-to-mesenchymal transition (EMT) genes known to resist chemotherapy. In contrast, Chemo+Cal increased the fraction of epithelial cells and downregulated EMT genes compared to Chemo. Trasncriptome analysis of the tumor cells demonstrated that Chemo treatment increased the expression of Fibronectin 1 (FN1), a gene associated with tumor invasiveness, EMT, and metastasis, while lowering the expression of Trefoil Factor Family1 (Tff1), which is related to tumor-suppression and chemosensitivity. Chemo+Cal treatment reversed the expression of both FN1 and Tff1 gene compared to Chemo treatment. Conclusion: Single cell transcriptome analysis provided valuable insights into treatment-induced molecular subtype changes, which may predict future resistance and invasiveness. Our study revealed important mechanisms of calcipotriol that enhance the efficacy of chemotherapy by improving microvascular perfusion and permeability and by reducing chemo-resistance by enriching epithelial cells in PDA tumors. Citation Format: Hoon Choi, Mamta Gupta, Thomas Karasic, Miguel Joaquim, Emma Furth, Stephen Pickup, Cynthia Clendenin, Hee Kwon Song, Yong Fan, Jeffrey Duda, James Gee, Mark Rosen, Peter O’Dwyer, Rong Zhou. Quantitative MRI metrics and single cell transcriptome reveal effects of stroma-directed drug and chemotherapy in a GEM model of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A089.

Spherical harmonics-based deep learning achieves generalized and accurate diffusion tensor imaging.

Diffusion tensor imaging (DTI) is a prevalent magnetic resonance imaging (MRI) technique, widely used in clinical and neuroscience research. However, the reliability of DTI is affected by the low signal-to-noise ratio inherent in diffusion-weighted (DW) images. Deep learning (DL) has shown promise in improving the quality of DTI, but its limited generalization to variable acquisition schemes hinders practical applications. This study aims to develop a generalized, accurate, and efficient DL-based DTI method. By leveraging the representation of voxel-wise diffusion MRI (dMRI) signals on the sphere using spherical harmonics (SH), we propose a novel approach that utilizes SH coefficient maps as input to a network for predicting the diffusion tensor (DT) field, enabling improved generalization. Extensive experiments were conducted on simulated and in-vivo datasets, covering various DTI application scenarios. The results demonstrate that the proposed SH-DTI method achieves advanced performance in both quantitative and qualitative analyses of DTI. Moreover, it exhibits remarkable generalization capabilities across different acquisition schemes, centers, and scanners, ensuring its broad applicability in diverse settings.

The significance of PI-RADS v2.1 score combined with quantitative parameters of DWI and DCE-MRI in differentiating between benign prostatic hyperplasia and prostate cancer

This study investigates the efficacy of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score combined with quantitative metrics from Diffusion Weighted Imaging (DWI) and Dynamic Contrast Enhancement Magnetic Resonance Imaging (DCE-MRI) in differentiating between benign prostatic hyperplasia (BPH) and prostate cancer (PCa). The data of 65 patients with prostate diseases were retrospectively analyzed, and they were divided into a BPH group (n = 34) and a PCa group (n = 31). All patients underwent a multiparametric MRI (mpMRI) examination, which included conventional MRI, DWI and DCE-MRI scans. Variables analyzed included the PI-RADS v2.1 score, apparent diffusion coefficient (ADC), volume transfer constant (Ktrans), rate constant (Kep) and extravascular space volume ratio (Ve). The diagnostic performance of the PI-RADS v2.1 score, DWI, DCE-MRI and their combined metrics in differentiating BPH from PCa was assessed using Receiver Operating Characteristic (ROC) curve analysis. The results demonstrated that the PI-RADS v2.1 scores, Ktrans and Kep values of the PCa group were significantly higher than those of the BPH group (p &lt; 0.001), while the ADC value of the PCa group was significantly lower than the BPH group (p &lt; 0.001). No significant difference was observed in the Ve value between the two groups (p = 0.596). ROC analysis indicated that the area under the curve (AUC) values for the PI-RADS v2.1 score, ADC, Ktrans, Kep, Ve and their combination parameters were 0.824, 0.916, 0.903, 0.904, 0.625 and 0.990, respectively, with the combined parameters showing higher sensitivity and specificity than any single parameter. These findings suggest that the PI-RADS v2.1 score, along with DWI and DCE-MRI sequences, are valuable tools for differentiating BPH from PCa. The quantitative parameters, including ADC, Ktrans and Kep values, offer significant imaging references for clinical assessment, and the combination parameters can significantly enhance diagnostic accuracy.

Single-shot diffusion trace-weighted MR spectroscopy: Comparison with unipolar and bipolar diffusion-weighted point-resolved spectroscopy.

This study demonstrates the feasibility and performance of the point-resolved spectroscopy (PRESS)-based, single-shot diffusion trace-weighted sequence in quantifying the trace apparent diffusion coefficient (ADC) in phantom and in vivo using a 3-T MRI/MRS scanner. The single-shot diffusion trace-weighted PRESS sequence was implemented and compared with conventional diffusion-weighted (DW)-PRESS variants using bipolar and unipolar diffusion-sensitizing gradients. Nine phantom datasets were acquired using each sequence, and seven volunteers were scanned in three different brain regions to determine the range and variability of trace ADC values, and to allow a comparison of trace ADCs among the sequences. This sequence results in a comparatively stable range of trace ADC values that are statistically significantly higher than those produced from unipolar and bipolar DW-PRESS sequences. Only total n-acetylaspartate, total creatine, and total choline were reliably estimated in all sequences with Cramér-Rao lower bounds of, at most, 20%. The larger trace ADCs from the single-shot sequences are probably attributable to the shorter diffusion time relative to the other sequences. Overall, this study presents the first demonstration of the single-shot diffusion trace-weighted sequence in a clinical scanner at 3 T. The results show excellent agreement of phantom trace ADCs computed with all sequences, and in vivo ADCs agree well with the expected differences between gray and white matter. The diffusion trace-weighted sequence could provide an estimate of the trace ADC in a shorter scan time (by nearly a factor of 3) compared with conventional DW-PRESS approaches that require three separate orthogonal directions.