Apparent Diffusion Coefficient Changes Research Articles

Abstract Sa1101: Association Between Changes in Hypoxic-Ischemic Brain Injury and Neurological Outcomes in Cardiac Arrest Survivors.

Aim: Quantitative analysis of hypoxic-ischemic brain injury (HIBI) using apparent diffusion coefficient (ADC) values from brain magnetic resonance imaging (MRI) is used to predict poor neurological outcomes in out-of-hospital cardiac arrest (OHCA) survivors. Our study aimed to determine the association between changes in HIBI and neurological outcomes in OHCA survivors using two types of MRI. Methods: This observational study used data collected prospectively from a tertiary academic hospital. The study included adult comatose OHCA survivors who underwent targeted temperature management (TTM) and brain MRI within 6 hours (first) and 72–96 hours (second) using the same MR scanner. We analyzed the neurological outcomes based on brain volumes below a specific ADC value using 10-step intervals within the range of 200–1200 × 10 -6 mm 2 /s for the first and second MRIs. ADC-R(x) represents the proportion of total brain volume occupied by voxels, with ADC values ranging from 200 × 10 -6 mm 2 /s to each threshold. Additionally, ADC(x) represents the proportion of total brain volume occupied by voxels that are “threshold - 10” at each threshold. Poor neurological outcomes were categorized as cerebral performance levels 3–5, observed 6 months after OHCA. Results: Overall, 122 patients (25% female) were included in the analysis, of whom 61 (50%) showed poor neurological outcomes. Higher ADC-R(x) were observed in the poor neurological outcome group on both the first and second MRI scans at all ADC intervals (all P < 0.05) (Figure 1). In the Good Neurological Outcome group, the ADC-R values ranged between 370 and 940, with the second MRI value being smaller than that of the first (right shift, P < 0.05). In contrast, the Poor Neurological Outcome group showed ADC-R values ranging between 340 and 1190, with the second MRI value being higher than that of the first (left shift, P < 0.05) (Figure 2). The difference in ADC(x) between the second and first MRI based on neurological outcome showed a positive change in ADC below 620 for a poor neurological outcome and a positive change in ADC above 740 for a good neurological outcome (Figure 3). Conclusions: In this cohort study, we observed that the initial HIBI that occurred during OHCA worsened or returned to normal depending on the neurological outcome after TTM. Prospective multicenter studies are required to generalize our findings.

NIMG-29. EARLY REDUCTION IN MRI DIFFUSION APPARENT DIFFUSION COEFFICIENT (ADC) STRONGLY PREDICTS LONG TERM RESPONSE TO ONC201 THERAPY IN PATIENTS WITH H3K27M-DMG

Abstract ONC201 is the first monotherapy to improve outcomes in H3K27M- diffuse midline glioma (DMG) beyond radiation. Despite impressive early efficacy in H3K27M-DMG, individual response to ONC201 is variable and no radiographic biomarkers predict long term response. Previous studies demonstrated baseline MRI diffusion apparent diffusion coefficient (ADC) is lower in DMG with H3K27M compared to wildtype but change after radiation therapy was not correlated with improved OS or PFS. We hypothesize ADC will enable stratification of patients more likely to respond to ONC201. Imaging and clinical data were abstracted from chart review of patients treated with ONC201 at University of Michigan. Two neuroradiologists performed centralized review for RAPNO measurements and mean ADC was assessed using ROI measured in consistent anatomic locations, with areas of cystic degeneration or necrosis excluded. Sixty-one patients were identified for review. Preliminary analysis was performed on twenty-three patients, with upfront ONC201 therapy, median age 14.8 years old (5-25yo), primary site includes pontine (n=15), thalamic (n=7). Baseline characteristics of age, ADC and size at diagnosis or follow-up RAPNO scored size were not statistically significant. Patients with longer than median survival (334 days) demonstrated increased ADC (+58.25x10-6mm2/s) from baseline to cycle 2 whereas patients with shorter than median survival demonstrated decreased ADC (-174.8x10-6mm2/s) (p = 0.0076). Further, patients with decreased ADC demonstrated mean OS of 302.8 days and patients with increased ADC had mean OS of 588.0 (p = 0.0054). In H3K27M-DMG patients treated with ONC201, increased ADC after two cycles of ONC201 was strongly predictive of longer overall survival. Our recent work demonstrated that ONC201 disrupts metabolic and epigenetic pathways to restore pathognomonic H3K27me3 reduction, which may underline greater change in ADC. Ongoing work will validate these findings in an independent external cohort and integrate histogram analysis, parametric assessments, MRI perfusion and liquid biopsy biomarkers (cf-tDNA and metabolomics).

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

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

Impact of geometric correction on echo-planar imaging-based apparent diffusion coefficient maps for abdominal radiotherapy

Objective. The apparent diffusion coefficient (ADC) extracted from diffusion-weighted magnetic resonance imaging (DWI) is a potential biomarker in radiotherapy (RT). DWI is often implemented with an echo-planar imaging (EPI) read-out due to speed, but unfortunately low geometric accuracy follows. This study aimed to investigate the influence of geometric distortions on the ADCs extracted from the gross tumor volume (GTV) and on the shape of the GTV in abdominal EPI-DWI. Approach. Twenty-one patients had EPI-DWI scans on a 1.5 T MRI sim before treatment and on a 1.5 T MRI-Linac at one of the first treatment fractions. Off-resonance correction with and without eddy current correction were applied to ADC maps. The clinical GTVs were deformed based on the same (but inverted) corrections to assess the local-regional geometric influence of distortions. Mean surface distance (MSD), Hausdorff distance (HD), and Dice similarity coefficient (DSC) were calculated to compare the original and distorted GTVs, and ADC values were calculated based on a mono-exponential model. Phantom measurements were performed to validate the applied correction method. Main results. The median (range) ADC change within the GTV after full distortion correction was 1.3% (0.02%–6.9%) for MRI-Sim and 1.5% (0.1%–6.4%) for MRI-Linac. The additional effect of the eddy current correction was small in both systems. The median (range) MSD, HD, and DSC comparing the original and off-resonance distorted GTVs for all patients were 0.43 mm (0.11–0.94 mm), 4.00 mm (1.00–7.81 mm) and 0.93 (0.82–0.99), respectively. Significance. Overall effect of distortion correction was small in terms of derived ADC values, indicating that distortion correction is unimportant for prediction of outcomes based on ADC. However, large local geometric changes occurred after off-resonance distortion correction for some patients, suggesting that if the spatial information from ADC maps is to be used for dose painting strategies, corrections should be applied.

21 Early Apparent Diffusion Coefficient (ADC) Changes During Concurrent Chemoradiation: An Imaging Biomarker for Treatment Response and Recurrence Prediction in Glioblastoma

21 Early Apparent Diffusion Coefficient (ADC) Changes During Concurrent Chemoradiation: An Imaging Biomarker for Treatment Response and Recurrence Prediction in Glioblastoma

Correlation analysis of dynamic changes of abdominal fat during rapid weight loss after bariatric surgery: A prospective magnetic resonance imaging study

ObjectiveThe factors related to the changes in the liver and abdominal adipose tissue during the rapid weight loss after bariatric surgery remain uncertain. MethodsThis study included 44 participants who had undergone sleeve gastrectomy. The study aimed to analyze changes and correlations of body weight (BW), laboratory tests, and magnetic resonance imaging (MRI) indicators of the liver and abdominal adipose tissue conducted before and after bariatric surgery at 1, 3, and 6 months. ResultsFollowing a rapid weight loss within 6 months of surgery, there was a concurrent decrease in blood glucose, blood lipids, and fat content of the liver and abdomen and the changes showed a correlation. The change of BW (ΔBW) was positively correlated with the change of hepatic proton density fat fraction (ΔPDFF) in one and three months after surgery and was positively correlated with the change of abdominal visceral fat area (ΔAVFA) in six months after surgery, (P<0.05). In one month after surgery, ΔPDFF was positively correlated with the change of aspartate aminotransferase (ΔAST), change of alanine aminotransferase (ΔALT), and change of triglyceride glucose (ΔTYG) index (P<0.05). ΔPDFF was positively correlated with the change of hepatic native T1 values (P<0.001) and was moderately negatively correlated with the change of hepatic apparent diffusion coefficient (ΔADC) values in three months after surgery (P<0.05). ConclusionΔBW can serve as an indirect indicator for evaluating changes in liver fat fraction at 1 and 3 months after bariatric surgery and indicative of changes in visceral fat 6 months after surgery. ΔPDFF was positively correlated with ΔAST, ΔALT and ΔTYG index in 1 months after surgery.

Analysis of diffusion changes in cerebral tissues of Parki̇nson's patients who underwent subthalamic nucleus deep brain stimulation: Correlation of improvements in motor and neuropsychiatric symptoms

ObjectiveParkinson's disease (PD) as a neurodegenerative disorder characterized by a reduction in both the quantity and functionality of dopaminergic neurons. This succinctly highlights the central pathological feature of PD and its association with dopaminergic neuron degeneration, which underlies the motor and non-motor symptoms of the disease.This study aims to elucidate the nuances of apparent diffusion coefficient (ADC) changes in different cerebral regions by after the bilateral subthalamic nucleus (STN) deep brain stimulation (DBS) surgery of PD, as well as to investigate their potential interactions with the motor and neuropsychiatric spectrum. MethodsPatients who underwent STN-DBS surgery for PD between 2017 and 2019 were included in this study. The results of diffusion magnetic resonance imaging (MRI), Unified Parkinson Disease Rating Scale (UPDRS) III scores, Beck and Hamilton depression tests were recorded before and at the 3rd month of postoperative stimulation. The data obtained were evaluated with the Wilcoxon signed rank test. Result of the statistical tests were within the 95 % confidence interval and p values were significant below 0.05. ResultsOur study was conducted with a total of 13 patients, 8 men and 5 women. As a result of measurements made in a total of 32 different regions, especially in the motor and neuropsychiatric areas of the brain, an increase in ADC values was found in all areas. ADC changes of eight localizations such as left corpus callosum, right corona radiata, left corona radiata, hippocampus, right insula, left superior cerebellar peduncle, left caudate nucleus and left putamen were statistically significant. UPDRS III scores improved by 57 % (p <0.05), and Beck and Hamilton depression scores by 25 % and 33 %, respectively (p> 0.05). ConclusionsThis article implicate that bilateral STN-DBS surgery potentially exerts beneficial effects on both motor and neuropsychiatric symptomatology in individuals with PD. We believe that this therapeutic mechanism is hypothesized to involve modulation of diffusion alterations within distinct cerebral tissues.

Multiparametric quantitative magnetic resonance imaging of uterine fibroids for prediction of growth rate-a pilot study.

Uterine fibroid (UF) growth rate and future morbidity cannot be predicted. This can lead to sub-optimal clinical management, with women being lost to follow-up and later presenting with severe disease that may require hospitalization, transfusions, and urgent surgical interventions. Multi-parametric quantitative magnetic resonance imaging (MRI) could provide a biomarker to predict growth rate facilitating better-informed disease management and better clinical outcomes. We assessed the ability of putative quantitative and qualitative MRI predictive factors to predict UF growth rate. Twenty women with UFs were recruited and completed baseline and follow-up MRI exams, 1-2.5 years apart. The subjects filled out symptom severity and health-related quality of life questionnaires at each visit. A standard clinical pelvic MRI non-contrast exam was performed at each visit, followed by a contrast-enhanced multi-parametric quantitative MRI (mp-qMRI) exam with T2, T2*, and apparent diffusion coefficient (ADC) mapping and dynamic contrast-enhanced MRI. Up to 3 largest fibroids were identified and outlined on the T2-weighted sequence. Fibroid morphology and enhancement patterns were qualitatively assessed on dynamic contrast-enhanced MRI. The UFs' volumes and average T2, T2*, and ADC values were calculated. Pearson correlation coefficients were calculated between UF growth rate and T2, T2*, ADC, and baseline volume. Multiple logistic regression and receiver operating characteristic (ROC) analysis were performed to predict fast-growing UFs using combinations of up to 2 significant predictors. A significance level of alpha =0.05 was used. Forty-four fibroids in 20 women had growth rate measurement available, and 36 fibroids in 16 women had follow-up quantitative MRI available. The distribution of fibroid growth rate was skewed, with approximately 20% of the fibroids exhibiting fast growth (>10 cc/year). However, there were no significant changes in median baseline and follow-up values of symptom severity and health-related quality of life scores. There was no change in average T2, T2*, and ADC at follow-up exams and there was a moderate to strong correlation to the fibroid growth rate in baseline volume and average T2 and ADC in slow-growing fibroids (<10 cc/year). A multiple logistic regression to identify fast growing UFs (>10 cc/year) achieved an area under the curve (AUC) of 0.80 with specificity of 69% at 100% sensitivity. The mp-qMRI parameters T2, ADC, and UF volume obtained at the time of initial fibroid diagnosis may be able to predict UF growth rate. Mp-qMRI could be integrated into the management of UFs, for individualized care and improved clinical outcomes.

Changes in Daily Apparent Diffusion Coefficient on Fully Quantitative Magnetic Resonance Imaging Correlate With Established Genomic Pathways of Radiation Sensitivity and Reveal Novel Biologic Associations

Changes in quantitative magnetic resonance imaging (qMRI) are frequently observed during chemotherapy or radiation therapy (RT). It is hypothesized that qMRI features are reflective of underlying tissue responses. It's unknown what underlying genomic characteristics underly qMRI changes. We hypothesized that qMRI changes may correlate with DNA damage response (DDR) capacity within human tumors. Therefore, we designed the current study to correlate qMRI changes from daily RT treatment with underlying tumor transcriptomic profiles. Study participants were prospectively enrolled (National Clinical Trial 03500081). RNA expression levels for 757 genes from pretreatment biopsies were obtained using a custom panel that included signatures of radiation sensitivity and DDR. Daily qMRI data were obtained from a 1.5 Tesla MR linear accelerator. Using these images, d-slow, d-star, perfusion, and apparent diffusion coefficient-mean values in tumors were plotted per-fraction, over time, and associated with genomic pathways. A total of 1022 qMRIs were obtained from 39 patients and both genomic data and qMRI data from 27 total patients. For 20 of those patients, we also generated normal tissue transcriptomic data. Radio sensitivity index values most closely associated with tissue of origin. Multiple genomic pathways including DNA repair, peroxisome, late estrogen receptor responses, KRAS signaling, and UV response were significantly associated with qMRI feature changes (P < .001). Genomic pathway associations across metabolic, RT sensitivity, and DDR pathways indicate common tumor biology that may correlate with qMRI changes during a course of treatment. Such data provide hypothesis-generating novel mechanistic insight into the biologic meaning of qMRI changes during treatment and enable optimal selection of imaging biomarkers for biologically MR-guided RT.

Distinguishing Laterality in Brain Injury in Rabbit Fetal Magnetic Resonance Imaging Using Novel Volume Rendering Techniques

Introduction: Our laboratory has been exploring the MRI detection of fetal brain injury, which previously provided a prognostic biomarker for newborn hypertonia in an animal model of cerebral palsy (CP). The biomarker relies on distinct patterns of diffusion-weighted imaging-defined apparent diffusion coefficient (ADC) in fetal brains during uterine hypoxia-ischemia (H-I). Despite the challenges posed by small brains and tissue acquisition, our objective was to differentiate between left and right brain ADC changes. Methods: A novel aspect involved utilizing three-dimensional rendering techniques to refine ADC measurements within spheroids encompassing fetal brain tissue. 25-day gestation age of rabbit fetuses underwent global hypoxia due to maternal uterine ischemia. Results: Successful differentiation of left and right brain regions was achieved in 28% of the fetal brains. Ordinal analysis revealed predominantly higher ADC on the left side compared to the right at baseline and across the entire time series. During H-I and reperfusion-reoxygenation, the right side exhibited a favored percentage change. Among these fetal brains, 73% exhibited the ADC pattern predictive of hypertonia. No significant differences between left and right sides were observed in patterns predicting hypertonia, except for one timepoint during H-I. This study also highlights a balance between left-sided and right-sided alterations within the population. Conclusion: This study emphasizes the importance of investigating laterality and asymmetric hemispheric lesions for early diagnosis of brain injury, leading to CP. The technological limitations in obtaining a clear picture of the entire fetal brain for every fetus mirror the challenges encountered in human studies.

Normal Brain and Brain Tumor ADC: Changes Resulting From Variation of Diffusion Time and/or Echo Time in Pulsed-Gradient Spin Echo Diffusion Imaging.

Increasing gradient performance on modern magnetic resonance imaging scanners has profoundly reduced the attainable diffusion and echo times for clinically available pulsed-gradient spin echo (PGSE) sequences. This study investigated how this may impact the measured apparent diffusion coefficient (ADC), which is considered an important diagnostic marker for differentiation between normal and abnormal brain tissue and for therapeutic follow-up. Diffusion time and echo time dependence of the ADC were evaluated on a high-performance 3 T magnetic resonance imaging scanner. Diffusion PGSE brain scans were performed in 10 healthy volunteers and in 10 brain tumor patients using diffusion times of 16, 40, and 70 ms, echo times of 60, 75, and 104 ms at 3 b-values (0, 100, and 1000 s/mm 2 ), and a maximum gradient amplitude of 68 mT/m. A low gradient performance system was also emulated by reducing the diffusion encoding gradient amplitude to 19 mT/m. In healthy subjects, the ADC was measured in 6 deep gray matter regions and in 6 white matter regions. In patients, the ADC was measured in the solid part of the tumor. With increasing diffusion time, a small but significant ADC increase of up to 2.5% was observed for 6 aggregate deep gray matter structures. With increasing echo time or reduced gradient performance, a small but significant ADC decrease of up to 2.6% was observed for 6 aggregate white matter structures. In tumors, diffusion time-related ADC changes were inconsistent without clear trend. For tumors with diffusivity above 1.0 μm 2 /ms, with prolonged echo time, there was a pronounced ADC increase of up to 12%. Meanwhile, for tumors with diffusivity at or below 1.0 μm 2 /ms, no change or a reduction was observed. Similar results were observed for gradient performance reduction, with an increase of up to 21%. The coefficient of variation determined in repeat experiments was 2.4%. For PGSE and the explored parameter range, normal tissue ADC changes seem negligible. Meanwhile, observed tumor ADC changes can be relevant if ADC is used as a quantitative biomarker and not merely assessed by visual inspection. This highlights the importance of reporting all pertinent timing parameters in ADC studies and of considering these effects when building scan protocols for use in multicenter investigations.

190 Do Fractional Anisotropy and Apparent Diffusion Coefficient From Diffusion Tensor Imaging Correlate to Symptoms of Radiculopathy? A Case Series From BACPAC MRI

INTRODUCTION: Quantitative diffusion tensor imaging (DTI) parameters such as fractional anisotropy (FA) and apparent diffusion coefficient (ADC) are used to detect axonal pathology in nerve injuries. METHODS: Ganglia of the lumbar plexus nerves (L1-5) were input as seeds to track the nerve fibers using Constant Solid Angle reconstruction. Fiber tracts and values of FA and ADC were extracted along the lumbar plexus nerve profiles. Change in pain (VAS) and disability (ODI) after interlaminar epidural steroid injection at site of compression was compared to the changes in FA and ADC values. RESULTS: Five exams from three patients with bilateral L4-5 foraminal narrowing were included in this study. Two patients were imaged at two time points, three months apart. The average age of the cohort was 62.6 ± 5.3 years. Mean FA values were lowest at L3 (left: 0.32 ± 0.08; right: 0.35 ± 0.05) and L4 (left: 0.39 ± 0.06; right: 0.38 ± 0.03). Correspondingly, mean ADC values were highest at L3 (left: 0.0017 ± 0.0002; right: 0.0016 ± 0.0001) and L4 (left: 0.0.0013 ± 0.0001; right: 0.0015 ± 0.0002). For one patient, pain did not change in severity and ODI improved from severe to moderate disability after steroid injection: FA increased with no significant change in ADC. For another patient, pain increased from moderate to severe and ODI stayed the same after injection: FA decreased and ADC did not significantly change. CONCLUSIONS: The tractography generated from the segmentation model demonstrated lowest FA and highest ADC values corresponding to the level of compression. For patient outcomes, the FA values were observed to be more sensitive to changes in pain and disability compared to the ADC values.

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.

High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance.

Majority of men with low-risk prostate cancer can be managed with active surveillance (AS). This study evaluates a high-resolution diffusion-weighted imaging (HR-DWI) technique to predict adverse biopsy histology (AH), defined as Gleason score ≥7 on any biopsy or ≥3 increase in number of positive biopsy cores on systematic biopsies. We test the hypothesis that high-grade disease and progressing disease undergo subtle changes during even short intervals that can be detected by HR-DWI. In a prospective clinical trial, serial multiparametric MRIs, incorporating HR-DWI and standard DWI (S-DWI) were performed approximately 12 months apart prior to prostate biopsy (n = 59). HR-DWI, which uses reduced field-of-view and motion compensation techniques, was compared with S-DWI. HR-DWI had a 3-fold improvement in spacial resolution compared with S-DWI as confirmed using imaging phantoms. For detecting AH, multiparametric MRI using HR-DWI had a sensitivity of 75% and specificity of 83.9%, and MRI using S-DWI had a sensitivity of 71.4% and specificity of 54.8%. The AUC for HR-DWI was significantly higher (0.794 vs. 0.631, P = 0.014). Secondary analyses of univariable predictors of AH showed tumor size increase [OR 16.8; 95% confidence interval (CI): 4.06-69.48; P < 0.001] and apparent diffusion coefficient (ADC) decrease (OR 5.06; 95% CI: 1.39-18.38; P = 0.014) on HR-DWI were significant predictors of AH. HR-DWI outperforms S-DWI in predicting AH. Patient with AH have tumors that change in size and ADC that could be detected using HR-DWI. Future studies with longer follow-up should assess HR-DWI for predicting disease progression during AS. We report on a prospective clinical trial using a MRI that has three times the resolution of standard MRI. During AS for prostate cancer, two high-resolution MRIs performed approximately a year apart can detect tumor changes that predict the presence of aggressive cancers that should be considered for curative therapy such as prostatectomy or radiation.

Sex differences in normal fetal regional brain apparent diffusion coefficient changes assessed by in utero DWI.

There are differences in the vulnerability of male and female fetal brains to adverse intrauterine exposure, preterm birth, and associated perinatal brain injury. The main objective of this study was to identify any statistically significant difference in the change of apparent diffusion coefficient (ADC) in the intracranial regions of male and female fetuses in the second and third trimesters. Diffusion-weighted imaging (DWI) was performed in 200 fetuses between 20 and 37 gestational ages (GA) with normal results or suspicious results on sonography followed by structural MRI. Pairwise ADC values of the regions of interest (ROIs) were manually delineated on either side of the cerebral white matter: frontal white matter (FWM), parietal white matter (PWM), occipital white matter (OWM), temporal white matter (TWM), basal ganglia (BG), thalamus (THA), cerebellar hemisphere (CBM), and a single measurement in the pons. The changes in these values were studied over the gestational range, along with potential sex differences and asymmetries of the cerebral hemispheres. During the third trimester, ADC values in OWM, TWM, and CBM were significantly higher in male fetuses than those in female fetuses (p < 0.05). After the correction of false-discovery rates (FDR), the difference in CBM was the only statistically significant (p = 0.0032). However, the decreased rate of ADC values in male fetuses in CWM (except for FWM), BG, THA, CBM, and pons was higher than that in female fetuses during the second and third trimesters. We have shown some differences in the intracranial regional ADC changes between male and female fetuses using in utero DWI during the second and third trimesters.

Repeatability and reproducibility of prostate apparent diffusion coefficient values on a 1.5 T magnetic resonance linear accelerator

Background and PurposeIntegrated magnetic resonance linear accelerator (MR-Linac) systems offer potential for biologically based adaptive radiation therapy using apparent diffusion coefficient (ADC). Accurate tracking of longitudinal ADC changes is key to establishing ADC-driven dose adaptation. Here, we report repeatability and reproducibility of intraprostatic ADC using deformable image registration (DIR) to correct for inter-fraction prostate changes. Materials and MethodsThe study included within-fraction repeat ADC measurements for three consecutive fractions for 20 patients with prostate cancer treated on a 1.5 T MR-Linac. We deformably registered successive fraction T2-weighted images and applied the deformation vector field to corresponding ADC maps to align to fraction 2. We delineated gross tumour volume (GTV), peripheral zone (PZ) and prostate clinical target volume (CTV) regions-of-interest (ROIs) on T2-weighted MRI and copied to ADC maps. We computed intraclass correlation coefficients (ICC) and percent repeatability coefficient (%RC) to determine within-fraction repeatability and between-fraction reproducibility for individual voxels, mean and 10th percentile ADC values per ROI. ResultsThe ICC between repeats and fractions was excellent for mean and 10th percentile ADC in all ROIs (ICC > 0.86), and moderate repeatability and reproducibility existed for individual voxels (ICC > 0.542). Similarly, low %RC within-fraction (4.2–17.9 %) mean and 10th percentile ADC existed, with greater %RC between fractions (10.2–36.8 %). Higher %RC existed for individual voxel within-fraction (21.7–30.6 %) and between-fraction (32.1–34.5 %) ADC. ConclusionsResults suggest excellent ADC repeatability and reproducibility in clinically relevant ROIs using DIR to correct between-fraction anatomical changes. We established the precision of voxel-level ADC tracking for future biologically based adaptation implementation.

Development of a multiparametric model for predicting the response to neoadjuvant chemotherapy in breast cancer.

Choosing the appropriate treatment early and predicting the efficacy of neoadjuvant chemotherapy (NAC) for locally advanced breast cancer patients are of particular importance for clinicians. Developing and validating a multiparametric model for predicting NAC would be very meaningful for clinical practice. This study included 91 patients with locally advanced breast cancer treated from 2016 to 2020. The correlation between multiparametric characteristics and the efficacy of NAC was examined. The data were randomly divided into training and validation sets. A least absolute shrinkage and selection operator (LASSO) regression analysis was used for the variable screening. A multivariable logistic regression analysis was used to construct the model. Calibration and decision curves were used to assess the performance of the established model. Lymph node metastasis, the first standard apparent diffusion coefficient (ADC) at the baseline, the change in the standard ADC at the first follow-up, the change in tumor volume at the first follow-up, and the clinical stage of the tumor at the baseline were selected for inclusion in the model. In the receiver operating characteristic (ROC) analysis, the areas under the curve (AUCs) were 0.984 [95% confidence interval (CI): 0.958-1] and 0.815 (95% CI: 0.509-1) for the primary and validation cohorts, respectively. The utility of the established model was confirmed by calibration and decision curves, and a nomogram was obtained. A multiparametric model based on clinical-pathological-magnetic resonance imaging (MRI) features was established to predict the effect of NAC in patients with locally advanced breast cancer.

Early change in apparent diffusion coefficient as a predictor of response to neoadjuvant androgen deprivation and external beam radiation therapy for intermediate- to high-risk prostate cancer

To determine the role of serial apparent diffusion coefficient (ADC) as a biomarker for response to neoadjuvant androgen deprivation therapy (nADT) followed by external beam radiation therapy (EBRT) in intermediate- to high-risk prostate cancer (PCa) patients. This Health Insurance Portability and Accountability Act (HIPAA)-compliant, institutional review board (IRB)-approved prospective study included 12 patients with intermediate- to high-risk PCa patients prior to nADT and EBRT, who underwent serial serum prostate-specific antigen (PSA) and multiparametric prostate magnetic resonance imaging (mpMRI) at baseline (BL), 8-weeks after nADT initiation (time point [TP]1), 6-weeks into EBRT delivery (TP2), and 6-months after nADT initiation (TP3). Tumour volume (tVOL) and tumour and normal tissue ADC (tADC and nlADC) were determined at all TPs. tADC and nlADC dynamics were correlated with post-treatment PSA using Pearson's correlation coefficient. Paired t-tests compared pre/post-treatment ADC. There was a sequential decrease in PSA at all TPs, reaching their lowest values at TP3 post-treatment completion. Mean tADC increased significantly from baseline to TP1 (917.8±107.7×10-6 versus 1033.8±139.3×10-6 mm2/s; p<0.01), with no subsequent change at TP2 or TP3. Both percentage and absolute change in tADC from BL to TP1 correlated with post-treatment PSA (r=-0.666, r=-0.674; p=0.02). Post-treatment PSA in good responders (<0.1 ng/ml) versus poor responders (≥ 0.1 ng/ml) was associated with a greater increase in tADC from BL to TP1 (169.2±122.4×10-6 versus 22.9±75.5×10-6 mm2/s, p=0.03). This pilot study demonstrates the potential for early ADC metrics as a biomarker of response to nADT and EBRT in intermediate to high-risk PCA.

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.

Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient

BackgroundThis study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters.MethodsA retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices.ResultsIn enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs.ConclusionsEffective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.