Apparent Diffusion Coefficient Changes Research Articles

Distinguishing Laterality in Brain Injury in Rabbit Fetal MRI Using Novel Volume Rendering Techniques.

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 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. A novel aspect involved utilizing three-dimensional rendering techniques to refine ADC measurements within spheroids encompassing fetal brain tissue. 25-day gestation rabbit fetuses underwent global hypoxia due to maternal uterine ischemia. 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 time point during hypoxia-ischemia. This study also highlights a balance between left-sided and right-sided alterations within the population. 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.

Protective effects of human urinary kallidinogenase against corticospinal tract damage in acute ischemic stroke patients.

This study aimed to assess the effects of human urinary kallidinogenase (HUK) on motor function outcome and corticospinal tract recovery in patients with acute ischemic stroke (AIS). This study was a randomized, controlled, single-blinded trial. Eighty AIS patients were split into two groups: the HUK and control groups. The HUK group was administered HUK and standard treatment, while the control group received standard treatment only. At admission and discharge, the National Institutes of Health Stroke Scale (NIHSS), Barthel Index (BI) and muscle strength were scored. The primary endpoint was the short-term outcomes of AIS patients under different treatments. The secondary endpoint was the degree of corticospinal tract fiber damage under different treatments. There was a significant improvement in the NIHSS Scale, BI and muscle strength scores in the HUK group compared with controls (Mann-Whitney U test; P < 0.05). Diffusion tensor tractography classification and intracranial arterial stenosis were independent predictors of short-term recovery by linear regression analysis. The changes in fractional anisotropy (FA) and apparent diffusion coefficient (ADC) decline rate were significantly smaller in the HUK group than in the control group (P < 0.05). Vascular endothelial growth factor (VEGF) increased significantly after HUK treatment (P < 0.05), and the VEGF change was negatively correlated with changes in ADC. HUK is beneficial for the outcome in AIS patients especially in motor function recovery. It may have protective effects on the corticospinal tract which is reflected by the reduction in the FA and ADC decline rates and increased VEGF expression. The study was registered on ClinicalTrials.gov (unique identifier: NCT04102956).

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.

FRI619 Kidney Magnetic Resonance Imaging Reveals Altered Tissue Architecture In Young Persons With Type 1 And 2 Diabetes

Abstract Disclosure: S. Poon: None. K. Nash: None. Y. Choi: None. L. Li: None. P. Prasad: None. D. Raalte: Other; Self; consulting relationships with Boehringer Ingelheim, Eli Lilly, Merck and Sanofi, and receives research operating funding from AstraZeneca, Boehringer Ingelheim-Eli Lilly Diabetes Alliance, MSD. A. Karihaloo: Employee; Self; Novo Nordisk. A. Sawyer: None. P. Bjornstad: Advisory Board Member; Self; AstraZeneca, Bayer, Lilly, Boehringer Ingelheim, Novo Nordisk, and XORTX. Other; Self; PB reports serving or having served as a consultant for AstraZeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, Eli Lilly, LG Chemistry, Sanofi, Novo Nordisk, and Horizon Pharma. Background: Apparent diffusion coefficient (ADC) by magnetic resonance imaging (MRI) provides information about the microstructure and cellular organization of the kidney, and has been linked with kidney function decline in adults with chronic kidney disease. However, it is unclear whether alterations in tissue architecture or cellular density are also present in young persons with type 1 and 2 diabetes. Accordingly, the objective of this analysis was to determine early changes in ADC among young persons with and without diabetes. Materials and Method: Kidney MRIs were performed in 37 lean controls (age: 18±6 years, 54% female, eGFR: 106±19 ml/min/1.73m2), 28 participants with youth-onset T1D (age: 20±4 years, 50% female, diabetes duration: 9±6 years, HbA1c: 8.3±1.3%, eGFR: 110±19 ml/min/1.73m2) and 30 participants with youth-onset T2D (age: 17±4 years, 62% female, diabetes duration: 2±2 years, HbA1c: 7.4±2.2%, eGFR: 127±24 ml/min/1.73m2). All scans were performed on 3T whole-body scanners. A single reader at The NorthShore University HealthSystem analyzed all images while blinded to participants’ clinical information. Lower values of cortical ADC on diffusion-weighted MRI may indicate increased cellular density and are often used to estimate fibrosis. Estimated GFR (eGFR) were calculated by Full Age Spectrum serum creatinine equation. We performed multivariable linear regression models adjusted for age and sex. Results: Compared to lean controls (age and sex-adjusted means ± standard errors (SE): (1722±22 × 10−6 mm2/s), young persons with T1D (1636±28 × 10−6 mm2/s, p=0.02) and T2D (1612±27 × 10−6 mm2/s, p=0.002) exhibited lower cortical ADC. Despite younger age and shorter diabetes duration, young persons with T2D had numerically lower cortical ADC compared to those with T1D, although the difference did not reach statistical significance. Higher age and male sex were associated with lower cortical ADC (β±SE: −7.5±2.8 x 10−6 mm2/s per 1 year of age, p=0.009; β±SE: −71.1±28.5 x 10−6 mm2/s per 1 year for male sex, p=0.008) in multivariable models. Lower eGFR was associated with lower cortical ADC (β±SE: 2.3±0.8 x 10−6 mm2/s per 1 ml/min/1.73m2 increment eGFR, p=0.005). HbA1c and urine albumin-to-creatinine ratio did not associate significantly with cortical ADC in multivariable models. Conclusion: Young persons with diabetes exhibit lower cortical ADC compared to healthy lean controls, suggesting alternations in microstructure and cellular density and potentially early signs of fibrosis. Additionally, despite shorter duration of disease and younger age, participants with T2D had the lowest cortical ADC values among the 3 groups. Further research is needed to investigate the role of cortical ADC in predicting kidney function decline in young individuals with diabetes, as well as molecular determinants of the alterations in microstructure and cellular density. Presentation: Friday, June 16, 2023

Longitudinal Monitoring of Quantitative Imaging Kinetics of Primary Tumor and Nodal Volumes Using the MR-Linac Device in Head and Neck Cancer Patients

We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients. Thirty patients with pathologically confirmed HNSCC and received curative-intent RT at the University of Texas MD Anderson Cancer Center, were included in this prospective study. Baseline and weekly MRIs (weeks 1-6) were obtained, and various ADC parameters (mean, 5th, 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th, 90th and 95th percentile) were extracted from the target regions of interest (ROIs). Pre-RT and weekly ADC parameters were correlated with response during RT, loco-regional control, and the development of relapse using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) was performed to identify the optimal ΔADC threshold associated with different oncologic outcomes. There was an overall significant rise in all ADC parameters during different time points of RT compared to baseline values for both GTV-P & GTV-N. The increased ADC values for GTV-P were statistically significant only for primary tumors achieving CR during RT. RPA identified GTV-P ΔADC 5th percentile >13% at the 3rd week of RT as the most significant parameter associated with CR for GTV-P during RT (p <0.001). Baseline ADC parameters didn't significantly correlate with response to RT or other oncologic outcomes. There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. Additionally, a significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3rd and 4th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively). Assessment of ADC kinetics at regular intervals throughout RT is potentially able to predict the response to RT and oncologic outcome. Further studies with larger cohorts and multi-institutional data are needed for validation of our results.

Restriction spectrum imaging with elastic image registration for automated evaluation of response to neoadjuvant therapy in breast cancer.

Dynamic contrast-enhanced MRI (DCE) and apparent diffusion coefficient (ADC) are currently used to evaluate treatment response of breast cancer. The purpose of the current study was to evaluate the three-component Restriction Spectrum Imaging model (RSI3C), a recent diffusion-weighted MRI (DWI)-based tumor classification method, combined with elastic image registration, to automatically monitor breast tumor size throughout neoadjuvant therapy. Breast cancer patients (n=27) underwent multi-parametric 3T MRI at four time points during treatment. Elastically-registered DWI images were used to generate an automatic RSI3C response classifier, assessed against manual DCE tumor size measurements and mean ADC values. Predictions of therapy response during treatment and residual tumor post-treatment were assessed using non-pathological complete response (non-pCR) as an endpoint. Ten patients experienced pCR. Prediction of non-pCR using ROC AUC (95% CI) for change in measured tumor size from pre-treatment time point to early-treatment time point was 0.65 (0.38-0.92) for the RSI3C classifier, 0.64 (0.36-0.91) for DCE, and 0.45 (0.16-0.75) for change in mean ADC. Sensitivity for detection of residual disease post-treatment was 0.71 (0.44-0.90) for the RSI3C classifier, compared to 0.88 (0.64-0.99) for DCE and 0.76 (0.50-0.93) for ADC. Specificity was 0.90 (0.56-1.00) for the RSI3C classifier, 0.70 (0.35-0.93) for DCE, and 0.50 (0.19-0.81) for ADC. The automatic RSI3C classifier with elastic image registration suggested prediction of response to treatment after only three weeks, and showed performance comparable to DCE for assessment of residual tumor post-therapy. RSI3C may guide clinical decision-making and enable tailored treatment regimens and cost-efficient evaluation of neoadjuvant therapy of breast cancer.

Relationship between apparent diffusion coefficient and survival as a function of distance from gross tumor volume on radiation planning MRI in newly diagnosed glioblastoma.

To investigate the changes in apparent diffusion coefficient (ADC) within incrementally-increased margins beyond the gross tumor volume (GTV) on post-operative radiation planning MRI and their prognostic utility in glioblastoma. Radiation planning MRIs of adult patients with newly diagnosed glioblastoma from 2017 to 2020 were assessed. The ADC values were normalized to contralateral normal white matter (nADC). Using 1mm isotropic incremental margin increases from the GTV, the nADC values were calculated at each increment. Age, ECOG performance status, extent of resection and MGMT promoter methylation status were obtained from medical records. Using univariate and multivariable Cox regression analysis, association of nADC to progression-free and overall survival (PFS, OS) was assessed at each increment. Seventy consecutive patients with mean age of 53.6 ± 10.3 years, were evaluated. The MGMT promoter was methylated in 31 (44.3%), unmethylated in 36 (51.6%) and unknown in 3 (4.3%) patients. 11 (16%) underwent biopsy, 41 (44%) subtotal resection and 18 (26%) gross total resection. For each 1mm increase in distance from GTV, the nADC decreased by 0.16% (p < 0.0001). At 1-5mm increment, the nADC was associated with OS (p < 0.01). From 6 to 11mm increment the nADC was associated with OS with the p-value gradually increasing from 0.018 to 0.046. nADC was not associated with PFS. The nADC values at 1-11mm increments from the GTV margin were associated with OS. Future prospective multicenter studies are needed to validate the findings and to pave the way for the utilization of ADC for margin reduction in radiation planning.

Quantitative diffusion-weighted MRI response assessment in rhabdomyosarcoma: an international retrospective study on behalf of the European paediatric Soft tissue sarcoma Study Group Imaging Committee

ObjectiveTo investigate the feasibility of diffusion-weighted magnetic resonance imaging (DW-MRI) as a predictive imaging marker after neoadjuvant chemotherapy in patients with rhabdomyosarcoma.Material and methodsWe performed a multicenter retrospective study including pediatric, adolescent and young adult patients with rhabdomyosarcoma, Intergroup Rhabdomyosarcoma Study group III/IV, treated according to the European paediatric Soft tissue sarcoma Study Group (EpSSG) RMS2005 or MTS2008 studies. DW-MRI was performed according to institutional protocols. We performed two-dimensional single-slice tumor delineation. Areas of necrosis or hemorrhage were delineated to be excluded in the primary analysis. Mean, median and 5th and 95th apparent diffusion coefficient (ADC) were extracted.ResultsOf 134 included patients, 82 had measurable tumor at diagnosis and response and DW-MRI scans of adequate quality and were included in the analysis. Technical heterogeneity in scan acquisition protocols and scanners was observed. Mean ADC at diagnosis was 1.1 (95% confidence interval [CI]: 1.1–1.2) (all ADC expressed in * 10−3 mm2/s), versus 1.6 (1.5–1.6) at response assessment. The 5th percentile ADC was 0.8 (0.7–0.9) at diagnosis and 1.1 (1.0–1.2) at response. Absolute change in mean ADC after neoadjuvant chemotherapy was 0.4 (0.3–0.5). Exploratory analyses for association between ADC and clinical parameters showed a significant difference in mean ADC at diagnosis for alveolar versus embryonal histology. Landmark analysis at nine weeks after the date of diagnosis showed no significant association (hazard ratio 1.3 [0.6–3.2]) between the mean ADC change and event-free survival.ConclusionA significant change in the 5th percentile and the mean ADC after chemotherapy was observed. Strong heterogeneity was identified in DW-MRI acquisition protocols between centers and in individual patients.Graphical

Diffusion-weighted MRI at the Late Stage after Radiotherapy for Evaluating Salivary Gland Injury.

Salivary gland injury is the main complication of radiotherapy for nasopharyngeal carcinoma (NPC) patients. The purpose of this study was to evaluate the value of diffusion-weighted magnetic resonance imaging (DW-MRI) as a reliable tool to assess salivary gland function in NPC patients after radiotherapy. This study analysed the MR images of 31 NPC patients at different time points within 2-3 years after radiotherapy. The changes in the apparent diffusion coefficient (ADC) and its relationship with radiation dose were analysed. Both the parotid and submandibular gland ADC values increased significantly 3-6 months after radiotherapy and then decreased gradually. The ADC value of the parotid gland was positively correlated with radiation dose at the late stage (P = 0.012, r = 0.359). The submandibular gland ADC change value (P = 0.035) and change ratio (P = 0.027) of the high radiation dose group were significantly lower than those of the low dose group at the late stage. The correlation between ADC values of parotid and submandibular glands and the radiation dose indicated that DW-MRI could be helpful in evaluating salivary gland injury after radiotherapy.

A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

Background and PurposeDiffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes. Materials and MethodsTwenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADCmean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics. ResultsThe median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56–1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63–1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising. ConclusionsThe SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts.

Four-quadrant vector mapping of hybrid multidimensional MRI data for the diagnosis of prostate cancer.

The interpretation of prostate multiparametric magnetic resonance imaging (MRI) is subjective in nature, and there is large inter-observer variability among radiologists and up to 30% of clinically significant cancers are missed. This has motivated the development of new MRI techniques and sequences, especially quantitative approaches to improve prostate cancer diagnosis. Using hybrid multidimensional MRI, apparent diffusion coefficient (ADC) and T2 have been shown to change as a function of echo time (TE) and b-values, and that this dependence is different for cancer and benign tissue, which can be exploited for prostate cancer diagnosis. The purpose of this study is to investigate whether four-quadrant vector mapping of hybrid multidimensional MRI (HM-MRI) data can be used to diagnose prostate cancer (PCa) and determine cancer aggressiveness. Twenty-one patients with confirmed PCa underwent preoperative MRI prior to radical prostatectomy. Axial HM-MRI were acquired with all combinations of TE=47, 75, 100ms and b-values of 0, 750, 1500s/mm2 , resulting in a 3×3 data matrix associated with each voxel. Prostate Quadrant (PQ) mapping analysis represents HM-MRI data for each voxel as a color-coded vector in the four-quadrant space of HM-MRI parameters (a 2D matrix of signal values for each combination of b-value and TE) with associated amplitude and angle information representing the change in T2 and ADC as a function of b-value and TE, respectively. Cancers have a higher PQ4 (22.50%±21.27%) and lower PQ2 (69.86%±28.24%) compared to benign tissue: peripheral, transition, and central zone (PQ4=0.13%±0.56%, 5.73%±15.07%, 2.66%±4.05%, and PQ2=98.51%±3.05%, 86.18%±21.75%, 93.38%±9.88%, respectively). Cancers have a higher vector angle (206.5±41.8°) and amplitude (0.017±0.013) compared to benign tissue. PQ metrics showed moderate correlation with Gleason score (|ρ|=0.388-0.609), with more aggressive cancers being associated with increased PQ4 and angle and reduced PQ2 and amplitude. A combination of four-quadrant analysis metrics provided an area under the curve of 0.904 (p<0.001) for the differentiation of prostate cancer from benign prostatic tissue. Four-quadrant vector mapping of HM-MRI data provides effective cancer markers, with cancers associated with high PQ4 and high vector angle and lower PQ2 and vector amplitude.