Baseline Apparent Diffusion Coefficient Research Articles

Prediction of overall survival in patients with locally advanced pancreatic cancer using longitudinal diffusion-weighted MRI.

Biomarkers for prediction of outcome in patients with pancreatic cancer are wanted in order to personalize the treatment. This study investigated the value of longitudinal diffusion-weighted magnetic resonance imaging (DWI) for prediction of overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiotherapy (SBRT). The study included 45 patients with LAPC who received 5 fractions of 10 Gy on a 1.5T MRI-Linac. DWI was acquired prior to irradiation at each fraction. The analysis included baseline values and time-trends of the apparent diffusion coefficient (ADC) and DWI parameters obtained using a decomposition method. A multivariable Cox proportional hazards model for OS was made using best-subset selection, using cross-validation based on Bootstrap. The median OS from the first day of SBRT was 15.5 months (95% CI: 13.2-20.6), and the median potential follow-up time was 19.8 months. The best-performing multivariable model for OS included two decomposition-based DWI parameters: one baseline and one time-trend parameter. The C-Harrell index describing the model's discriminating power was 0.754. High baseline ADC values were associated with reduced OS, whereas no association between the ADC time-trend and OS was observed. Decomposition-based DWI parameters indicated value in the prediction of OS in LAPC. A DWI time-trend parameter was included in the best-performing model, indicating a potential benefit of acquiring longitudinal DWI during the SBRT course. These findings support both baseline and longitudinal DWI as candidate prognostic biomarkers, which may become tools for personalization of the treatment of patients with LAPC.

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.

Early MRI Predictors of Relapse in Primary Central Nervous System Lymphoma Treated with MATRix Immunochemotherapy.

Primary Central Nervous System Lymphoma (PCNSL) is a highly malignant brain tumour. We investigated dynamic changes in tumour volume and apparent diffusion coefficient (ADC) measurements for predicting outcome following treatment with MATRix chemotherapy in PCNSL. Patients treated with MATRix (n = 38) underwent T1 contrast-enhanced (T1CE) and diffusion-weighted imaging (DWI) before treatment, after two cycles and after four cycles of chemotherapy. Response was assessed using the International PCNSL Collaborative Group (IPCG) imaging criteria. ADC histogram parameters and T1CE tumour volumes were compared among response groups, using one-way ANOVA testing. Logistic regression was performed to examine those imaging parameters predictive of response. Response after two cycles of chemotherapy differed from response after four cycles; of the six patients with progressive disease (PD) after four cycles of treatment, two (33%) had demonstrated a partial response (PR) or complete response (CR) after two cycles. ADCmean at baseline, T1CE at baseline and T1CE percentage volume change differed between response groups (0.005 < p < 0.038) and were predictive of MATRix treatment response (area under the curve: 0.672-0.854). Baseline ADC and T1CE metrics are potential biomarkers for risk stratification of PCNSL patients early during remission induction therapy with MATRix. Standard interim response assessment (after two cycles) according to IPCG imaging criteria does not reliably predict early disease progression in the context of a conventional treatment approach.

Early transmural healing and its predictors assessed by magnetic resonance enterography in patients with Crohn's disease receiving ustekinumab.

Transmural healing (TH) is a potential therapeutic goal of Crohn's disease (CD) and is associated with better clinical outcomes. However, few studies have described early TH and its predictors. We aimed to evaluate early TH and its predictors using magnetic resonance enterography (MRE) in patients with CD receiving ustekinumab (UST). This was a retrospective observational study. Patients with active CD treated with UST and their intestinal segments with bowel wall thickness (BWT) ⩽ 3 mm at baseline were included. Clinical characteristics, laboratory indicators, endoscopic manifestations, and MRE indices were evaluated at baseline and week 26 (W26) of the therapy. The following MRE parameters were assessed: BWT, edema, apparent diffusion coefficient (ADC), Clermont score, Magnetic Resonance Index of Activity score, fat stranding, comb sign, and stricture. TH was defined as BWT ⩽ 3 mm without any signs of inflammation (i.e., ulceration, edema, diffusion-weighted hyperintensity, and increased contrast enhancement) at W26. The study included 37 patients with 106 intestinal segments (including 15 proximal small intestines, 33 terminal ilea, and 58 colons). Clinical features, laboratory indicators, endoscopic results, and MRE parameters at W26 were significantly improved after UST treatment in both patient-based and intestinal segment-based analysis. Seven (18.9%) patients and 26 (24.5%) intestinal segments achieved TH at W26. Baseline BWT [odds ratio (OR) = 0.287, 95% confidence interval (CI), 0.090-0.918, p = 0.035] and ADC (OR = 2.997, 95% CI, 1.009-8.908, p = 0.048) predict TH of patients at W26. Baseline ADC (OR = 2.857, 95% CI, 1.285-6.349, p = 0.010) and presence of stenosis (OR = 0.196, 95% CI, 0.052-0.735, p = 0.016) were associated with TH of segments at W26. Early TH assessed by MRE was observed in nearly one-fifth of patients with CD and intestinal segments after UST treatment for 26 weeks. Baseline MRE indices such as BWT and presence of stenosis might negatively predict TH, while ADC might positively predict early TH.

Apparent Diffusion Coefficient (ADC) as an Early Biomarker for Tumor Response to Radiation Therapy, a Meta-Analysis

<h3>Purpose/Objective(s)</h3> MRI equipped linear accelerators are increasing the routine ability to acquire daily diffusion weight imaging (DWI) during a course of radiation therapy (RT). Multiple small series have examined DWI and apparent diffusion coefficient (ADC) as an early biomarker of tumor response to RT. We sought to comprehensively evaluate ADC change (ΔADC) by conducting a meta-analysis of published data. We hypothesized that quantifiable changes in ADC occur early after initiation of treatment and that a certain magnitude in ΔADC changes would be associated with response to RT. <h3>Materials/Methods</h3> A search was conducted for studies with ADC values acquired during and following RT. Studies were included that published mean ADC values of tumors prior to treatment (baseline), 1 and/or 2 weeks into treatment, and included therapeutic response data or progression reported in follow up. The mean percentage changes between studies were combined using the inverse variance weighted method, where variances were estimated from the study reported standard deviations, using a random effects model, to accommodate potential between study heterogeneity. A single estimate of percentage change in ADC, along with the standard deviation and sample size corresponding to estimate was used as the summary statistic of interest from each study, for the response and non-response groups separately. These were combined using the inverse variance weighting method to obtain an overall estimate of percentage ADC change for the two groups of interest, where the square of the reported standard deviation served as the variance estimate. The overall estimate was computed using the random-effects meta-analysis technique. <h3>Results</h3> Data from eight published studies were analyzed totaling 207 patients undergoing RT for brain metastases (n=66), esophageal (n=50), head-and-neck (n=34), cervical (n=33), and rectal (n=24) cancer. One week after the induction of RT, there was no significant change in ADC from baseline in non-responding lesions, +3.32%, 95% CI [-2.25, +8.89], or responding lesions, +6.61%, 95% CI [-0.27, +13.49]. Two weeks after induction, however, the ADC in responding lesions increased by an average of 16.60%, 95% CI [4.86, 28.34], while non-responding lesions remained unchanged from baseline with a mean ΔADC of +4.36%, 95% CI [-8.38, +17.10]. ADC was significantly increased from baseline at two weeks, but not at one week, and lesions with less than 4.86% increase in ADC from baseline at two weeks were unlikely to be responding to the current therapeutic regimen. <h3>Conclusion</h3> From this relatively small meta-analysis it was demonstrated that significant increases in mean ADC for responding lesions were observed as early as two weeks after the initiation of RT. No significant change from baseline ADC was observed in tumors that did not respond to therapy. These data suggest a strong potential role for ΔADC as an early universal biomarker should be investigated in prospective clinical trials as a method to personalize RT dose.

Longitudinal Changes and Predictive Value of Multiparametric MRI Features for Prostate Cancer Patients Treated with MRI-Guided Lattice Extreme Ablative Dose (LEAD) Boost Radiotherapy.

Simple SummaryIn this study, we investigated the longitudinal changes and predictive value of multiparametric MRI (mpMRI) features of prostate cancer patients receiving Lattice Extreme Ablative Dose (LEAD) boost radiotherapy (RT). Ninety-five mpMRI from 25 patients, acquired pre-RT and at 3 time points following RT were analyzed. Five regions of interest were analyzed, related to tumor, peritumoral, and normally-appearing tissues. We identified significant changes in the imaging parameters following RT in all regions. By using selected features at the four scan points and their differences (Δ radiomics), we were able to build viable predictive models for endpoint biopsy positivity. Our study demonstrates that RT causes significant changes to quantitative imaging features in both tumorous and normally-appearing tissues. Because of the noninvasive nature of the mpMRI, acquiring multiple exams post-RT is feasible to monitor treatment response. Several quantitative imaging features are promising predictors of treatment failure based on post-treatment positive biopsy, a strong marker for clinically relevant endpoints.We investigated the longitudinal changes in multiparametric MRI (mpMRI) (T2-weighted, Apparent Diffusion Coefficient (ADC), and Dynamic Contrast Enhanced (DCE-)MRI) of prostate cancer patients receiving Lattice Extreme Ablative Dose (LEAD) radiotherapy (RT) and the capability of their imaging features to predict RT outcome based on endpoint biopsies. Ninety-five mpMRI exams from 25 patients, acquired pre-RT and at 3-, 9-, and 24-months post-RT were analyzed. MRI/Ultrasound-fused biopsies were acquired pre- and at two-years post-RT (endpoint). Five regions of interest (ROIs) were analyzed: Gross tumor volume (GTV), normally-appearing tissue (NAT) and peritumoral volume in both peripheral (PZ) and transition (TZ) zones. Diffusion and perfusion radiomics features were extracted from mpMRI and compared before and after RT using two-tailed Student t-tests. Selected features at the four scan points and their differences (Δ radiomics) were used in multivariate logistic regression models to predict the endpoint biopsy positivity. Baseline ADC values were significantly different between GTV, NAT-PZ, and NAT-TZ (p-values < 0.005). Pharmaco-kinetic features changed significantly in the GTV at 3-month post-RT compared to baseline. Several radiomics features at baseline and three-months post-RT were significantly associated with endpoint biopsy positivity and were used to build models with high predictive power of this endpoint (AUC = 0.98 and 0.89, respectively). Our study characterized the RT-induced changes in perfusion and diffusion. Quantitative imaging features from mpMRI show promise as being predictive of endpoint biopsy positivity.

Establishing ADC-Based Histogram and Texture Features for Early Treatment-Induced Changes in Head and Neck Squamous Cell Carcinoma.

The purpose of this study was to assess baseline variability in histogram and texture features derived from apparent diffusion coefficient (ADC) maps from diffusion-weighted MRI (DW-MRI) examinations and to identify early treatment-induced changes to these features in patients with head and neck squamous cell carcinoma (HNSCC) undergoing definitive chemoradiation. Patients with American Joint Committee on Cancer Stage III–IV (7th edition) HNSCC were prospectively enrolled on an IRB-approved study to undergo two pre-treatment baseline DW-MRI examinations, performed 1 week apart, and a third early intra-treatment DW-MRI examination during the second week of chemoradiation. Forty texture and six histogram features were derived from ADC maps. Repeatability of the features from the baseline ADC maps was assessed with the intra-class correlation coefficient (ICC). A Wilcoxon signed-rank test compared average baseline and early treatment feature changes. Data from nine patients were used for this study. Comparison of the two baseline ADC maps yielded 11 features with an ICC ≥ 0.80, indicating that these features had excellent repeatability: Run Gray-Level Non-Uniformity, Coarseness, Long Zone High Gray-Level, Variance (Histogram Feature), Cluster Shade, Long Zone, Variance (Texture Feature), Run Length Non-Uniformity, Correlation, Cluster Tendency, and ADC Median. The Wilcoxon signed-rank test resulted in four features with significantly different early treatment-induced changes compared to the baseline values: Run Gray-Level Non-Uniformity (p = 0.005), Run Length Non-Uniformity (p = 0.005), Coarseness (p = 0.006), and Variance (Histogram) (p = 0.006). The feasibility of histogram and texture analysis as a potential biomarker is dependent on the baseline variability of each metric, which disqualifies many features.

Baseline apparent diffusion coefficients: Validation study of new predictor of survival in patients with unresectable hepatocellular carcinoma following chemoembolization

To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start of the second course of chemoembolization. Receiver operating characteristic (ROC) curve analysis is performed to evaluate the diagnostic performance and determine optimal cut-off values. Cox regression and Kaplan-Meier survival analyses are used to explore the differences in overall survival (OS) between the responders and non-responders. The difference is statistically significant in the baseline ADC between the responders and non-responders (P < 0.001). ROC analyses indicate that the baseline ADC value is a good predictor of response to treatment with an area under the ROC curve (AUC) of 0.744 and the optimal cut-off value of 1.22×10-3 mm2/s. The Cox regression model shows that the baseline ADC is an independent predictor of OS, with a 57.2% reduction in risk. An optimal baseline ADC value is a functional imaging response biomarker that has higher discriminatory power to predict tumor response and prolonged survival following chemoembolization in HCC patients.

Lower Baseline Apparent Diffusion Coefficient Values are Associated with Worse Survival in Locally Advanced Pancreatic Cancer

It is challenging to obtain adequate pathologic tissue to personalize therapy for locally advanced pancreatic cancer (LAPC) patients. Noninvasive diffusion MRI (dMRI) has the potential to characterize underlying tumor biology and treatment responsiveness. Our prior work found a strong, significant association between pretreatment apparent diffusion coefficient (ADC) values and pancreatic tumor cell destruction in patients with resectable pancreatic cancer undergoing preoperative chemoradiation (chemoRT). The goal of the current study was to prospectively investigate the relationship between dMRI characteristics and outcomes after chemoRT in LAPC patients. Locally advanced pancreatic cancer patients were prospectively enrolled onto an IRB-approved clinical trial, investigating dMRI characteristics before and during chemoRT. High quality dMRI images in the tumor plane were obtained and two radiation oncologists delineated each tumor on T1-weighted MRI and dMRI images. Baseline and mid-radiation (mid-RT) ADC values were compared with time to local failure (TTLF), time to distant failure (TTDF), progression free survival (PFS), and overall survival (OS). Pre- and post-radiation CA-19-9 lab values were also obtained and compared with clinical outcomes. Univariable Cox proportional hazard models were used for statistical analysis. A total of 23 dMRI scans were obtained in 9 patients (6 male, 3 female) who received gemcitabine-based chemoRT. For the overall cohort, the median age was 64 years (range 52-73), median PFS was 18 months, and median OS was 25.3 months from diagnosis. Baseline dMRIs were obtained a median of 25 days (range 1 – 35) prior to radiation. We found a significant association between lower baseline ADC values and all clinical outcomes. Lower mean baseline tumor ADC values were associated with lower OS, lower PFS, shorter TTLF, and shorter TTDF (see Table 1). In comparison, there were no significant relationships between CA-19-9 lab values or mid-RT ADC values with any clinical outcomes. Lower baseline tumor ADC values were found to significantly correlate with clinical outcomes including worse survival in LAPC patients. These findings are concordant with prior studies showing poor pathological responses in resectable pancreatic cancer patients with lower baseline ADC values. Further research is needed in a larger cohort of patients to study how this noninvasive biomarker may help with clinical decision-making and treatment planning.Abstract 3443; TableCox Proportional Hazards Model of Mean Pancreatic Tumor ADCTimepointEndpointHazard Ratio95% CIp-valueBaselineOS0.650.4 – 1.00.0496BaselinePFS0.540.3 – 0.90.01BaselineTTLF0.180.04 – 0.80.02BaselineTTDF0.540.3 – 0.90.03Mid-RTOS1.130.8 – 1.60.51Mid-RTPFS1.080.8 – 1.50.65Mid-RTTTLF00 – Inf0.99Mid-RTTTDF0.650.4 – 1.10.13 Open table in a new tab

Role of Radiomics and Advanced MR Imaging (Diffusion MRI) in Predicting Clinical Prognostication of Uterine Cervix Carcinoma

Radiation with concurrent chemotherapy forms the cornerstone of management for International Federation of Gynecology and Obstetrics (FIGO) stage IB2 to IVA uterine cervix carcinoma disease. Radiomics has emerged as a promising tool for imaging biomarker discovery in era of precision medicine. We explored potential of Radiomics alone and in combination with diffusion imaging derived quantitative parameter namely apparent diffusion co-efficient (ADC) using supervised classification algorithms in predicting outcomes and prognosis. Retrospective evaluation of the imaging was done for a study cohort of 52 patients of squamous cell carcinoma of uterine cervix who were candidates for radical treatment with chemo radiation. One radiologist having 6 years of experience manually drew the region of interest on the tumor for purposes of segmentation and textural analysis. ADC values were calculated from conventional from the darkest part of the tumor, both before (labelled ADC1) and post treatment (labelled ADC2) with chemo radiation. The segmented tumor was validated independently by two radiologists having 30 years of experience each. A total of 851 Radiomics features were extracted from the available imaging using slicer 3D software and open source software. Feature selection was done by taking the union of the features which had Pearson correlation > 0.35 for recurrence > 0.35 for lymph node and > 0.49 for Stage. Models were trained to predict the clinical outcomes using leave one out cross-validation and different algorithms. Using Radiomics features alone building a monotype multilayer perceptron neural network models for predicting recurrence we were able to achieve an accuracy of 85%. The Kappa score (0.55) and the area under the curve (AUC) was 0.80. Using baseline ADC values and change in ADC during treatment in combination with Radiomics features yielded better AUC of 0.82. Using Monotype multilayer perceptron neural network to determine stage (accuracy 60%, kappa 0.38 and AUC 0.75) were achieved when Radiomics was used alone. For predicting lymph node status, we used Nearest Shrunken Centroids model to achieve an accuracy of 81 % and AUC of 0.76 combining Radiomics, change of ADC and baseline ADC. Further on dividing the patients into 2 groups (based on extensive loco-regional disease with distant metastasis (18) vs good response (34) we found that 3 Radiomics wavelet features showed significant statistical difference. The study is an effort to bridge the unmet need of translational predictive biomarkers in stratification of uterine cervix cancer patients based on prognosis. Radiomics features on imaging could be vital in prognostication and prediction of recurrence.

Role of Radiomics and advanced MR imaging (Diffusion MRI) in prediction of molecular phenotypes (P16, EGFR, P53) and Clinical prognostication among Oropharyngeal squamous cell carcinoma (OPSCC)

Human papillomavirus (HPV) and smoking are independent factors affecting survival in OPSCC. Radiomics has emerged as a promising tool for imaging biomarker discovery in era of precision medicine. We investigate the ability of Radiomics to predict molecular phenotype from a study population of OPSCC. Further we explored potential of Radiomics alone and in combination with diffusion imaging derived quantitative parameter apparent diffusion co-efficient (ADC), clinical parameters (addiction- smoking) using supervised classification algorithms in predicting outcomes. Retrospective evaluation of the imaging was conducted for a study cohort of 40 patients in whom p16, EGFR and p53 molecular phenotype was done using immunohistochemistry (IHC). One radiologist having 6 years of experience manually drew the region of interest on the tumor for purposes of segmentation and textural analysis. ADC values were calculated from conventional from the darkest part of the tumor, both before and post treatment with chemo radiation. The segmented tumor was validated independently by two radiologists having 30 years of experience each. A total of 851 Radiomics features were extracted from the available imaging using slicer 3D software and Pyradiomics. Feature selection (48 for molecular phenotype and 32 for clinical determinants) was done by taking the union of the features which had Pearson correlation >0.3 with p16 and EGFR status, > 0.4 for p53, > 0.3 with Grade of tumor and > 0.6 with T Stage. Models were trained to predict the biomarkers using leave one out cross-validation and different algorithms for biomarker prediction and prognostic outcomes (T stage, Grade of tumor and Recurrence). Using Radiomics features alone and different machine learning models in prediction of molecular phenotypes we were able to achieve an accuracy of 89% for p16 and 80% for EGFR. The Kappa score (0.51) and the area under the curve (AUC) was 0.79 for EGFR expression. Using the Monotype multilayer perceptron neural network to determine grade of tumor best results (accuracy 89%, kappa 0.61 and AUC 0.82) were achieved when Radiomics was used alone. The combination of Radiomics with addiction provided better AUC of 0.86 and accuracy of 88%. Accuracy for T staging was 60 % with AUC 0.81, while for recurrence combination of Radiomics, baseline ADC values and clinical addiction gave us best model with accuracy of 81%, AUC 0.76 and kappa of 0.45. (Details in table) The study is an effort to bridge the unmet need of translational predictive biomarkers in stratification of HPV positive OPSCC patients based on prognosis value. Radiomics features on imaging could be vital in deciphering molecular phenotypes, serve as tools for prognostication and predict recurrence.

Renal fibrosis detected by diffusion-weighted magnetic resonance imaging remains unchanged despite treatment in subjects with renovascular disease

Tissue fibrosis is an important index of renal disease progression. Diffusion-weighted magnetic resonance imaging’s (DWI-MRI) apparent diffusion coefficient (ADC) reveals water diffusion is unobstructed by microstructural alterations like fibrosis. We hypothesized that ADC may indicate renal injury and response to therapy in patients with renovascular disease (RVD). RVD patients were treated with medical therapy (MT) and percutaneous transluminal renal angioplasty (MT + PTRA) (n = 11, 3 bilaterally, n = 14 kidneys) or MT (n = 9). ADC and renal hypoxia (R2*) by blood-oxygen-level-dependent MRI were studied before (n = 27) and 3 months after (n = 20) treatment. Twelve patients underwent renal biopsies. Baseline ADC values were correlated with changes in eGFR, serum creatinine (SCr), systolic blood pressure (SBP), renal hypoxia, and renal vein levels of pro-inflammatory marker tumor necrosis-factor (TNF)-α. Renal oxygenation, eGFR, and SCr improved after MT + PTRA. ADC inversely correlated with the histological degree of renal fibrosis, but remained unchanged after MT or MT + PTRA. Basal ADC values correlated modestly with change in SBP, but not in renal hypoxia, TNF-α levels, or renal function. Lower ADC potentially reflects renal injury in RVD patients, but does not change in response to medical or interventional therapy over 3 months. Future studies need to pinpoint indices of kidney recovery potential.

Baseline bone marrow ADC value of diffusion-weighted MRI: a potential independent predictor for progression and death in patients with newly diagnosed multiple myeloma.

To illuminate the prognostic value of ADC (apparent diffusion coefficient), an important quantitative parameter of diffusion-weighted MRI, for multiple myeloma (MM). A prospective single-center study which enrolled 114 consecutive newly diagnosed MM patients with baseline whole-body diffusion-weighted MRI (WB DW-MRI) results was conducted. Baseline clinical and MRI parameters were analyzed with univariate and multivariate approaches to identify independent risk factors for progression-free survival (PFS) and overall survival (OS). Five different DW-MRI patterns were seen, and the mean ADC value of the representative background bone marrow was 0.4662 ± 0.1939 × 10-3 mm2/s. After a mean follow-up of 50.2 months (range, 15.7-75.8 months), twenty-four patients died and seven were lost to follow-up. The mean ADC value of the representative background bone marrow was showed to be an independent risk factor for both PFS (HR 4.664; 95% confidence interval (CI) 1.138-19.121; p = 0.032) and OS (HR 14.130; 95% CI 1.544-129.299; p = 0.019). Normal/salt-and-pepper pattern on DW-MRI was associated with PFS using univariate analysis (p = 0.035) but lost the significance with multivariate Cox regression. Mean ADC value of the representative background bone marrow predicts both PFS and OS which suggests the role of baseline DW-MRI for risk stratification in newly diagnosed MM patients. • Whole-body diffusion-weighted MRI (WB DW-MRI) might be helpful to improve the current risk stratification systems for newly diagnosed multiple myeloma (MM). • Morphological parameters as MRI pattern and focal lesion-associated parameters have been reported to be related to survival. However, important functional parameters such as apparent diffusion coefficient (ADC) values were not incorporated into the current risk stratification model. • This study is one of the first endeavors to delineate the correlation of baseline ADC values and survival in MM patients. It is revealed that the mean ADC value of the representative background bone marrow (L3-S1 and iliac bone) was an independent risk factor for both PFS and OS.

Long-term apparent diffusion coefficient value changes in patients undergoing radiosurgical treatment of meningiomas

A noninvasive method to predict the progress or treatment response of meningiomas is desirable to improve the tumor management. Studies showed that apparent diffusion coefficient (ADC) pretreatment values can predict treatment response in brain tumors. The aim of this study was to analyze changes of intratumoral ADC values in patients with meningiomas undergoing conservative or radiosurgery. MR images of 51 patients with diagnose of meningiomas were retrospectively reviewed. Twenty-five patients undergoing conservative or radiosurgery treatment, respectively, were included in the study. The follow-up data ranged between 1 and 10 years. Based on ROI analysis, the mean ADC values, ADC10%min, and ADC90%max were evaluated at different time points during follow-up. Baseline ADC values in between both groups were similar. The ADCmean values, ADC10%min, and ADC90%max within the different groups did not show any significant changes during the follow-up times in the untreated (ADCmean over 10 years period: 0.87 ± 0.05 × 10-3 mm2/s) and radiosurgically treated (ADCmean over 4 years period: 1.02 ± 0.12 × 10-3 mm2/s) group. However, statistically significant difference was observed when comparing the ADCmean and ADC90%max values of untreated with radiosurgically treated (p < 0.0001) meningiomas. Also, ADC10%min revealed statistically significant difference between the untreated and the radiosurgery group (p < 0.05). ADC values in conservatively managed meningiomas remain stable during the follow-up. However, meningiomas undergoing radiosurgery reveal significant change of the mean ADC values over time, suggesting that ADC may reflect a change in the biological behavior of the tumor. These observations might suggest the value of ADC changes as an indicator of treatment response.

Kidney Functional Magnetic Resonance Imaging and Change in eGFR in Individuals with CKD.

Kidney functional magnetic resonance imaging (MRI) requires further investigation to enhance the noninvasive identification of patients at high risk of CKD progression. In this exploratory study, we obtained baseline diffusion-weighted and blood oxygen level-dependent MRI in 122 participants of the CKD Optimal Management with Binders and Nicotinamide trial, which was a multicenter, randomized, double-blinded, 12-month, four-group parallel trial of nicotinamide and lanthanum carbonate versus placebo conducted in individuals with eGFR 20-45 ml/min per 1.73 m2. Lower values of apparent diffusion coefficient (ADC) on diffusion-weighted MRI may indicate increased fibrosis, and higher values of relaxation rate (R2*) on blood oxygen level-dependent MRI may represent decreased oxygenation. Because there was no effect of active treatment on eGFR over 12 months, we tested whether baseline kidney functional MRI biomarkers were associated with eGFR decline in all 122 participants. In a subset of 87 participants with 12-month follow-up MRI data, we evaluated whether kidney functional MRI biomarkers change over time. Mean baseline eGFR was 32±9 ml/min per 1.73 m2, and mean annual eGFR slope was -2.3 (95% confidence interval [95% CI], -3.4 to -1.1) ml/min per 1.73 m2 per year. After adjustment for baseline covariates, baseline ADC was associated with change in eGFR over time (difference in annual eGFR slope per 1 SD increase in ADC: 1.3 [95% CI, 0.1 to 2.5] ml/min per 1.73 m2 per year, ADC×time interaction P=0.04). This association was no longer significant after further adjustment for albuminuria (difference in annual eGFR slope per 1 SD increase in ADC: 1.0 (95% CI, -0.1 to 2.2) ml/min per 1.73 m2 per year, ADC×time interaction P=0.08). There was no significant association between baseline R2* and change in eGFR over time. In 87 participants with follow-up functional MRI, ADC and R2* values remained stable over 12 months (intraclass correlation: 0.71 and 0.68, respectively). Baseline cortical ADC was associated with change in eGFR over time, but this association was not independent of albuminuria. Kidney functional MRI biomarkers remained stable over 1 year. CKD Optimal Management with Binders and Nicotinamide (COMBINE), NCT02258074.

ADC as a predictor of pathologic response to neoadjuvant therapy in esophageal cancer: a systematic review and meta-analysis.

Diffusion-weighted magnetic resonance imaging (DWI) is part of clinical practice. The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) as a predictor of pathologic response to neoadjuvant therapy (nCRT) in patients with esophageal cancer (EC). The MEDLINE, Embase, and Google Scholar databases were systematically searched for studies using ADC to evaluate response to neoadjuvant therapy in patients with EC. Methodological quality of the studies was evaluated with the QUADAS tool. Data from eligible studies were extracted and evaluated by two independent reviewers. Meta-analyses were performed comparing mean ADC values between responders and non-responders to nCRT in three different scenarios: baseline (BL) absolute values; percent change between intermediate (IM) values and BL; and percent change between final follow-up (FU) value and baseline BL. Seven studies (n = 158 patients) were included. Responders exhibited a statistically significant percent increase in ADC during nCRT (mean difference [MD] 21.06%, 95%CI = 13.04-29.09; I2= 49%; p = 0.12). A similar increase was identified in the complete pathologic response (pCR) versus non-complete pathologic response (npCR) subgroup (MD = 25.68%, 95%CI = 18.87-32.48; I2= 0%; p = 0.60). At the end of treatment, responders also exhibited a statistically significant percent increase in ADC (MD = 22.49%, 95%CI = 9.94-35.05; I2= 0%; p = 0.46). BL ADC was not associated with any definition of pathologic response (MD = 0.11%, 95%CI = - 0.21-0.42; I2= 85%; p < 0.01). These results suggest that ADC can be used as a predictor of pathologic response, with a statistically significant association between percent ADC increase during and after treatment and pCR. ADC may serve as a tool to help in guiding clinical decisions. • DWI is routinely included in MRI oncological protocols. • ADC can be used as a predictor of pathologic response, with a statistically significant association between percent ADC increase during and after treatment and pCR.

Predictive role of Apparent Diffusion Coefficient (ADC) from Diffusion Weighted MRI in patients with sacral chordoma treated with carbon ion radiotherapy (CIRT) alone

PurposeTo evaluate if baseline ADC from DWI sequences could predict response to treatment in patients with sacral chordoma not suitable for surgery treated with carbon ion radiotherapy (CIRT) alone compared with volume changes. MethodsFifty-nine patients with sacral chordoma not suitable for surgery underwent one cycle of CIRT alone and a minimum of 12-months follow-up. All patients underwent MRI before treatment (baseline), every three months in the first two years after treatment, and every six months afterwards. For each MRI, lesion volume was obtained and median, kurtosis, and skewness ADC were analyzed within the whole lesion volume. Volume changes between baseline and the last available follow-up were used to divide patients with partial response, progression of disease and stable disease (PR, PD, and SD). ResultsTen patients were excluded since DWI sequences from baseline MRI were not available. ADC maps obtained from baseline DWI examinations of 50 lesions in the remaining 49 patients were considered. Seven lesions were categorized as PD, 30 PR, and 13 SD. PD showed significantly higher median ADC values at baseline (p = 0.003) compared with both PR and SD (1665vs1253vs1263 *10−6 mm²/s), and more negative skewness values (-0.26vs0.26vs0.08), although not significantly different (p = 0.16). ConclusionsPreliminary results suggest that baseline ADC could predict response to treatment with CIRT, particularly to detect potential non-responder patients.

Diffusion-weighted MRI in Advanced Epithelial Ovarian Cancer: Apparent Diffusion Coefficient as a Response Marker

Background Treatment of advanced epithelial ovarian cancer results in a relapse rate of 75%. Early markers of response would enable optimization of management and improved outcome in both primary and recurrent disease. Purpose To assess the apparent diffusion coefficient (ADC), derived from diffusion-weighted MRI, as an indicator of response, progression-free survival (PFS), and overall survival. Materials and Methods This prospective multicenter trial (from 2012-2016) recruited participants with stage III or IV ovarian, primary peritoneal, or fallopian tube cancer (newly diagnosed, cohort one; relapsed, cohort two) scheduled for platinum-based chemotherapy, with interval debulking surgery in cohort one. Cohort one underwent two baseline MRI examinations separated by 0-7 days to assess ADC repeatability; an additional MRI was performed after three treatment cycles. Cohort two underwent imaging at baseline and after one and three treatment cycles. ADC changes in responders and nonresponders were compared (Wilcoxon rank sum tests). PFS and overall survival were assessed by using a multivariable Cox model. Results A total of 125 participants (median age, 63.3 years [interquartile range, 57.0-70.7 years]; 125 women; cohort one, n = 47; cohort two, n = 78) were included. Baseline ADC (range, 77-258 × 10-5mm2s-1) was repeatable (upper and lower 95% limits of agreement of 12 × 10-5mm2s-1 [95% confidence interval {CI}: 6 × 10-5mm2s-1 to 18 × 10-5mm2s-1] and -15 × 10-5mm2s-1 [95% CI: -21 × 10-5mm2s-1 to -9 × 10-5mm2s-1]). ADC increased in 47% of cohort two after one treatment cycle, and in 58% and 53% of cohorts one and two, respectively, after three cycles. Percentage change from baseline differed between responders and nonresponders after three cycles (16.6% vs 3.9%; P = .02 [biochemical response definition]; 19.0% vs 6.2%; P = .04 [radiologic definition]). ADC increase after one cycle was associated with longer PFS in cohort two (adjusted hazard ratio, 0.86; 95% CI: 0.75, 0.98; P = .03). ADC change was not indicative of overall survival for either cohort. Conclusion After three cycles of platinum-based chemotherapy, apparent diffusion coefficient (ADC) changes are indicative of response. After one treatment cycle, increased ADC is indicative of improved progression-free survival in relapsed disease. Published under a CC BY 4.0 license. Online supplemental material is available for this article.

The Value of Magnetic Resonance Imaging to Assessing Response and Prognosis to Total Neoadjuvant Treatment (TNT) in Locally Advanced Rectal Cancer

To investigate the potential value of magnetic resonance imaging (MRI) in assessing response and prognostic relevance to total neoadjuvant treatment (TNT) in locally advanced rectal cancer (LARC) with high risk factors. This was a retrospective study of pre-, during, and post-TNT MRI of patients with LARC with high risk factors who underwent TNT before operation. Patients received three cycles of induction chemotherapy (ICT) followed by neoadjuvant radiotherapy and 2 cycles of concurrent chemotherapy (CRT).After that, 3 cycles of consolidation chemotherapy (CCT) were delivered. Radiation dose of pelvic IMRT/VMRT was 50.4 Gy/28f. MRI scans were performed before TNT (baseline), after CRT (post-CRT) and after CCT(post-CCT), respectively. MRI parameters such as the apparent diffusion coefficient (ADC) values of tumor, T2 adjusted values of tumor (T2 values of tumor/T2 values of gluteus maximus muscle) (T2a), maximum cross-sectional area of tumor on diffusion-weighted imaging (SDWI) and T2-weight (ST2), the numbers of lymph node metastases (LNN) and diameter of lymph node (LND), were measured by two experienced readers independently. In addition, the changes in MRI parameters relative to baseline were calculated. Spearman’s correlation coefficient and Wilcoxon’s rank sum test were used to assess association between MRI parameters and complete response (CR). Cox regression was used to evaluate association between MRI parameters and OS/DFS. We analyzed MRI images of 52 patients who underwent TNT from 2015 to 2017 retrospectively. Among them, there were 22 patients (42%) who achieved CR, including 15 pathologic CR (pCR) in those who underwent surgery and 7 clinical CR (cCR). The median follow-up was 30 months (11-39 months). As to the baseline MRI parameters, only ADC was correlated with CR (r=0.312, p=0.026). 1 and 2-year OS rate of the whole cohort was 98.1% and 93.2%, respectively. 1 and 2-year DFS rate were 92.3% and 84.3%, respectively. Multivariate analysis showed that baseline T2a ≥5 (HR 0.048, 95% CI 0.009 - 0.265; p<0.001) and baseline SDWI ≥2cm2 (HR 17.875, 95% CI 1.854-172.306; p=0.013) were independent prognostic factors for unfavorable DFS. There were 25 patients who had complete baseline, post-CRT, and post-CCT MRI images. For these patients, baseline ADC (r=0.544, p=0.005), post-CCT ADC (r=0.522, p=0.007), ΔADC (post-CCT relative to baseline) (r=0.522, p=0.007), post-CRT LNN (r=-0.400, p=0.047), ΔLNN (post-CRT relative to baseline) (r=0.677, p=0.000199), and ΔLND (post-CRT relative to baseline) (r=0.594, p=0.002) were correlated with CR. ΔSDWI (post-CRT relative to baseline) >30 cm2 (HR 0.036, 95% CI 0.004 - 0.363; p=0.005) was independent prognostic factor for better DFS. Baseline ADC, ΔADC, ΔLNN, and ΔLND seem to have correlation with response to TNT. T2 adjusted value, baseline SDWI and ΔSDWI > 30 cm2 might relate to better DFS.

Imaging Biomarkers Multiparametric 3 Tesla MRI and FMISO Hypoxia PET during Chemoradiotherapy in HNSCC and Their Relation to Outcome

To prospectively assess in HNSCC patients the effect of chemoradiotherapy (CRT) on tumor hypoxia and tissue properties with [18F]FMISO PET/CT (FMISO PET) and multiparametric (mp) MRI at baseline and at an early (week 2) and late (week 5) time point during treatment and to analyze whether mpMRI and PET parameters are related with outcome. Patients with stage III to IVb HNSCC undergoing definitive CRT (total dose 70 Gy, 3 cycles of cisplatin over 7 weeks) were included. Patients were prospectively imaged with [18F]FDG PET/CT at baseline and with serial FMISO PET and serial 3 Tesla mpMRI for T1w-, T2w- as well as contrast-enhanced perfusion and diffusion-weighted measurements (ktrans, ve and apparent diffusion coefficient (ADC) maps) in weeks 0, 2 and 5. Patients were identified as responders or non-responders during follow-up regarding loco-regional control (LRC) and overall survival (OS). Tumor volumes were contoured and SUVmax FMISO PET and mean values for mpMRI parameters were compared between responders and non-responders with the t-test and Log Rank test at a significance level of p≤0.05. A complete set of serial FMISO PET data and 3 T MRI was available in 21 patients. Of those, 12 patients were diagnosed with local recurrence. Baseline tumor volume and FMISO-PET-derived tumor hypoxia (SUVmax FMISO) were higher among patients with local recurrence as compared to locally controlled patients (p=n.s.). On Kaplan-Meier analysis stratified at median change in SUVmax FMISO between weeks 0 to 5 (ΔFMISOwk0-5), LRC was higher for ΔFMISOwk0-5 > median (p=n.s.). For ADC, an increase was found from week 0 to 5 (responders > non-responders). LRC was significantly higher for patients with ΔADCwk0-5 and %ΔADCwk0-5 > median (Log Rank, p=0.04 and p=0.005). In perfusion MRI, ktrans increased from week 0 to 5 for both non-responders and responders (p=n.s.). For non-responders, ktrans reached a maximum at week 2, while for responders, ktrans showed a steady increase until week 5. Interstitial space volume fraction ve did not differ significantly between responders and non-responders and increased between week 0 and 5 (p=n.s.). Baseline ADC below median was significantly (p=0.013) correlated with improved OS. ADCweek2 below median was associated with improved OS (p=n.s.). Baseline ve below median was significantly correlated with improved OS (p=0.043) and associated with increased LRC (p=n.s.). Multiparametric MRI parameters ADC and interstitial space volume fraction ve obtained at baseline were significantly correlated with improved OS and an increase of ADC between week 0 to 5 was significantly correlated with improved LRC. FMISO-PET-derived tumor hypoxia and mean values of MRI parameters ktrans and ve differed between relapsing and non-relapsing patients, however without reaching statistical significance in this cohort. The correlations found for ve and ADC may suggest predictive power for OS and LRC depending on baseline imaging and the dynamics of ADC.