Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis for Assessing Normal-Sized Lymph Node Metastasis in Cervical Cancer: Comparison Between Readout-Segmented and Single-Shot Echo-Planar Diffusion-Weighted Imaging.

The Usefulness of Apparent Diffusion Coefficient Maps in the Evaluation of Radiation Therapy for Primary Central Nerve System Lymphoma

Multimodal imaging has been increasingly used in oncology, especially in cervical cancer. By using a simultaneous positron emission (PET) and magnetic resonance imaging (MRI, PET/MRI) approach, PET and MRI can be obtained at the same time which minimizes motion artefacts and allows an exact imaging fusion, which is especially important in anatomically complex regions like the pelvis. The associations between functional parameters from MRI and 18F-FDG-PET reflecting different tumor aspects are complex with inconclusive results in cervical cancer. The present study correlates histogram analysis and 18F-FDG-PET parameters derived from simultaneous FDG-PET/MRI in cervical cancer. Overall, 18 female patients (age range: 32–79 years) with histopathologically confirmed squamous cell cervical carcinoma were retrospectively enrolled. All 18 patients underwent a whole-body simultaneous 18F-FDG-PET/MRI, including diffusion-weighted imaging (DWI) using b-values 0 and 1000 s/mm2. Apparent diffusion coefficient (ADC) histogram parameters included several percentiles, mean, min, max, mode, median, skewness, kurtosis, and entropy. Furthermore, mean and maximum standardized uptake values (SUVmean and SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were estimated. No statistically significant correlations were observed between SUVmax or SUVmean and ADC histogram parameters. TLG correlated inversely with p25 (r=−0.486, P=0.041), p75 (r=−0.490, P=0.039), p90 (r=−0.513, P=0.029), ADC median (r=−0.497, P=0.036), and ADC mode (r=−0.546, P=0.019). MTV also showed significant correlations with several ADC parameters: mean (r=−0.546, P=0.019), p10 (r=−0.473, P=0.047), p25 (r=−0.569, P=0.014), p75 (r=−0.576, P=0.012), p90 (r=−0.585, P=0.011), ADC median (r=−0.577, P=0.012), and ADC mode (r=−0.597, P=0.009). ADC histogram analysis and volume-based metabolic 18F-FDG-PET parameters are related to each other in cervical cancer.

ADC histogram analysis for prediciting highly aggressive breast carcinomas

The objective of this study was to explore whether volumetric apparent diffusion coefficient (ADC) histogram analysis can provide additional value to Vesical Imaging Reporting and Data System (VI-RADS) in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC). 80 patients were retrospectively reviewed with pathologically proven NMIBC (n = 53) or MIBC (n = 27). All patients underwent MRI including diffusion-weighted imaging (DWI) (b = 0, 800s/mm2), and the VI-RADS score was evaluated based on DWI. Volumetric ADC histogram parameters were calculated from the volumetric of interest (VOI) on DWI, including the min ADC, mean ADC, median ADC, max ADC, 10th, 25th, 75th, 90th percentiles ADC, skewness, kurtosis, and entropy. The Mann-Whitney U-test was used to compare histogram parameters between NMIBC and MIBC. Receiver operating characteristic analysis was used to evaluate the diagnostic value of each significant parameter. Among all parameters, the VI-RADS yield the highest Area Under the Curve (AUC, 0.88; sensitivity, 88.89%; specificity, 83.61%). MIBC had significantly lower min ADC, mean ADC, median ADC, 10th, 25th, 75th, and 90th percentiles ADC than NMIBC (p = 0.002, p < 0.001, p < 0.001, p = 0.003, p = 0.004, p < 0.001, p < 0.001). Skewness and kurtosis of MIBC were significantly higher than those of NMIBC (p < 0.001, p < 0.001). The combination of VI-RADS and skewness showed significantly higher AUC (AUC 0.923; 95% CI 0.847-0.969) than only with VI-RADS (AUC 0.880; 95% CI 0.793-0.940). Volumetric ADC histogram analysis and VI-RADS are both useful methods in differentiating MIBC from NMIBC, and the volumetric ADC histogram analysis can provide additional value to VI-RADS.

Apparent diffusion coefficient values and normalised apparent diffusion coefficient values in grading of glioma

The aim of this study was to assess the effect of differences in acquisition technique on whole-brain apparent diffusion coefficient (ADC) histogram parameters, as well as to assess scan-rescan reproducibility. Diffusion-weighted imaging (DWI) was performed in 7 healthy subjects with b-values 0-800, 0-1000, and 0-1500 s/mm(2) and fluid-attenuated inversion recovery (FLAIR) DWI with b-values 0-1000 s/mm(2). All sequences were repeated with and without repositioning. The peak location, peak height, and mean ADC of the ADC histograms and mean ADC of a region of interest (ROI) in the white matter were compared using paired-sample t tests. Scan-rescan reproducibility was assessed using paired-sample t tests, and repeatability coefficients were reported. With increasing maximum b-values, ADC histograms shifted to lower values, with an increase in peak height ( p<0.01). With FLAIR DWI, the ADC histogram shifted to lower values with a significantly higher, narrower peak ( p<0.01), although the ROI mean ADC showed no significant differences. For scan-rescan reproducibility, no significant differences were observed. Different DWI pulse sequences give rise to different ADC histograms. With a given pulse sequence, however, ADC histogram analysis is a robust and reproducible technique. Using FLAIR DWI, the partial-voluming effect of cerebrospinal fluid, and thus its confounding effect on histogram analyses, can be reduced.

To determine if apparent diffusion coefficient (ADC) histogram analysis can stratify progression-free survival in patients with recurrent glioblastoma multiforme (GBM) prior to bevacizumab treatment. The study was approved by the institutional review board and was HIPAA compliant; informed consent was obtained. Bevacizumab-treated and control patients (41 per cohort) diagnosed with recurrent GBM were analyzed by using whole enhancing tumor ADC histograms with a two normal distribution mixture fitting curve on baseline (pretreatment) magnetic resonance (MR) images to generate ADC classifiers, including the overall mean ADC as well as the mean ADC from the lower curve (ADC(L)). Overall and 6-month progression-free survival (as defined by the Macdonald criteria) was determined by using Cox proportional hazard ratios and the Kaplan-Meier method with log-rank test. For bevacizumab-treated patients, the hazard ratio for progression by 6 months in patients with less than versus greater than mean ADC(L) was 4.1 (95% confidence interval: 1.6, 10.4), and there was a 2.75-fold reduction in the median time to progression. For the control patients, there was no significant difference in median time to progression for the patients with low versus high ADC(L) (hazard ratio, 1.8; 95% confidence interval: 0.9, 3.7). For bevacizumab-treated patients, pretreatment ADC more accurately stratified 6-month progression-free survival than did change in enhancing tumor volume at first follow-up (73% vs 58% accuracy, P = .034). Pretreatment ADC histogram analysis can stratify progression-free survival in bevacizumab-treated patients with recurrent GBM.

Diffusion-weighted imaging (DWI) using single-shot echo-planar imaging (ss-EPI) is prone to artifacts, geometric distortion, and T2* blurring. Readout-segmented echo-planar imaging (rs-EPI) may improve image quality in the DWI of cervical cancer (CC). This study aimed to compare the image quality between rs-EPI and ss-EPI DWI in CC and to evaluate whether the apparent diffusion coefficient (ADC) values of ss-EPI (ssADC) and rs-EPI (rsADC) can differentiate the status of lymphovascular space invasion (LVSI) and lymph node metastasis (LNM). This prospective study included 69 patients with CC who underwent ss-EPI and rs-EPI DWI before surgery. Qualitative reader scores, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC values derived from ss-EPI and rs-EPI were compared. The differences in ADC values were analyzed in patients who were (a) LNM-positive (LNM+, n = 17) and LNM-negative (LNM-, n = 52); (b) LVSI-positive (LVSI+, n = 33) and LVSI-negative (LVSI-, n = 36). The rs-EPIs of CC had higher subjective image quality scores and a lower SNR than ss-EPI (all P < 0.001); no significant differences existed between rs-EPI and ss-EPI for either CNR or ADC (CNR, P = 0.313; ADC, P = 0.949; P > 0.05 for all). The rsADC and ssADC of the LNM+ group were substantially lower than those of the LNM- group (rsADC, P = 0.000; ssADC, P = 0.000; P < 0.001 for all); the areas under the receiver operating characteristic curve were 0.855 and 0.851, respectively. However, there were no differences in ADC values between the LVSI+ and LVSI- groups (rsADC, P = 0.271; ssADC, P = 0.200; P > 0.05 for all). Over a similar scan time, rs-EPI improves the qualitative image quality of DWI significantly more than ss-EPI and has good diagnostic accuracy for LNM status in CC. However, neither could predict the LVSI status. Readout-segmented EPI improves the qualitative image quality of DWI and has good diagnostic accuracy for LNM status in CC, compared with conventional ss-EPI. It is more inclined to qualitative analysis of CC foci and provides a better scheme when choosing the DWI sequence scanning strategy for CC.

Objective To compare ADC values obtained from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) techniques of prostate cancer and to investigate the correlation between RS-EPI ADC values and Gleason scores. Methods A retrospective analysis of RS-EPI and SS-EPI DWI were performed in 23 patients with pathologically confirmed prostate cancer. Routine MRI, RS-EPI DWI and SS-EPI DWI were obtained prior to ultrasound guided systemic biopsy in all cases. According to the location of lesion from biopsy report, a ROI was drawn on ADC map obtained from RS-EPI DWI and SS-EPI DWI, respectively, at cancerous foci with low T2WI and high DWI signal intensity. Foci were classified into well differentiated group (Gleason score≤6) and poorly and moderately differentiated group (Gleason score≥7). ADC values between RS-EPI and SS-EPI were compared by using t test. The relationship between ADC values and Gleason scores was assessed using Spearman test. The sensitivity and specificity of RS-EPI ADC value for differential diagnosis of two groups and the best cutoff were evaluated from ROC. Results Twenty nine well differentiated foci and 126 poorly and moderately differentiated foci were identified. The mean RS-EPI ADC value and the mean SS-EPI ADC value of well differentiated group and poorly and moderately differentiated group were (1.136 ± 0.136) × 10-3mm2/s, (1.125±0.198)×10-3mm2/s; (0.891±0.161)×10-3mm2/s, (0.875 ±0.184)×10-3mm2/s, respectively. Neither well differentiated group nor poorly and moderately differentiated group had a significant difference between the mean ADC value of two techniques (t values were 0.359 and 1.727, P values were 0.722 and 0.087, respectively). Either mean RS-EPI ADC value or mean SS-EPI ADC value between two groups had a significant difference (t values were 7.572 and 6.499, P<0.01, respectively). There was an inverse relationship between ADC values obtained from RS-EPI and SS-EPI and Gleason scores (r values were -0.638 and -0.565, P<0.01, respectively). When the cutoff value was 1.041×10-3mm2/s, the sensitivity and specificity of RS-EPI ADC value to differentiate two groups were 85.7% (108/126), 86.2% (25/29), respectively, and the area under ROC curve was 0.882. Conclusions There were no significant difference between ADC values obtained from RS-EPI and SS-EPI. ADC values of both techniques had positive correlation with Gleason scores. RS-EPI ADC values may have potential to allow noninvasive assessment of prostate cancer aggressiveness, which could help in the stratification of patients for appropriate therapy. Key words: Prostate neoplasms; Magnetic resonance imaging; Pathology

This study was designed to investigate the preoperative prediction of the mid-term efficacy of high-intensity focused ultrasound (HIFU) in the treatment of uterine fibroids by apparent diffusion coefficient (ADC) histogram analysis. Eighty-six patients with a total of 101 uterine fibroids were retrospectively collected consecutively. The region of interest (ROI) was outlined layer by layer on diffusion-weighted imaging (DWI) images with b = 1000s/mm2 to obtain ADC histogram parameters, including the mean, maximum, minimum, 10th, 25th, 50th, 75th and 90th percentiles as well as skewness, kurtosis, and entropy. The volume reduction rate (VRR) of fibroids at 6 months postoperatively was calculated as an indicator of the mid-term effect, and according to the VRR, the cohort was divided into a markedly effective group (VRR ≥ 50%) and a nonmarkedly effective group (VRR < 50%). Differences in ADC histogram parameters between the markedly effective and nonmarkedly effective groups were analyzed by applying univariate and multivariate binary logistic regression to screen out statistically significant indicators, and the predictive efficacy of the relevant ADC histogram parameters was assessed by receiver operating characteristic (ROC) curves. The markedly effective group included 42 fibroids, and the noneffective group included 59 fibroids. The results of the univariate analysis showed that ADCmean, ADCmax, ADC10th, ADC25th, skewness, kurtosis, and entropy were significantly different between the two groups. The results of the multivariate analysis showed that ADC10th and skewness were statistically significant indicators, the area under the ROC curve (AUC) was 0.678 and 0.739, respectively, and the combined AUC of the two was 0.790. Major study limitations include: this is a single-center retrospective study, the investigator manually segmented the lesions, and no further analysis of postoperative pathology regarding the findings of the study. ADC histogram analysis helps to preoperatively predict the mid-term efficacy of HIFU in the treatment of uterine fibroids. ADC10th and skewness are independent predictors of the mid-term efficacy of HIFU, and the combined efficacy of the two is superior to that of a single indicator.

The purpose of this study was to evaluate quantitative apparent diffusion coefficient (ADC) metrics for the downgrading of Gleason score (GS) 9 or 10 prostate cancer (PCa) diagnosed by means of nontargeted transrectal ultrasound-guided biopsy. Between 2012 and 2015, 30 men with a diagnosis of GS 9 or 10 PCa at nontargeted transrectal ultrasound-guided biopsy underwent 3-T multiparametric MRI before radical prostatectomy (RP). Two radiologists blinded to the histopathologic results independently assessed multiparametric MR images using Prostate Imaging Reporting and Data System (PI-RADS) version 2. Whole-lesion ADC mean, centile, and texture features were extracted from coregistered ADC and RP maps by a third blinded radiologist. Comparisons were performed by chi-square, multivariable logistic regression, and ROC analysis. Tumors were downgraded to intermediate risk (GS 4 + 3 [n = 7] and GS 3 + 4 [n = 2]) PCa in 30.0% (9/30) of men after RP. There were no statistically significant differences between groups with respect to age (p = 0.028), prostate-specific antigen level (p = 0.018), or clinical stage (p = 0.021). PI-RADS version 2 scores did not differ between groups (p = 0.035, p = 0.091) with moderate agreement (κ = 0.48). There were no differences in mean or centile ADC (p = 0.269-0.634) between the two groups. ADC entropy was significantly lower in downgraded tumors (5.542 ± 0.721 [SD] vs 8.089 ± 1.237, p < 0.001) with no difference in kurtosis or skewness (p = 0.133, p = 0.296). The ROC AUC for the diagnosis of downgrading was 0.93 (95% CI, 0.84-1.00) with sensitivity of 85.7% and specificity of 88.9% when entropy was less than 6.31. ADC entropy was significantly lower in GS 9 and 10 tumors diagnosed by means of nontargeted transrectal ultrasound-guided biopsy that were eventually downgraded to intermediate risk (GS 7) after RP. ADC texture analysis may be useful for further risk stratification of PCa diagnosed at biopsy.

BackgroundQuantitative diffusion-weighted imaging (DWI) probes into tissue microstructure in solid tumours. In this retrospective ethically approved study, we investigated DWI as a potential non-invasive predictor of tumour dignity and prognosis in paediatric patients with neuroblastic tumours.MethodsNineteen consecutive patients with neuroblastoma (NB, n = 15), ganglioneuroblastoma (GNB, n = 1) and ganglioneuroma (GN, n = 3) underwent 3-T magnetic resonance imaging at first diagnosis and after 3-month follow-up, following a protocol including DWI (b = 50 and 800 s/mm2) in addition to standard sequences. All DWI scans were analysed for tumour volume assessment and apparent diffusion coefficient (ADC) calculation. Correlation with tumour pathology and risk factors (bone-marrow metastases, MYCN-amplification and 1p-deletion), therapeutic regime (observation versus chemotherapy) and clinical follow-up was evaluated.ResultsAt baseline, mean ADC in NB was lower than in GNB/GN (0.76 vs. 1.47 × 10−3 mm2/s, p = 0.003). An ADC cutoff ≤ 1.05 identified malignant disease with 100.0% sensitivity (95% confidence interval [CI] 29.2–100.0%) and 93.8% specificity (95% CI 69.8–99.8%). Initial ADC was < 0.80 in all NB patients with eventual tumour relapse. During follow-up, tumour ADC values increased in the observation group (NB/GN) without relapse (p = 0.043). In eventually relapsing tumours, ADC values at follow-up tended to decrease further despite reduction in tumour volume.ConclusionsADC values at first presentation differed significantly between malignant and benign neuroblastic tumours. Low baseline ADC was predictive of tumour progression and relapse in NB patients. With therapy, increasing ADC values appeared to predict relapse-free survival, while a decreasing ADC during therapy was an indicator of poor prognosis.

T2-Weighted Imaging and Apparent Diffusion Coefficient Histogram Parameters Predict Meningioma Consistency

PurposeGlioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.MethodsPre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics.ResultsGrade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG.ConclusionsADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.

PurposeThis study investigated the breast lesion conspicuity and apparent diffusion coefficient (ADC) reliability for three different diffusion-weighted imaging (DWI) protocols: spatiotemporal encoding (SPEN), single-shot echo-planar imaging (SS-EPI), and readout segmentation of long variable echo-trains (RESOLVE).MethodsSixty-five women suspected of having breast tumors were included in this study, with 44 lesions (36 malignant, 8 benign) analyzed further. Breast MRI was performed on a 3 Tesla (3T) system (MAGNETOM Prisma, Siemens) equipped with a dedicated 18-channel breast array coil for a phantom and patients. Three DWI protocols—SPEN, SS-EPI, and RESOLVE—were used. SS-EPI was acquired with an in-plane resolution of 2 × 2 mm2, a slice thickness of 3 mm, and b-values of 0 and 1000 s/mm2. SPEN had a higher in-plane resolution of 1 × 1 mm2, a slice thickness of 1.5 mm, and b-values of 0, 850, and 1500 s/mm2. RESOLVE was acquired with an in-plane resolution of 1 × 1 mm2, a slice thickness of 1.5 mm, and b-values of 0 and 850 s/mm2. Lesion conspicuity and ADC values were evaluated.ResultsThe average lesion conspicuity scores were significantly higher for RESOLVE (3.54 ± 0.65) than for SPEN (3.07 ± 0.91) or SS-EPI (2.48 ± 0.78) (P < 0.01). The SPEN score was significantly higher than the SS-EPI score (P < 0.01). Phantom measurements indicated marginally lower ADC values for SPEN compared to SS-EPI and RESOLVE across all concentrations. The results revealed that SPEN (b = 0, 850, 1500 sec/mm2) yielded significantly lower ADC values compared to SPEN (b = 0, 850 sec/mm2) in malignant lesions (P < 0.01), with no significant difference observed between SPEN (b = 0, 850 sec/mm2), SS-EPI, and RESOLVE. For benign lesions, no significant difference in ADC values was found between SPEN (b = 0, 850 sec/mm2), SPEN (b = 0, 850, 1500 sec/mm2), SS-EPI, and RESOLVE.ConclusionRESOLVE provided the highest lesion conspicuity, and ADC values in breast lesions were not significantly different among sequences ranging b values 850–1000 sec/mm2. SPEN with higher b-values (0, 850, 1500 vs. 0, 850 sec/mm2) yielded significantly lower ADC values in malignant lesions, highlighting the importance of b-value selection in ADC quantification.