Volumetric Apparent Diffusion Coefficient Histogram Research Articles

Volumetric apparent diffusion coefficient histogram analysis in term neonatal asphyxia treated with hypothermia.

Our aim is to estimate the long-term neurological sequelae and prognosis in term neonatal asphyxia treated with hypothermia via volumetric apparent diffusion coefficient (ADC) map histogram analysis (HA). Brain MRI studies of eighty-three term neonates with asphyxia who received whole-body hypothermia treatment and examined between postnatal (PN) 4 to 6th days were retrospectively re-evaluated by two radiologists. Volumetric HA was performed for the areas frequently affected in deep and superficial asphyxia (thalamus, lentiform nucleus, posterior limb of internal capsule, corpus callosum forceps major and perirolandic cortex-subcortical white matter) on ADC map. The quantitative ADC values were obtained separately for each region. Qualitative-visual (conventional) MRI findings were also re-evaluated. Neonates were examined neurodevelopmentally according to the Revised Brunet-Lezine scale. The distinguishability of long-term neurodevelopmental outcomes was statistically investigated. With HA, the adverse neurodevelopmental outcomes could only be distinguished from mild-moderated impairment and normal development at the thalamus with 10th percentile ADC (p = 0.02 and p = 0.03; respectively) and ADCmin (p = 0.03 and p = 0.04; respectively). Also with the conventional MRI findings, adverse outcome could be distinguished from mild-moderated impairment (p = 0.04) and normal development (p = 0.04) via cytotoxic edema of the thalamus, corpus striatum and diffuse cerebral cortical. The long-term adverse neurodevelopmental outcomes in newborns with asphyxia who received whole-body hypothermia treatment can be estimate similarly with volumetric ADC-HA and the conventional assessment of the ADC map. This study compare early MRI ADC-HA with neurological sequelae in term newborns with asphyxia who received whole-body hypothermia treatment. We couldn't find any significant difference in predicting adverse neurological sequelae between the visual-qualitative evaluation of the ADC map and HA.

Volumetric apparent diffusion coefficient histogram analysis for determining the degree of differentiation of periampullary carcinomas

Background/Aim: The classification of periampullary adenocarcinomas into pancreatobiliary-type periampullary adenocarcinoma and intestinal-type periampullary adenocarcinoma (PPAC and IPAC, respectively) has gained significant acceptance in the medical community. A patient's prognosis is determined by the degree of differentiation of these tumor types. The objective of the present investigation was to assess the efficacy of volumetric apparent diffusion coefficient (ADC) histogram analysis in assessing the degree of differentiation for these two tumor types. Methods: This retrospective cohort research evaluated 54 PPAC (45 well-differentiated and nine poorly differentiated) and 15 IPAC (11 well-differentiated and four poorly differentiated) patients. Magnetic resonance imaging (1.5 T MRI) scans were used to evaluate the results. The features of the histogram for the ADC values were computed and incorporated several statistical measures, such as the mean, minimum, median, maximum, and percentiles in addition to the skewness, kurtosis, and variance. Results: In both PPAC and IPAC patients, the ADC values exhibited lower values in the poorly differentiated group when compared with the well-differentiated group. However, the changes between groups did not reach statistical significance. Among IPAC patients, the well-differentiated group had a larger kurtosis (P=0.048). In IPAC patients, the calculated value for the area under the curve (AUC) of kurtosis was determined to be 0.818. When the threshold was set at 0.123, the specificity and sensitivity were observed to be 90% and 75%, respectively. Conclusion: Our research indicates that the kurtosis of ADC is an effective indicator to determine the level of IPAC differentiation. Analysis of the histogram at increased b values can provide valuable insights to help determine the degree of differentiation of IPAC using a noninvasive technique.

Differentiation of bladder cancer stages using the vesical imaging -reporting and data system and apparent diffusion coefficient.

T stage is closely related to the treatment and prognosis of patients with bladder cancer (BC). However, preoperative T staging is still challenging. Multiparametric magnetic resonance imaging (mpMRI) may be valuable. This study was performed to explore the value of the Vesical Imaging-Reporting and Data System (VI-RADS) and the volumetric apparent diffusion coefficient (ADC) histogram parameters in detecting T2 stage and below stage (≤T2 stage) from T3 stage and above stage (≥T3 stage) BCs. The study included 62 patients (mean age, males vs. females: 62.1±10.9 vs. 61.8±11.7 years) with BC pathologically confirmed by partial or radical cystectomy. All of the tumors were scored normatively by two radiologists using the VI-RADS scoring system by two radiologists. The volumetric ADC histogram of each lesion was obtained from the ADC maps. The Cochran-Armitage test was used to examine the relevance between VI-RADS scores and T stages. The Mann-Whitney U test was used to compare the histogram parameters between ≤T2 stage and ≥T3 stage BCs. A receiver operating characteristic (ROC) curve was used to assess the predictive power of each model. The minimum ADC; mean ADC; median ADC; maximum ADC; and 10th, 25th, 75th, and 90th percentile ADC of ≤T2 stage BCs were significantly higher than those of ≥T3 stage BCs, while skewness and kurtosis had opposite results. VI-RADS achieved the highest area under the curve (AUC) of 0.834 among all parameters. The combination of VI-RADS, skewness and kurtosis yield a significantly higher AUC than VI-RADS alone (0.915 vs. 0.834, P=0.0478). VI-RADS and volume ADC histogram analysis can effectively discriminate between ≤T2 stage and ≥T3 stage BCs, and the volumetric ADC histogram can provide further information to supplement VI-RADS.

Analysis of Pancreatobiliary and Intestinal Type Periampullary Carcinomas Using Volumetric Apparent Diffusion Coefficient Histograms

Magnetic resonance imaging plays an important role in the evaluation of patients with known or suspected periampullary masses. The utilization of volumetric apparent diffusion coefficient (ADC) histogram evaluation for the entire lesion eradicates the potential for subjectivity in the region of interest placement, thus guaranteeing the accuracy of computation and repeatability. To investigate the value of volumetric ADC histogram analysis in the differentiation of intestinal-type (IPAC) and pancreatobiliary-type periampullary adenocarcinomas (PPAC). This retrospective study included 69 patients with histopathologically confirmed periampullary adenocarcinoma (54 PPAC and 15 IPAC). Diffusion-weighted imaging was obtained at b values of 1000mm²/s. The histogram parameters of ADC values, comprising the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance, were calculated independently by two radiologists. Using the interclass correlation coefficient, the interobserver agreement was evaluated. The ADC parameters for the PPAC group were all lower than those of the IPAC group. The PPAC group had higher variance, skewness, and kurtosis than the IPAC group. However, the difference between the kurtosis (P=.003), the 5th (P=.032), 10th (P=.043), and 25th (P=.037) percentiles of ADC values was statistically significant. The area under the curve (AUC) of the kurtosis was the highest (AUC=0.752; cut-off value=-0.235; sensitivity=61.1%; specificity=80.0%). Volumetric ADC histogram analysis with b values of 1000mm²/s can discriminate subtypes noninvasively before surgery.

The efficiency of volumetric apparent diffusion coefficient histogram analysis in breast papillary neoplasms

Background/Aim: Papillary neoplasia encompasses both malignant and benign lesions, and core needle biopsy (CNB) is crucial in their diagnosis. Histological findings determine their management. Here we compare volumetric apparent diffusion coefficient (ADC) histogram analysis of carcinomas and benign pathologies identified by histopathology from excisional biopsies. Methods: This retrospective study included 524 patients who underwent breast magnetic resonance imaging (MRI) for a suspicious breast mass from January 2018 to October 2022. Patients with benign lesions, incompatible ultrasound-guided CNB results with papillary neoplasia, and those with MRI exams insufficient for diagnosis due to motion artifacts were excluded. After applying the exclusion criteria, the study included 48 patients (average aged 61.5 (14.8) years; range, 31 to 72 years). After excisional biopsies, 30 benign lesions and 18 carcinomas were identified. MRI was acquired at 1.5 T (Verio; Siemens Medical Solutions, Erlangen, Germany), and the b-values for diffusion-weighted imaging were calculated at 1000 s/mm2. Histogram parameters were computed. Receiver operating characteristic (ROC) curve analysis was performed to investigate diagnostic accuracy, evaluate histogram analysis performance, and determine threshold values. Results: The ADCmin, ADCmean, ADCmax, and all ADC value percentiles were significantly lower in the carcinoma group than in the benign group (P<0.001). The variance, skewness, and kurtosis were higher in the carcinoma group. ADCmax had the highest area under the curve (AUC: 0.985; cut-off 1.247 × 10-3 mm2/s; sensitivity 86%, and specificity 92%), followed by ADCmean (AUC: 0.950; cut-off 0.903 × 10-3 mm2/s; sensitivity 94%, and specificity 96%). Conclusion: Volumetric ADC histogram analysis of papillary neoplasia at higher b-values can be an imaging marker to detect carcinoma and quantitatively reveal the lesions’ diffusion characteristics.

Volumetric apparent diffusion coefficient (ADC) histogram analysis of the brain in paediatric patients with hypoxic ischaemic encephalopathy.

To evaluate the whole brain, hippocampus, thalamus, and lentiform nucleus by volumetric apparent diffusion coefficient (ADC) histogram analysis in paediatric patients with hypoxic-ischaemic encephalopathy (HIE). This retrospective study included 25 patients with HIE and 50 patients as the control group. Diffusion-weighted imaging was obtained at b-values of 1000 mm2/s. The histogram parameters of ADC values, including the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance were determined. The interclass correlation coefficient (ICC) was used to assess the inter-observer agreement. ADCmin, ADCmean, and ADCmax, as well as the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values for the HIE group were all lower than those of the control group (p < 0.001) in the volumetric histogram analysis of the hippocampus, thalamus, and lentiform nucleus. In the whole-brain histogram analysis, ADC min, and the 50th and 75th percentiles of ADC values did not differ significantly, while other parameters were lower in the HIE group. The ROC curve revealed that the ADC histogram parameters of the hippocampus provided the most accurate results for the diagnosis of HIE. The area under the curve (AUC) of the 95th percentile of ADC values was the highest (AUC = 0.915; cut-off 1.262 × 10-3 mm2/s; sensitivity 88% and specificity 84%). Volumetric ADC histogram analysis of the whole brain, hippocampus, thalamus, and lentiform nucleus with b-values of 1000 mm2/s can serve as an imaging marker for determining HIE.

An Overview of the Role of Multiparametric MRI in the Investigation of Testicular Tumors.

Simple SummaryAlthough conventional ultrasonography remains the primary imaging modality for the assessment of testicular tumors, multiparametric MRI of the scrotum, which combines morphologic and functional data, serves as a powerful adjunct. Based on the recommendations issued by the Scrotal and Penile Imaging Working Group of the European Society of Urogenital Radiology, scrotal MRI is strongly recommended after equivocal US findings. In cases of testicular masses, the main clinical indications are as follows: lesion characterization when sonographic findings are non-diagnostic, discrimination between germ-cell and non-germ-cell testicular tumors, local staging of testicular tumors in patients who are candidates for testis-sparing surgery, and preoperative histological characterization of testicular germ-cell tumors in selected cases. This article aims to provide an overview of the role of multiparametric MRI in the investigation of testicular tumors.Conventional ultrasonography represents the mainstay of testis imaging. In cases in which ultrasonography is inconclusive, scrotal MRI using a multiparametric protocol may be used as a useful problem-solving tool. MRI of the scrotum is primarily recommended for differentiating between benign and malignant testicular masses when sonographic findings are ambiguous. This technique is also accurate in the preoperative local staging of testicular tumors and, therefore, is recommended in patients scheduled for testis-sparing surgery. In addition, MRI may provide valuable information regarding the histological characterization of testicular germ-cell tumors, in selected cases. Scrotal MRI may also help in the differentiation between testicular germ-cell neoplasms and non-germ-cell neoplasms. Axial T1-weighted imaging, axial and coronal T2-weighted imaging, axial diffusion-weighted imaging, and coronal subtracted dynamic contrast-enhanced imaging are the minimum requirements for scrotal MRI. A variety of MRI techniques—including diffusion tensor imaging, magnetization transfer imaging, proton MR spectroscopy, volumetric apparent diffusion coefficient histogram analysis, and MRI-based radiomics—are being investigated for testicular mass characterization, providing valuable supplementary diagnostic information. In the present review, we aim to discuss clinical indications for scrotal MRI in cases of testicular tumors, along with MRI findings of common testicular malignancies.

Volumetric apparent diffusion coefficient histogram analysis of the testes in nonobstructive azoospermia: a noninvasive fingerprint of impaired spermatogenesis?

To explore the association between testicular volumetric apparent diffusion coefficient (ADC) histogram analysis metrics and histologic categories in nonobstructive azoospermia (NOA). The role of ADC histogram analysis in predicting the presence of spermatozoa, prior to testicular sperm extraction (TESE), was also investigated. Forty-one NOA men and 17 age-matched controls underwent scrotal MRI with diffusion-weighted imaging. Histogram analysis of ADC data of the whole testis was performed. Metrics including mean, standard deviation, median, mode, 25th percentile, 75th percentile, skewness, kurtosis, and entropy of volumetric ADC histograms were calculated. Nonparametric statistical tests were used to assess differences in ADC histogram parameters between NOA histologic categories (hypospermatogenesis, severe hypospermatogenesis, early maturation arrest, and Sertoli cell-only syndrome) and normal testes and, between NOA with positive and negative sperm retrieval. Normal testes had a lower mean, median, mode, 25th percentile (p < 0.001), and 75th percentile of ADC (p = 0.001), compared to NOA histologic phenotypes. NOA with hypospermatogenesis had a lower 25th percentile of ADC compared to NOA with severe hypospermatogenesis. Regression analysis revealed that the 25th percentile of ADC had a moderately negative correlation with NOA histologic phenotype. The median ADC proved the most significant metric (p = 0.007) to predict the presence of sperm. Testicular volumetric ADC histogram parameters may contribute in the identification of the subpopulation of NOA men with a specific type of spermatogenic arrest. • Volumetric ADC histogram analysis metrics may be used as noninvasive markers of impaired spermatogenesis in nonobstructive azoospermia. • The 25th percentile of ADC proved useful in discriminating between NOA testes with hypospermatogenesis and severe hypospermatogenesis. • The median ADC proved the most significant parameter to predict the presence of viable spermatozoa prior to TESE.

Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index.

Objectives To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman's correlation analysis. Results Of the 189 breast lesions included, there were significant differences in patient age (P < 0.001) and lesion size (P = 0.006) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P < 0.001). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P = 0.001) and estrogen receptor (ER)/progesterone receptor (PR) status (P = 0.020 and P = 0.041, respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group (Ki − 67 < 14%) and 70 tumours in the high-proliferation group (Ki − 67 ≥ 14) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status (P = 0.007 and P < 0.001, respectively), and there were weak correlations between ADC entropy (r = 0.383) and skewness (r = 0.209) and the Ki-67 index. Conclusion The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.

Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer.

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-based histogram analysis differentiates histological subtypes of periampullary adenocarcinoma.

BACKGROUNDFor periampullary adenocarcinoma, the histological subtype is a better prognostic predictor than the site of tumor origin. Intestinal-type periampullary adenocarcinoma (IPAC) is reported to have a better prognosis than the pan-creatobiliary-type periampullary adenocarcinoma (PPAC). However, the classification of histological subtypes is difficult to determine before surgery. Apparent diffusion coefficient (ADC) histogram analysis is a noninvasive, non-enhanced method with high reproducibility that could help differentiate the two subtypes.AIMTo investigate whether volumetric ADC histogram analysis is helpful for distinguishing IPAC from PPAC.METHODSBetween January 2015 and October 2018, 476 consecutive patients who were suspected of having a periampullary tumor and underwent magnetic resonance imaging (MRI) were reviewed in this retrospective study. Only patients who underwent MRI at 3.0 T with different diffusion-weighted images (b-values = 800 and 1000 s/mm2) and who were confirmed with a periampullary adenocarcinoma were further analyzed. Then, the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values and ADCmin, ADCmax, kurtosis, skewness, and entropy were obtained from the volumetric histogram analysis. Comparisons were made by an independent Student's t-test or Mann-Whitney U test. Multiple-class receiver operating characteristic curve analysis was performed to determine and compare the diagnostic value of each significant parameter.RESULTSIn total, 40 patients with histopathologically confirmed IPAC (n = 17) or PPAC (n = 23) were enrolled. The mean, 5th, 25th, 50th, 75th, 90th, and 95th percentiles and ADCmax derived from ADC1000 were significantly lower in the PPAC group than in the IPAC group (P < 0.05). However, values derived from ADC800 showed no significant difference between the two groups. The 75th percentile of ADC1000 values achieved the highest area under the curve (AUC) for differentiating IPAC from PPAC (AUC = 0.781; sensitivity, 91%; specificity, 59%; cut-off value, 1.50 × 10-3 mm2/s).CONCLUSIONVolumetric ADC histogram analysis at a b-value of 1000 s/mm2 might be helpful for differentiating the histological subtypes of periampullary adenocarcinoma before surgery.

Volumetric Apparent Diffusion Coefficient Histogram Analysis in Differentiating Intrahepatic Mass-Forming Cholangiocarcinoma From Hepatocellular Carcinoma.

Accurate differentiation between intrahepatic mass-forming cholangiocarcinoma (IMCC) and hepatocellular carcinoma (HCC) is needed because treatment and prognosis differ significantly. To explore whether volumetric apparent diffusion coefficient (ADC) histogram analysis can provide additional value to dynamic enhanced MRI in differentiating IMCC from HCC. Retrospective. In all, 131 patients with pathologically proven IMCC (n = 33) or HCC (n = 98). 3.0T MRI/conventional T1 -weighted imaging (T1 WI), T2 WI, and diffusion-weighted imaging (DWI) with b value of 800 sec/mm2 , dynamic enhanced MRI with gadobenate dimeglumine. Dynamic enhanced MR images were analyzed by two independent reviewers using a five-point scale to determine the diagnosis. Volumetric ADC assessments were performed independently by two radiologists to obtain different histogram parameters for each lesion. Quantitative histogram parameters were compared between the IMCC group and HCC group. Diagnostic performance of dynamic enhanced MRI, volumetric ADC histogram analysis, and the combination of both were analyzed. Intraclass correlation coefficient (ICC) analysis, independent Student's t-test, or Mann-Whitney U-test, receiver operator characteristic (ROC) curves analysis, and McNemar test. The sensitivity and specificity for dynamic enhanced MRI to differentiate IMCC from HCC were 82.1% and 82.6%, respectively. For all volumetric ADC histogram parameters, the 75th percentile ADC (ADC75% ) had the highest AUC (0.791) in differentiating IMCC from HCC, with sensitivity and specificity of 69.7% and 77.6%, respectively. When combining dynamic enhanced MRI with ADC75% , the sensitivity and specificity were 82.1% and 91.9%, respectively. Compared to dynamic enhanced MRI alone, the specificity for combined dynamic enhanced MRI and ADC75% was significantly increased (P = 0.008). Volumetric ADC histogram analysis provides additional value to dynamic enhanced MRI in differentiating IMCC from HCC. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:975-983.

Subtype Differentiation of Small (≤ 4 cm) Solid Renal Mass Using Volumetric Histogram Analysis of DWI at 3-T MRI.

The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI. This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis. ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p < 0.05). Mean ADC, median ADC, 75th and 90th percentile ADC, SD ADC, and entropy of malignant tumors were significantly higher than those of benign tumors (all p < 0.05). Combination of mean ADC with histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%). Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.

Investigation of volumetric apparent diffusion coefficient histogram analysis for assessing complete response and clinical outcomes following pre-operative chemoradiation treatment for rectal carcinoma.

To investigate the relationship of pre-treatment volumetric apparent diffusion coefficient (ADC) histogram parameters with post-operative histopathologic treatment response and clinical outcomes following pre-operative chemoradiation treatment (CRT) in rectal cancer. In a Health Insurance Portability and Accountability Act compliant retrospective study, 78 rectal cancer patients treated with pre-operative CRT and rectal MRI were included. MR imaging analysis was performed using OncoTREAT (software tool). Multiple volumetric ADC histogram parameters (voxel distribution across ADC ranges, kurtosis, and skewness) were assessed. Correlation was made to post-operative pathological complete response, clinical, or radiological evidence of disease progression using the Mann-Whitney test. Post CRT, 8 patients showed pathologic complete response and 13 patients showed distant disease progression. Pre-treatment mean ADC was 1.2 × 10-3 mm2/s (range 0.3-1.99 × 10-3 mm2/s). Mean kurtosis measured was 0.56 (range -1 to 6; SD 1.36). Mean skewness was 0.3 (range -1 to 2; SD 0.69). Skewness had significant correlation (p value = 0.006) with disease progression. The mean rectal tumor volume was 24cc (range 1cc-134cc). Pre-treatment MRI tumor volume showed significant correlation (p value = 0.013) with pathologic complete response. Mean ADC and percentage voxels distribution against ADC ranges had no significant correlation with treatment response or disease outcomes. Volumetric ADC histogram analysis of pre-CRT rectal cancer MRI appears promising for prediction of post-CRT complete response and disease progression.

Retrospective Assessment of Histogram-Based Diffusion Metrics for Differentiating Benign and Malignant Endometrial Lesions.

Our study aimed to retrospectively evaluate the utility of volumetric histogram-based diffusion metrics in differentiating benign from malignant endometrial abnormalities. A total of 54 patients underwent pelvic magnetic resonance imaging with diffusion-weighted imaging before endometrial tissue diagnosis. Two radiologists placed volumes of interest on the apparent diffusion coefficient (ADC) map encompassing the entire endometrium and focal endometrial lesions. The mean ADC, percentile ADC values, kurtosis, skewness, and entropy of ADC were compared between benign and malignant abnormalities. In premenopausal patients, significant independent predictors of malignancy were whole-endometrium analysis for R1, 10th to 25th ADC percentile (P = 0.012); whole-endometrium analysis for R2, mean ADC (P = 0.001) and skewness (P = 0.004); focal lesion analysis for R1, skewness (P = 0.045); focal lesion analysis for R2, 10th to 25th ADC percentile (P ≤ 0.0001). The area under the curve for malignancy was 90.0% to 97.3% and 76.1% to 77.3% for the more and less experienced radiologists, respectively. In postmenopausal patients, the only significant difference was kurtosis using whole-endometrium analysis for R1 (P = 0.042). Volumetric ADC histogram metrics may help radiologists assess the risk of malignancy in endometrial abnormalities on magnetic resonance imaging in premenopausal patients.