Rectal cancer is a common and serious disease in the Western hemisphere. Optimal treatment of rectal cancer involves a multidisciplinary approach, with collaboration required between radiologists, oncologists, surgeons, and pathologists to achieve local control and decrease the rate of recurrence. Several studies have been published that show the ability to accurately stage rectal cancer with magnetic resonance (MR) imaging. Moreover, advances in preoperative therapies require accurate preoperative staging with MR imaging to select those patients who may benefit from more intensive treatment, without subjecting those who will not benefit to unnecessary treatment. As we enter an era of individualized patient care, stratified according to the risk of both local and distant failure, imaging takes on the same importance as the tumor type and genetic susceptibility. MR imaging is now an essential tool to enable the oncology team to make appropriate treatment decisions. However, rectal cancer evaluation with MR imaging remains a challenge in the hands of nonexperts. This article describes a mnemonic device, "DISTANCE," to enable a systematic approach to the interpretation of MR images, thereby enabling all the clinically relevant features to be adequately assessed: DIS, for Distance from the Inferior part of the tumor to the transitional Skin; T, for T staging; A, for Anal complex; N, for Nodal staging; C, for Circumferential resection margin; and E, for Extramural vascular invasion.

• MRI is recommended for initial staging of endometrial cancer. • MR imaging protocol should be tailored based on the risk of lymph node metastases. • Myometrial invasion is best assessed using combined axial-oblique T2WI, DWI and contrast-enhanced imaging. • The mnemonic "Clinical and MRI Critical TEAM" summarizes key elements of the standardized report.

• For normal liver, tri-exponential IVIM model might be superior to bi-exponential • A very fast compartment (D = 404.00 ± 43.7 × 10 (-3) mm (2) /s; f = 13.5 ± 0.8 %) is determined from the tri-exponential model • The compartment contributes to the IVIM signal only for b ≤ 15 s/mm(2).

Purpose:To investigate magnetic resonance (MR) volumetry of endometrial tumors and its association with deep myometrial invasion, tumor grade, and lymphovascular invasion and to assess the value of apparent diffusion coefficient (ADC) histographic analysis of the whole tumor volume for prediction of tumor grade and lymphovascular invasion. Materials and Methods:The institutional review board approved this retrospective study; patient consent was not required. Between May 2010 and May 2012, 70 women (mean age, 64 years; range, 24-91 years) with endometrial cancer underwent preoperative MR imaging, including axial oblique and sagittal T2-weighted, dynamic contrast material-enhanced, and diffusion-weighted imaging. Volumetry of the tumor and uterus was performed during the six sequences, with manual tracing of each section, and the tumor volume ratio (TVR) was calculated. ADC histograms were generated from pixel ADCs from the whole tumor volume. The threshold of TVR associated with myometrial invasion was assessed by using receiver operating characteristic curves. An independent sample Mann Whitney U test was used to compare differences in ADCs, skewness, and kurtosis between tumor grade and the presence of lymphovascular invasion. Results:No significant difference in tumor volume and TVR was found among the six MR imaging sequences (P = .95 and .86, respectively). A TVR greater than or equal to 25% allowed prediction of deep myometrial invasion with sensitivity of 100% and specificity of 93% (area under the curve, 0.96; 95% confidence interval: 0.86, 0.99) at axial oblique diffusion-weighted imaging. A TVR of greater than or equal to 25% was associated with grade 3 tumors (P = .0007) and with lymphovascular invasion (P , .0001).There was no significant difference in the ADCs between grades 1 and 2 tumors (P . .05). The minimum, 10th, 25th, 50th, 75th, and 90th percentile ADCs were significantly lower in grade 3 tumors than in grades 1 and 2 tumors (P , .02). Conclusion:The combination of whole tumor volume and ADC can be used for prediction of tumor grade, lymphovascular invasion, and depth of myometrial invasion.q RSNA, 2015

Results:Extreme values aside, results of histogram analysis of ADC and IVIM were equivalent to median values for tumor response assessment (P . .06). Prior to CRT, none of the median ADC and IVIM diffusion metrics correlated with subsequent tumor response (P . .36). Median D and ADC values derived from either whole-volume or single-section analysis increased significantly after CRT (P  .01) and were significantly higher in good versus poor responders (P  .02). Median IVIM f and D* values did not significantly change after CRT and were not associated with tumor response to CRT (P . .36). Interobserver agreement was excellent for whole-tumor volume analysis (range, 0.91-0.95) but was only moderate for singlesection ROI analysis (range, 0.50-0.63). Conclusion:Median D and ADC values obtained after CRT were useful for discrimination between good and poor responders. Histogram metrics did not add to the median values for assessment of tumor response. Volumetric analysis demonstrated better interobserver reproducibility when compared with single-section ROI analysis.q RSNA, 2016

Background: Rectal cancer surgery is technically challenging and depends on many factors. This study evaluated the ability of clinical and anatomical factors to predict surgical difficulty in total mesorectal excision. Conclusion: This simple morphometric score may assist surgical decision-making and comparative study by defining operative difficulty before surgery.

Ovarian carcinoma is the most common cause of death due to gynecologic malignancy. Peritoneal involvement is present in approximately 70% of patients at the time of initial diagnosis. The disease spreads abdominally by direct extension, exfoliation of tumor cells into the peritoneal space, and dissemination of tumor cells along lymphatic pathways. Carcinomatosis characterizes an advanced stage of disease in which peritoneal disease has spread throughout the upper abdomen (stage IIIC) or in which diffuse peritoneal disease is accompanied by malignant pleural infiltration or visceral metastases (stage IV). Common sites of intraperitoneal seeding of ovarian carcinoma include the pelvis, omentum, paracolic gutters, liver capsule, and diaphragm. Soft-tissue thickening, nodularity, and enhancement are all signs of peritoneal involvement. Advanced-stage disease is treated either with initial cytoreductive surgery (debulking) followed by adjuvant chemotherapy, or with initial neoadjuvant chemotherapy followed by debulking. Radiologic imaging plays an important role in the selection of patients who may benefit from neoadjuvant chemotherapy before debulking. However, accurate interpretation of the imaging findings is challenging and requires a detailed knowledge of the complex peritoneal anatomy, directionality of flow of peritoneal fluid, and specific disease sites that are likely to present particular difficulties with regard to surgical access and technique. Although there is as yet no clear consensus on the criteria for resectability of peritoneal lesions, extensive involvement of the small bowel or mesenteric root, involved lymph nodes superior to the celiac axis, pleural infiltration, pelvic sidewall invasion, bladder trigone involvement, and hepatic parenchymal metastases or implants near the right hepatic vein are considered indicative of potential nonresectability. Implants larger than 2 cm in diameter in the diaphragm, lesser sac, porta hepatis, intersegmental fissure, gallbladder fossa, or gastrosplenic or gastrohepatic ligament also may represent nonresectable disease.

Purpose To investigate whether qualitative magnetic resonance (MR) features can distinguish leiomyosarcoma (LMS) from atypical leiomyoma (ALM) and assess the feasibility of texture analysis (TA). Methods This retrospective study included 41 women (ALM=22, LMS=19) imaged with MRI prior to surgery. Two readers (R1, R2) evaluated each lesion for qualitative MR features. Associations between MR features and LMS were evaluated with Fisher's exact test. Accuracy measures were calculated for the four most significant features. TA was performed for 24 patients (ALM=14, LMS=10) with uniform imaging following lesion segmentation on axial T2-weighted images. Texture features were pre-selected using Wilcoxon signed-rank test with Bonferroni correction and analyzed with unsupervised clustering to separate LMS from ALM. Results Four qualitative MR features most strongly associated with LMS were nodular borders, haemorrhage, “T2 dark” area(s), and central unenhanced area(s) (p≤0.0001 each feature/reader). The highest sensitivity [1.00 (95%CI:0.82-1.00)/0.95 (95%CI: 0.74-1.00)] and specificity [0.95 (95%CI:0.77-1.00)/1.00 (95%CI:0.85-1.00)] were achieved for R1/R2, respectively, when a lesion had ≥3 of these four features. Sixteen texture features differed significantly between LMS and ALM (p-values: <0.001-0.036). Unsupervised clustering achieved accuracy of 0.75 (sensitivity: 0.70; specificity: 0.79). Conclusions Combination of ≥3 qualitative MR features accurately distinguished LMS from ALM. TA was feasible.