Quantitative MR texture analysis for the differentiation of uterine smooth muscle tumors with high signal intensity on T2-weighted imaging.

The purpose of this study was to distinguish leiomyosarcomas/smooth muscle tumors of uncertain malignant potential (STUMP) from leiomyomas with high signal intensity (SI) on T2-weighted imaging (T2WI) using quantitative MR texture analysis combined with patient characteristics and visual assessment. Thirty-one leiomyomas, 2 STUMPs, and 6 leiomyosarcomas showing high SI on T2WI were included. First, we searched for differences in patient characteristics and visual assessment between leiomyomas and leiomyosarcomas/STUMPs. We also compared the MR texture on T2WI and the apparent diffusion coefficient (ADC) to identify differences between leiomyomas and leiomyosarcomas/STUMPs. In the univariate analysis, significant differences between leiomyomas and leiomyosarcomas/STUMPs were observed in age, menopausal status, margin, hemorrhage, long diameter, T2-variance, T2-volume, ADC-variance, ADC-entropy, ADC-uniformity, ADC-90th and 95th percentile values, and ADC-volume (P < .05, respectively). There were significantly more postmenopausal patients with leiomyosarcomas/STUMPs than with leiomyomas, and leiomyosarcomas/STUMPs had more irregular margins, more frequent presence of hemorrhage and exhibited larger tumor diameters, T2-volume, T2-variance, ADC-volume, ADC-variance, ADC-entropy, and higher ADC-90th and 95th percentile values but lower ADC-uniformity. Multivariate analyses revealed that the independent differentiators were menopausal status, hemorrhage and ADC-entropy (P < .05, respectively). The area under the curve obtained by combining the 3 items was 0.980. The best cutoff value for ADC-entropy was 9.625 (sensitivity: 100%, specificity: 58%). The combination of menopausal status, hemorrhage, and ADC-entropy can help accurately distinguish leiomyosarcomas/STUMPs from leiomyomas with high SI on T2WI; however, external validation in a larger population is required because of the small sample size of our study.

A combination of preoperative CT findings and postoperative serum CEA levels improves recurrence prediction for stage I lung adenocarcinoma.

OBJECTIVES: To assess the prognostic value of combined evaluation of preoperative CT findings and pre/postoperative serum carcinoembryonic antigen (CEA) levels for pathological stage I lung adenocarcinoma. METHODS: This retrospective study included 250 consecutive patients who underwent complete resection for ≤ 3-cm pathological stage I (T1-2aN0M0) adenocarcinomas (132 men, 118 women; mean age, 67.8 years). Radiologists evaluated following CT findings: maximum tumor diameter, percentage of solid component (%solid), air bronchogram, spiculation, adjacency of bullae or interstitial pneumonia (IP) around the tumor, notch, and pleural indent. These CT findings, pre/postoperative CEA levels, age, gender, and Brinkman index were assessed by Cox proportional hazards model to determine the best prognostic model. Prognostic accuracy was examined using the area under the receiver operating characteristic curve (AUC). RESULTS: Median follow-up period was 73.2 months. In multivariate analysis, high %solid, adjacency of bullae or IP around the tumor, and high postoperative CEA levels comprised the best combination for predicting recurrence (P<0.05). A combination of these three findings had a greater accuracy in predicting 5-year disease-free survival than did %solid alone (AUC=0.853 versus 0.792; P=0.023), with a sensitivity of 85.7% and a specificity of 74.3% at the optimal threshold. The best cut-off values of %solid and postoperative CEA levels for predicting high-risk patients were ≥ 48% and ≥ 3.7 ng/mL, respectively. CONCLUSION: Compared to %solid alone, combined evaluation of %solid, adjacency of bullae or IP change around the tumor, and postoperative CEA levels improves recurrence prediction for stage I lung adenocarcinoma.

Differential diagnosis of uterine smooth muscle tumors using diffusion-weighted imaging: correlations with the apparent diffusion coefficient and cell density.

The purpose of this study is to investigate the utility of the apparent diffusion coefficient (ADC) in differentiating benign and malignant uterine smooth muscle tumors classified by signal intensity (SI) on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI), and to determine the correlation between ADC and tumor cell density. This retrospective study reviewed 168 lesions in 134 cases with pathologically confirmed uterine smooth muscle tumors, including 6 leiomyosarcomas and 3 smooth muscle tumors of uncertain malignant potential, and preoperative magnetic resonance imaging examinations performed between October 2009 and November 2012. T2WI and DWI were also performed for each subject. Tumors were then classified according to SI on T2WI and DWI relative to myometrial SI. The correlation between ADC and tumor cell density was also determined. In Group 1 (high on both T2WI/DWI), mean ADC was significantly lower for leiomyosarcoma (0.91 × 10(-3) mm(2)/s) than for leiomyoma (1.30 × 10(-3) mm(2)/s; p < 0.05) and mean cell density significantly higher for leiomyosarcoma (42.9%) than for leiomyoma (22.4%; p < 0.05). A strong negative correlation was seen between ADC and tumor cell density in Group 1 (Spearman, R = -0.72; p < 0.05). ADC may help to differentiate benign from malignant uterine smooth muscle tumors, particularly tumors with high SI on T2WI and DWI.