The accuracy of Multi-detector row CT for the assessment of tumor invasion of the mesorectal fascia in primary rectal cancer

PURPOSE: To evaluate the accuracy of Multi-detector row CT (MDCT) for the prediction of tumor invasion of the mesorectal fascia (MRF). MATERIALS AND METHODS: A total of 35 patients with primary rectal cancer underwent preoperative staging magnetic resonance imaging (MRI) and MDCT. The tumor relationship to the MRF, expressed in 3 categories (1--tumor free MRF = tumor distance > or = 1 mm; 2--threatened = distance < 1 mm; 3--invasion = distance 0 mm) was determined on CT by two observers at patient level and at different anatomical locations. A third expert reader evaluated the MRF tumor relationship on MRI, which served as reference standard. Receiver operating characteristic curves (ROC-curves) and areas under these curves (AUC) were calculated. The inter-observer agreement of CT was determined by using linear weighted kappa statistics. RESULTS: The AUC of CT for MRF invasion was 0.71 for observer 1 and 0.62 for observer 2. The inter-observer agreement was kappa = 0.34. The performance of CT at mid-high rectal levels was statistically significant better compared to low anterior (obs.1: AUC = 0.88 vs. 0.50; obs 2: AUC = 0.84 vs. 0.31; P < or = 0.040). CONCLUSION: Multi-detector row CT has a poor accuracy for predicting MRF invasion in low-anterior located tumors.The accuracy of CT significantly improves for tumors in the mid-high rectum. There is a high inconsistency among readers

T-staging of rectal cancer: accuracy of 3.0 Tesla MRI compared with 1.5 Tesla

OBJECTIVES: Magnetic resonance imaging (MRI) is not accurate in discriminating T1-2 from borderline T3 rectal tumors. Higher resolution on 3 Tesla-(3T)-MRI could improve diagnostic performance for T-staging. The aim of this study was to determine whether 3T-MRI compared with 1.5 Tesla-(1.5T)-MRI improves the accuracy for the discrimination between T1-2 and borderline T3 rectal tumors and to evaluate reproducibility. METHODS: 13 patients with non-locally advanced rectal cancer underwent imaging with both 1.5T and 3T-MRI. Three readers with different expertise evaluated the images and predicted T-stage with a confidence level score. Receiver operator characteristics curves with areas under the curve (AUC) and diagnostic parameters were calculated. Inter- and intra-observer agreements were calculated with quadratic kappa-weighting. Histology was the reference standard. RESULTS: Seven patients had pT1-2 tumors and six had pT3 tumors. AUCs ranged from 0.66 to 0.87 at 1.5T vs. 0.52-0.82 at 3T. Mean overstaging rate was 43% at 1.5T and 57% at 3T (P = 0.23). Inter-observer agreement was kappa 0.50-0.71 at 1.5T vs. 0.15-0.68 at 3T. Intra-observer agreement was kappa 0.71 at 1.5T and 0.76 at 3T. CONCLUSIONS: This is the first study to compare 3T with 1.5T MRI for T-staging of rectal cancer within the same patients. Our results showed no difference between 3T and 1.5T-MRI for the distinction between T1-2 and borderline T3 tumors, regardless of expertise. The higher resolution at 3T-MRI did not aid in the distinction between desmoplasia in T1-2-tumors and tumor stranding in T3-tumors. Larger studies are needed to acknowledge these findings

Translabial Three-Dimensional Ultrasonography Compared With Magnetic Resonance Imaging in Detecting Levator Ani Defects

To assess the diagnostic performance of translabial three-dimensional ultrasonography in detecting major levator ani defects in women with pelvic organ prolapse compared with magnetic resonance imaging (MRI) and to assess the interobserver agreement in detecting levator ani defects with translabial three-dimensional ultrasonography. In a multicenter cohort study, 140 women indicated for primary surgery of pelvic organ prolapse quantification stage II or more cystocele were included. Patients undergoing mesh surgery or concomitant stress incontinence surgery were excluded. All consenting patients underwent translabial three-dimensional ultrasonography and MRI of the pelvic floor before surgery. Two observers (out of a pool of four observers) assessed translabial three-dimensional ultrasound images; two other observers (out a pool of five observers) assessed MRIs for levator ani muscle damage. In case of disagreement, the images were discussed in a consensus meeting. Of the 135 scans, 45 major levator ani defects were detected on ultrasonogram (33.3%) and 32 were confirmed at MRI (23.7%). Of the 41 major levator ani defects detected on MRI, nine were missed at translabial three-dimensional ultrasonogram. Sensitivity was 0.78 (32 of 41) (95% confidence interval [CI] 0.65-0.91) and specificity was 0.86 (81 of 94) (95% CI 0.79-0.93) in detecting major levator ani defects with translabial three-dimensional ultrasonography compared with MRI. There was good agreement scoring levator ani defects on translabial three-dimensional ultrasonography, with a κ of 0.67 (95% CI 0.58-0.76); agreement in recognizing major levator ani defects was moderate, with a κ of 0.53 (95% CI 0.37-0.69). Translabial three-dimensional ultrasonography shows reasonable agreement with MRI in detecting major levator defects. Because of the moderate interobserver agreement, it will be difficult to implement ultrasonography in daily practice. Netherlands Trial Register, www.trialregister.nl, NTR222

Interobserver Reproducibility of Diffusion-Weighted MRI in Monitoring Tumor Response to Neoadjuvant Therapy in Esophageal Cancer

OBJECTIVE: To investigate the reproducibility of diffusion-weighted magnetic resonance imaging (DW-MRI) in assessing tumor response early in the course of neoadjuvant chemoradiotherapy in patients with operable esophageal cancer. METHODS: Eleven male patients (mean age 54.8 years) with newly diagnosed esophageal cancer underwent DW-MRI before and 10 days after start of chemoradiotherapy. Reproducibility of apparent diffusion coefficient (ADC) measurements by manual (freehand) and semi-automated volumetric methods was assessed. RESULTS: Interobserver reproducibility for the assessment of mean tumor ADC by the manual measurement method was good, with an ICC of 0.69 (95% CI, 0.36 to 0.85; P = 0.001). Interobserver reproducibility for the assessment of mean tumor ADC by the semi-automated volumetric measurement method was very good, with an ICC of 0.96 (95% CI, 0.91 to 0.98; P<0.001). CONCLUSION: Semi-automated volumetric ADC measurements have higher reproducibility than manual ADC measurements in assessing tumor response to chemoradiotherapy in patients with esophageal adenocarcinoma

Radiomics performs comparable to morphologic assessment by expert radiologists for prediction of response to neoadjuvant chemoradiotherapy on baseline staging MRI in rectal cancer

Purpose To compare the performance of advanced radiomics analysis to morphological assessment by expert radiologists to predict a good or complete response to chemoradiotherapy in rectal cancer using baseline staging MRI. Materials and methods We retrospectively assessed the primary staging MRIs [prior to chemoradiotherapy (CRT)] of 133 rectal cancer patients from 2 centers. First, two expert radiologists subjectively estimated the likelihood of achieving a "complete response" (ypT0) and "good response" (TRG 1-2), using a 5-point score (based on TN-stage, MRF/EMVI-status, size/signal/shape). Next, tumor volumes were segmented on high b value DWI (semi-automated, corrected by 2 non-expert and 2-expert readers, resulting in 5 segmentations), copied to the remaining sequences after which a total of 2505 radiomic features were extracted from T2W, low and high b value DWI and ADC. Stability of features for noise due to inter-reader and inter-scanner and protocol variations was assessed using intraclass correlation (ICC) and the Kruskal-Wallis test. Using data from center 1 (n = 86; training set), top 9 features were selected using minimum Redundancy Maximum Relevance and combined in a logistic regression model. Finally, diagnostic performance of the fitted models was assessed on data from center 2 (n = 47; validation set) and compared to the performance of the radiologists. Results The Radiomic models resulted in AUCs of 0.69-0.79 (with similar results for the segmentations performed by expert/non-expert readers) to predict response, results similar to the morphologic prediction by the expert radiologists (AUC 0.67-0.83). Radiomics using semi-automatically generated segmentations (without manual input) did not result in significant predictive performance. Conclusions Radiomics could predict response to therapy with comparable diagnostic performance as expert radiologists, regardless of whether image segmentation was performed by non-expert or expert readers, indicating that expert input is not required in order for the radiomics workflow to produce significant predictive performance.</p