Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer.

OBJECTIVES: To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset. METHODS: Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (ADC)) of 509 patients (9 centres) treated with neoadjuvant chemoradiotherapy (CRT) were collected. Response was defined as (1) complete versus incomplete response, or (2) good (Mandard tumor regression grade (TRG) 1-2) versus poor response (TRG3-5). Prediction models were developed using combinations of the following variable groups: (1) Non-imaging: age/sex/tumor-location/tumor-morphology/CRT-surgery interval (2) Basic staging: cT-stage/cN-stage/mesorectal fascia involvement, derived from (2a) original staging reports, or (2b) expert re-evaluation (3) Advanced staging: variables from 2b combined with cTN-substaging/invasion depth/extramural vascular invasion/tumor length (4) Quantitative imaging: tumour volume + first-order histogram features (from T2W-MRI and DWI/ADC) Models were developed with data from 6 centers (n = 412) using logistic regression with the Least Absolute Shrinkage and Selector Operator (LASSO) feature selection, internally validated using repeated (n = 100) random hold-out validation, and externally validated using data from 3 centers (n = 97). RESULTS: After external validation, the best model (including non-imaging and advanced staging variables) achieved an area under the curve of 0.60 (95%CI=0.48-0.72) to predict complete response and 0.65 (95%CI=0.53-0.76) to predict a good response. Quantitative variables did not improve model performance. Basic staging variables consistently achieved lower performance compared to advanced staging variables. CONCLUSIONS: Overall model performance was moderate. Best results were obtained using advanced staging variables, highlighting the importance of good-quality staging according to current guidelines. Quantitative imaging features had no added value (in this heterogeneous dataset). CLINICAL RELEVANCE STATEMENT: Predicting tumour response at baseline could aid in tailoring neoadjuvant therapies for rectal cancer. This study shows that image-based prediction models are promising, though are negatively affected by variations in staging quality and MRI acquisition, urging the need for harmonization. KEY POINTS: This multicenter study combining clinical information and features derived from MRI rendered disappointing performance to predict response to neoadjuvant treatment in rectal cancer. Best results were obtained with the combination of clinical baseline information and state-of-the-art image-based staging variables, highlighting the importance of good quality staging according to current guidelines and staging templates. No added value was found for quantitative imaging features in this multicenter retrospective study. This is likely related to acquisition variations, which is a major problem for feature reproducibility and thus model generalizability.

Associations between plasma sulfur amino acids and specific fat depots in two independent cohorts: CODAM and The Maastricht Study.

PURPOSE: Sulfur amino acids (SAAs) have been associated with obesity and obesity-related metabolic diseases. We investigated whether plasma SAAs (methionine, total cysteine (tCys), total homocysteine, cystathionine and total glutathione) are related to specific fat depots. METHODS: We examined cross-sectional subsets from the CODAM cohort (n = 470, 61.3% men, median [IQR]: 67 [61, 71] years) and The Maastricht Study (DMS; n = 371, 53.4% men, 63 [55, 68] years), enriched with (pre)diabetic individuals. SAAs were measured in fasting EDTA plasma with LC-MS/MS. Outcomes comprised BMI, skinfolds, waist circumference (WC), dual-energy X-ray absorptiometry (DXA, DMS), body composition, abdominal subcutaneous and visceral adipose tissues (CODAM: ultrasound, DMS: MRI) and liver fat (estimated, in CODAM, or MRI-derived, in DMS, liver fat percentage and fatty liver disease). Associations were examined with linear or logistic regressions adjusted for relevant confounders with z-standardized primary exposures and outcomes. RESULTS: Methionine was associated with all measures of liver fat, e.g., fatty liver disease [CODAM: OR = 1.49 (95% CI 1.19, 1.88); DMS: OR = 1.51 (1.09, 2.14)], but not with other fat depots. tCys was associated with overall obesity, e.g., BMI [CODAM: ß = 0.19 (0.09, 0.28); DMS: ß = 0.24 (0.14, 0.34)]; peripheral adiposity, e.g., biceps and triceps skinfolds [CODAM: ß = 0.15 (0.08, 0.23); DMS: ß = 0.20 (0.12, 0.29)]; and central adiposity, e.g., WC [CODAM: ß = 0.16 (0.08, 0.25); DMS: ß = 0.17 (0.08, 0.27)]. Associations of tCys with VAT and liver fat were inconsistent. Other SAAs were not associated with body fat. CONCLUSION: Plasma concentrations of methionine and tCys showed distinct associations with different fat depots, with similar strengths in the two cohorts.

Pelvic CT in addition to MRI to differentiate between rectal and sigmoid cancer on imaging using the sigmoid take-off as a landmark.

BACKGROUND: The sigmoid take-off (STO) is a recently established landmark to discern rectal from sigmoid cancer on imaging. STO-assessment can be challenging on magnetic resonance imaging (MRI) due to varying axial planes. PURPOSE: To establish the benefit of using computed tomography (CT; with consistent axial planes), in addition to MRI, to anatomically classify rectal versus sigmoid cancer using the STO. MATERIAL AND METHODS: A senior and junior radiologist retrospectively classified 40 patients with rectal/rectosigmoid cancers using the STO, first on MRI-only (sagittal and oblique-axial views) and then using a combination of MRI and axial CT. Tumors were classified as rectal/rectosigmoid/sigmoid (according to published STO definitions) and then dichotomized into rectal versus sigmoid. Diagnostic confidence was documented using a 5-point scale. RESULTS: Adding CT resulted in a change in anatomical tumor classification in 4/40 cases (10%) for the junior reader and in 6/40 cases (15%) for the senior reader. Diagnostic confidence increased significantly after adding CT for the junior reader (mean score 3.85 vs. 4.27; P < 0.001); confidence of the senior reader was not affected (4.28 vs. 4.25; P = 0.80). Inter-observer agreement was similarly good for MRI only (κ=0.77) and MRI + CT (κ=0.76). Readers reached consensus on the classification of rectal versus sigmoid cancer in 78%-85% of cases. CONCLUSION: Availability of a consistent axial imaging plane - in the case of this study provided by CT - in addition to a standard MRI protocol with sagittal and oblique-axial imaging views can be helpful to more confidently localize tumors using the STO as a landmark, especially for more junior readers.

Sources of variation in multicenter rectal MRI data and their effect on radiomics feature reproducibility.

OBJECTIVES: To investigate sources of variation in a multicenter rectal cancer MRI dataset focusing on hardware and image acquisition, segmentation methodology, and radiomics feature extraction software. METHODS: T2W and DWI/ADC MRIs from 649 rectal cancer patients were retrospectively acquired in 9 centers. Fifty-two imaging features (14 first-order/6 shape/32 higher-order) were extracted from each scan using whole-volume (expert/non-expert) and single-slice segmentations using two different software packages (PyRadiomics/CapTk). Influence of hardware, acquisition, and patient-intrinsic factors (age/gender/cTN-stage) on ADC was assessed using linear regression. Feature reproducibility was assessed between segmentation methods and software packages using the intraclass correlation coefficient. RESULTS: Image features differed significantly (p < 0.001) between centers with more substantial variations in ADC compared to T2W-MRI. In total, 64.3% of the variation in mean ADC was explained by differences in hardware and acquisition, compared to 0.4% by patient-intrinsic factors. Feature reproducibility between expert and non-expert segmentations was good to excellent (median ICC 0.89-0.90). Reproducibility for single-slice versus whole-volume segmentations was substantially poorer (median ICC 0.40-0.58). Between software packages, reproducibility was good to excellent (median ICC 0.99) for most features (first-order/shape/GLCM/GLRLM) but poor for higher-order (GLSZM/NGTDM) features (median ICC 0.00-0.41). CONCLUSIONS: Significant variations are present in multicenter MRI data, particularly related to differences in hardware and acquisition, which will likely negatively influence subsequent analysis if not corrected for. Segmentation variations had a minor impact when using whole volume segmentations. Between software packages, higher-order features were less reproducible and caution is warranted when implementing these in prediction models. KEY POINTS: • Features derived from T2W-MRI and in particular ADC differ significantly between centers when performing multicenter data analysis. • Variations in ADC are mainly (> 60%) caused by hardware and image acquisition differences and less so (< 1%) by patient- or tumor-intrinsic variations. • Features derived using different image segmentations (expert/non-expert) were reproducible, provided that whole-volume segmentations were used. When using different feature extraction software packages with similar settings, higher-order features were less reproducible.

Studying local tumour heterogeneity on MRI and FDG-PET/CT to predict response to neoadjuvant chemoradiotherapy in rectal cancer.

OBJECTIVE: To investigate whether quantifying local tumour heterogeneity has added benefit compared to global tumour features to predict response to chemoradiotherapy using pre-treatment multiparametric PET and MRI data. METHODS: Sixty-one locally advanced rectal cancer patients treated with chemoradiotherapy and staged at baseline with MRI and FDG-PET/CT were retrospectively analyzed. Whole-tumour volumes were segmented on the MRI and PET/CT scans from which global tumour features (T2Wvolume/T2Wentropy/ADCmean/SUVmean/TLG/CTmean-HU) and local texture features (histogram features derived from local entropy/mean/standard deviation maps) were calculated. These respective feature sets were combined with clinical baseline parameters (e.g. age/gender/TN-stage) to build multivariable prediction models to predict a good (Mandard TRG1-2) versus poor (Mandard TRG3-5) response to chemoradiotherapy. Leave-one-out cross-validation (LOOCV) with bootstrapping was performed to estimate performance in an 'independent' dataset. RESULTS: When using only imaging features, local texture features showed an AUC = 0.81 versus AUC = 0.74 for global tumour features. After internal cross-validation (LOOCV), AUC to predict a good response was the highest for the combination of clinical baseline variables + global tumour features (AUC = 0.83), compared to AUC = 0.79 for baseline + local texture and AUC = 0.76 for all combined (baseline + global + local texture). CONCLUSION: In imaging-based prediction models, local texture analysis has potential added value compared to global tumour features to predict response. However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture analysis appears to be limited. The overall performance to predict response when combining baseline variables with quantitative imaging parameters is promising and warrants further research. KEY POINTS: • Quantification of local tumour texture on pre-therapy FDG-PET/CT and MRI has potential added value compared to global tumour features to predict response to chemoradiotherapy in rectal cancer. • However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture over global tumour features is limited. • Predictive performance of our optimal model-combining clinical baseline variables with global quantitative tumour features-was encouraging (AUC 0.83), warranting further research in this direction on a larger scale.

Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

OBJECTIVES: To explore the value of multiparametric MRI combined with FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation. METHODS: Sixty-one locally advanced rectal cancer patients who underwent a baseline FDG-PET/CT and MRI (T2W + DWI) and received long-course neoadjuvant chemoradiotherapy were retrospectively analysed. Tumours were delineated on MRI and PET/CT from which the following quantitative parameters were calculated: T2W volume and entropy, ADC mean and entropy, CT density (mean-HU), SUV maximum and mean, metabolic tumour volume (MTV42%) and total lesion glycolysis (TLG). These features, together with sex, age, mrTN-stage ("baseline parameters") and the CRT-surgery interval were analysed using multivariable stepwise logistic regression. Outcome was a good (TRG 1-2) versus poor histopathological response. Performance (AUC) to predict response was compared for different combinations of baseline ± quantitative imaging parameters and performance in an 'independent' dataset was estimated using bootstrapped leave-one-out cross-validation (LOOCV). RESULTS: The optimal multivariable prediction model consisted of a combination of baseline + quantitative imaging parameters and included mrT-stage (OR 0.004, p < 0.001), T2W-signal entropy (OR 7.81, p = 0.0079) and T2W volume (OR 1.028, p = 0.0389) as the selected predictors. AUC in the study dataset was 0.88 and 0.83 after LOOCV. No PET/CT features were selected as predictors. CONCLUSIONS: A multivariable model incorporating mrT-stage and quantitative parameters from baseline MRI can aid in identifying well-responding patients before the start of treatment. Addition of FDG-PET/CT is not beneficial. KEY POINTS: • A multivariable model incorporating the mrT-stage and quantitative features derived from baseline MRI can aid in identifying well-responding patients before the start of neoadjuvant chemoradiotherapy. • mrT-stage was the strongest predictor in the model and was complemented by the tumour volume and signal entropy calculated from T2W-MRI. • Adding quantitative features derived from pre-treatment PET/CT or DWI did not contribute to the model's predictive performance.

Long-term imaging characteristics of clinical complete responders during watch-and-wait for rectal cancer-an evaluation of over 1500 MRIs.

OBJECTIVES: Rectal cancer patients with a clinical complete response after chemoradiotherapy (CRT) may be followed with a 'watch-and-wait' (W&W) approach as an alternative to surgery. MRI plays an important role in the follow-up of these patients, but basic knowledge on what to expect from the morphology of the irradiated tumour bed during follow-up is lacking, which can hamper image interpretation. The objective was to establish the spectrum of non-suspicious findings during long-term (> 2 years) follow-up in patients with a sustained clinical complete response undergoing W&W. METHODS: A total of 1509 T2W MRIs of 164 sustained complete responders undergoing W&W were retrospectively evaluated. Morphology of the tumour bed was evaluated (2 independent readers) on the restaging MRI and on the various follow-up MRIs and classified as (a) no fibrosis, (b) minimal fibrosis, (c) full thickness fibrosis, or (d) irregular fibrosis. Any changes occurring during follow-up were documented. RESULTS: A total of 104 patients (63%) showed minimal fibrosis, 38 (23%) full thickness fibrosis, 8 (5%) irregular fibrosis, and 14 (9%) no fibrosis. In 93% of patients, the morphology remained completely stable during follow-up; in 7%, a minor increase/decrease in fibrosis was observed. Interobserver agreement was excellent (κ 0.90). CONCLUSIONS: Typically, the morphology as established at restaging remains completely unchanged. The majority of patients show fibrosis with the predominant pattern being a minimal fibrosis confined to the rectal wall. Complete absence of fibrosis occurs in only 1/10 cases. Once validated in independent cohorts, these findings may serve as a reference for radiologists involved in the clinical follow-up of W&W patients. KEY POINTS: • In rectal cancer patients with a sustained complete response after chemoradiation, the rectal wall morphology as established on restaging MRI typically remains unchanged during long-term MRI follow-up. • The vast majority of complete responders show fibrosis with the predominant pattern being a minimal fibrotic remnant that remains confined to the rectal wall; complete absence of fibrosis occurs in only 10% of the cases. • Once validated in independent cohorts, the findings of this study may serve as a reference for radiologists involved in the clinical follow-up of rectal cancer patients undergoing watch-and-wait.

The reproducibility of skeletal muscle signal intensity on routine magnetic resonance imaging in Crohn's disease.

BACKGROUND AND AIM: Myosteatosis is a prognostic factor in cancer and liver cirrhosis. It can be determined noninvasively using computed tomography or, as shown recently, by magnetic resonance (MR) imaging. The primary aim was to analyze the reproducibility of skeletal muscle signal intensity on routine MR-enterographies, as indicator of myosteatosis, in Crohn's disease (CD) and to explore the association between skeletal muscle signal intensity at diagnosis with time to intestinal resection. METHODS: CD patients undergoing MR-enterography within 6 months from diagnosis and having a maximum of 5 years follow-up were included. Skeletal muscle signal intensity was analyzed on T1-weighted fat-saturated post-contrast images. Intra-observer and inter-observer reproducibilities were assessed by intra-class correlation coefficient and Cohen's kappa. Intra-observer and inter-observer variabilities were determined by Pearson correlation coefficient and displayed by Bland-Altman plots. Time to intestinal resection was studied by Kaplan-Meier analysis. RESULTS: Median time between diagnosis and MR-enterography was 5 weeks (inter-quartile range 1-9) in 35 CD patients. Skeletal muscle signal intensity showed good intra-class correlation and substantial agreement (for intra-observer, intraclass correlation coefficient = 0.948, κ = 0.677; and inter-observer reproducibility, intraclass correlation coefficient = 0.858, κ = 0.622). Resection free survival was shorter in the low skeletal muscle signal intensity group (P = 0.037). CONCLUSION: Skeletal muscle signal intensity on routine MR-enterographies is reproducible and was associated with unfavorable disease outcome, indicating potential clinical relevance.

Natural Language Processing in Dutch Free Text Radiology Reports: Challenges in a Small Language Area Staging Pulmonary Oncology.

Reports are the standard way of communication between the radiologist and the referring clinician. Efforts are made to improve this communication by, for instance, introducing standardization and structured reporting. Natural Language Processing (NLP) is another promising tool which can improve and enhance the radiological report by processing free text. NLP as such adds structure to the report and exposes the information, which in turn can be used for further analysis. This paper describes pre-processing and processing steps and highlights important challenges to overcome in order to successfully implement a free text mining algorithm using NLP tools and machine learning in a small language area, like Dutch. A rule-based algorithm was constructed to classify T-stage of pulmonary oncology from the original free text radiological report, based on the items tumor size, presence and involvement according to the 8th TNM classification system. PyContextNLP, spaCy and regular expressions were used as tools to extract the correct information and process the free text. Overall accuracy of the algorithm for evaluating T-stage was 0,83 in the training set and 0,87 in the validation set, which shows that the approach in this pilot study is promising. Future research with larger datasets and external validation is needed to be able to introduce more machine learning approaches and perhaps to reduce required input efforts of domain-specific knowledge. However, a hybrid NLP approach will probably achieve the best results.

A Pattern-Based Approach Combining Tumor Morphology on MRI With Distinct Signal Patterns on Diffusion-Weighted Imaging to Assess Response of Rectal Tumors After Chemoradiotherapy.

BACKGROUND: Diffusion-weighted imaging is increasingly used in rectal cancer MRI to assess response after chemoradiotherapy. Certain pitfalls (eg, artefacts) may hamper diffusion-MRI assessment, leading to suboptimal diagnostic performance. Combining diffusion-weighted MRI with the underlying morphology on standard (T2-weighted) MRI may help overcome these pitfalls. OBJECTIVE: The purpose of this study was to evaluate the diagnostic performance of a pattern-based approach combining tumor morphology on T2-weighted MRI with distinct diffusion-weighted imaging signal patterns to assess response after chemoradiotherapy in rectal cancer. DESIGN: Response to chemoradiotherapy was scored according to 4 patterns: 1) cases with either a clear residual mass with corresponding high-diffusion signal (A+) or completely normalized wall without diffusion signal (A-); 2) cases with circular and/or irregular fibrosis with (B+) or without (B-) small foci of diffusion signal scattered throughout the fibrosis; 3) cases with semicircular fibrosis with (C+) or without (C-) high diffusion signal at the inner margin of the fibrosis; and 4) polypoid tumors showing regression of the polyp and fibrosis at the site of the stalk with (D+) or without (D-) focal high-diffusion signal in the stalk. A total of 75 cases were rescored by an independent second reader to study interobserver variations. Standard of reference was histopathology or long-term outcome. SETTINGS: The study was conducted at a single tertiary referral center. PATIENTS: A total of 222 patients with locally advanced rectal cancer undergoing chemoradiotherapy were included. MAIN OUTCOME MEASURES: Diagnostic performance to discriminate between a complete response and residual tumor was measured. RESULTS: The pattern-based approach resulted in a sensitivity of 94%, specificity of 77%, positive predictive value of 88%, negative predictive value of 87%, and overall accuracy of 88% to differentiate between tumor versus complete response. Accuracies per pattern were 100% (A), 74% (B), 86% (C), and 92% (D). Interobserver agreement was good (κ = 0.75). LIMITATIONS: The study included no comparison with routine (nonpattern) diffusion-MRI assessment. CONCLUSIONS: A pattern-based approach combining tumor morphology with distinct diffusion-weighted imaging patterns results in good diagnostic performance to assess response. See Video Abstract at http://links.lww.com/DCR/A433.

Myosteatosis predicts survival after surgery for periampullary cancer: a novel method using MRI.

BACKGROUND: Myosteatosis, characterized by inter- and intramyocellular fat deposition, is strongly related to poor overall survival after surgery for periampullary cancer. It is commonly assessed by calculating the muscle radiation attenuation on computed tomography (CT) scans. However, since magnetic resonance imaging (MRI) is replacing CT in routine diagnostic work-up, developing methods based on MRI is important. We developed a new method using MRI-muscle signal intensity to assess myosteatosis and compared it with CT-muscle radiation attenuation. METHODS: Patients were selected from a prospective cohort of 236 surgical patients with periampullary cancer. The MRI-muscle signal intensity and CT-muscle radiation attenuation were assessed at the level of the third lumbar vertebra and related to survival. RESULTS: Forty-seven patients were included in the study. Inter-observer variability for MRI assessment was low (R2 = 0.94). MRI-muscle signal intensity was associated with short survival: median survival 9.8 (95%-CI: 1.5-18.1) vs. 18.2 (95%-CI: 10.7-25.8) months for high vs. low intensity, respectively (p = 0.038). Similar results were found for CT-muscle radiation attenuation (low vs. high radiation attenuation: 10.8 (95%-CI: 8.5-13.1) vs. 15.9 (95%-CI: 10.2-21.7) months, respectively; p = 0.046). MRI-signal intensity correlated negatively with CT-radiation attenuation (r=-0.614, p < 0.001). CONCLUSIONS: Myosteatosis may be adequately assessed using either MRI-muscle signal intensity or CT-muscle radiation attenuation.

MRI surveillance for the detection of local recurrence in rectal cancer after transanal endoscopic microsurgery.

OBJECTIVES: To evaluate diagnostic performance of follow-up MRI for detection of local recurrence of rectal cancer after transanal endoscopic microsurgery (TEM). METHODS: Between January 2006 and February 2014, 81 patients who underwent TEM were included. Two expert readers (R1 and R2), independently evaluated T2-weighted (T2W) MRI and diffusion-weighted (DWI) MRI for the detection of local recurrence, retrospectively, and recorded confidence on a five-point scale. Diagnostic performance of follow-up MRI was assessed using ROC-curve analysis and kappa statistics for the reproducibility between readers. RESULTS: 293 MRIs were performed, 203 included DWI. 18 (22%) patients developed a local recurrence: luminal 11, nodal two and both five. Areas under the curve (AUCs) for local recurrence detection were 0.72 (R1) and 0.80 (R2) for T2W-MRI. For DWI, AUCs were 0.70 (R1) and 0.89 (R2). For nodal recurrence AUCs were 0.72 (R1) and 0.80 (R2) for T2W-MRI. Reproducibility was good for T2W-MRI (κ0.68 for luminal and κ0.71 for nodal recurrence) and moderate for DWI (κ0.57). AUCs and reproducibility for recurrence detection increased during follow-up. CONCLUSIONS: Follow-up with MRI after TEM for rectal cancer is feasible. Postoperative changes can be confusing at the first postoperative MRI, but during follow-up diagnostic performance and reproducibility increase. KEY POINTS: • Follow-up with MRI is feasible for follow-up after TEM for rectal cancer. • DWI-MRI is a useful addition to detect recurrences after TEM. • Postoperative changes can be confusing and can lead to underestimation of recurrence. • Appearance of intermediate signal at T2W-MRI is suspicious for recurrence. • Nodal staging remains challenging.

Diffusion-weighted MRI to assess response to chemoradiotherapy in rectal cancer: main interpretation pitfalls and their use for teaching.

OBJECTIVES: To establish the most common image interpretation pitfalls for non-expert readers using diffusion-weighted imaging (DWI) to assess response to chemoradiotherapy in patients with rectal cancer and to explore the use of these pitfalls in an expert teaching setting. METHODS: Two independent non-expert readers (R1 and R2) scored the restaging DW MRI scans (b1,000 DWI, in conjunction with ADC maps and T2-W MRI scans for anatomical reference) in 100 patients for the likelihood of a complete response versus residual tumour using a five-point confidence score. The readers received expert feedback and the final response outcome for each case. The supervising expert documented any potential interpretation errors/pitfalls discussed for each case to identify the most common pitfalls. RESULTS: The most common pitfalls were the interpretation of low signal on the ADC map, small susceptibility artefacts, T2 shine-through effects, suboptimal sequence angulation and collapsed rectal wall. Diagnostic performance (area under the ROC curve) was 0.78 (R1) and 0.77 (R2) in the first 50 patients and 0.85 (R1) and 0.85 (R2) in the final 50 patients. CONCLUSIONS: Five main image interpretation pitfalls were identified and used for teaching and feedback. Both readers achieved a good diagnostic performance with an AUC of 0.85. KEY POINTS: • Fibrosis appears hypointense on an ADC map and should not be mistaken for tumour. • Susceptibility artefacts on rectal DWI are an important potential pitfall. • T2 shine-through on rectal DWI is an important potential pitfall. • These pitfalls are useful to teach non-experts how to interpret rectal DWI.

MRI for Local Staging of Colon Cancer: Can MRI Become the Optimal Staging Modality for Patients With Colon Cancer?

BACKGROUND: Colon cancer is currently staged with CT. However, MRI is superior in the detection of colorectal liver metastasis, and MRI is standard in local staging of rectal cancer. Optimal (local) staging of colon cancer could become crucial in selecting patients for neoadjuvant treatment in the near future (Fluoropyrimidine Oxaliplatin and Targeted Receptor Preoperative Therapy trial). OBJECTIVE: The purpose of this study was to evaluate the diagnostic performance of MRI for local staging of colon cancer. DESIGN: This was a retrospective study. SETTINGS: The study was conducted at the Maastricht University Medical Centre. PATIENTS: In total, 55 patients with biopsy-proven colon carcinoma were included. MAIN OUTCOME MEASURES: All of the patients underwent an MRI (1.5-tesla; T2 and diffusion-weighted imaging) of the abdomen and were retrospectively analyzed by 2 blinded, independent readers. Histopathology after resection was the reference standard. Both readers evaluated tumor characteristics, including invasion through bowel wall (T3/T4 tumors), invasion beyond bowel wall of ≥5 mm and/or invasion of surrounding organs (T3cd/T4), serosal involvement, extramural vascular invasion, and malignant lymph nodes (N+). Interobserver agreement was compared using κ statistics. RESULTS: MRI had a high sensitivity (72%-91%) and specificity (84%-89%) in detecting T3/T4 tumors (35/55) and a low sensitivity (43%-67%) and high specificity (75%-88%) in detecting T3cd/T4 tumors (15/55). For detecting serosal involvement and extramural vascular invasion, MRI had a high sensitivity and moderate specificity, as well as a moderate sensitivity and specificity in the detection of nodal involvement. Interobserver agreements were predominantly good; the more experienced reader achieved better results in the majority of these categories. LIMITATIONS: The study was limited by its retrospective nature and moderate number of inclusions. CONCLUSIONS: MRI has a good sensitivity for tumor invasion through the bowel wall, extramural vascular invasion, and serosal involvement. In addition, together with its superior liver imaging, MRI might become the optimal staging modality for colon cancer. However, more research is needed to confirm this. See Video Abstract at http://links.lww.com/DCR/A309.

Prediction of incomplete primary debulking surgery in patients with advanced ovarian cancer: An external validation study of three models using computed tomography.

OBJECTIVE: To test the ability of three prospectively developed computed tomography (CT) models to predict incomplete primary debulking surgery in patients with advanced (International Federation of Gynecology and Obstetrics stages III-IV) ovarian cancer. METHODS: Three prediction models to predict incomplete surgery (any tumor residual >1cm in diameter) previously published by Ferrandina (models A and B) and by Gerestein were applied to a validation cohort consisting of 151 patients with advanced epithelial ovarian cancer. All patients were treated with primary debulking surgery in the Eastern part of the Netherlands between 2000 and 2009 and data were retrospectively collected. Three individual readers evaluated the radiographic parameters and gave a subjective assessment. Using the predicted probabilities from the models, the area under the curve (AUC) was calculated which represents the discriminative ability of the model. RESULTS: The AUC of the Ferrandina models was 0.56, 0.59 and 0.59 in model A, and 0.55, 0.60 and 0.59 in model B for readers 1, 2 and 3, respectively. The AUC of Gerestein's model was 0.69, 0.61 and 0.69 for readers 1, 2 and 3, respectively. AUC values of 0.69 and 0.63 for reader 1 and 3 were found for subjective assessment. CONCLUSIONS: Models to predict incomplete surgery in advanced ovarian cancer have limited predictive ability and their reproducibility is questionable. Subjective assessment seems as successful as applying predictive models. Present prediction models are not reliable enough to be used in clinical decision-making and should be interpreted with caution.

Diagnostic Accuracy of CT for Local Staging of Colon Cancer: A Systematic Review and Meta-Analysis.

OBJECTIVE: The purpose of this article is to determine the accuracy of CT in the detection of tumor invasion beyond the bowel wall and nodal involvement of colon carcinomas. A literature search was performed to identify studies describing the accuracy of CT in the staging of colon carcinomas. Studies including rectal carcinomas that were inseparable from colon carcinomas were excluded. Publication bias was explored by using a Deeks funnel plot asymmetry test. A hierarchic summary ROC model was used to construct a summary ROC curve and to calculate summary estimates of sensitivity, specificity, and diagnostic odds ratios (ORs). CONCLUSION: On the basis of a total of 13 studies, pooled sensitivity, specificity, and diagnostic ORs for detection of tumor invasion beyond the bowel wall (T3-T4) were 90% (95% CI, 83-95%), 69% (95% CI, 62-75%), and 20.6 (95% CI, 10.2-41.5), respectively. For detection of tumor invasion depth of 5 mm or greater (T3cd-T4), estimates from four studies were 77% (95% CI, 66-85%), 70% (95% CI, 53-83%), and 7.8 (95% CI, 4.2-14.2), respectively. For nodal involvement (N+), 16 studies were included with values of 71% (95% CI, 59-81%), 67% (95% CI, 46-83%), and 4.8 (95% CI, 2.5-9.4), respectively. Two studies using CT colonography were included with sensitivity and specificity of 97% (95% CI, 90-99%) and 81% (95% CI, 65-91%), respectively, for detecting T3-T4 tumors. CT has good sensitivity for the detection of T3-T4 tumors, and evidence suggests that CT colonography increases its accuracy. Discriminating between T1-T3ab and T3cd-T4 cancer is challenging, but data were limited. CT has a low accuracy in detecting nodal involvement.

Performance of gadofosveset-enhanced MRI for staging rectal cancer nodes: can the initial promising results be reproduced?

OBJECTIVES: A previous study showed promising results for gadofosveset-trisodium as a lymph node magnetic resonance imaging (MRI) contrast agent in rectal cancer. The aim of this study was to prospectively confirm the diagnostic performance of gadofosveset MRI for nodal (re)staging in rectal cancer in a second patient cohort. METHODS: Seventy-one rectal cancer patients were prospectively included, of whom 13 (group I) underwent a primary staging gadofosveset MRI (1.5-T) followed by surgery (± preoperative 5 × 5 Gy) and 58 (group II) underwent both primary staging and restaging gadofosveset MRI after a long course of chemoradiotherapy followed by surgery. Nodal status was scored as (y)cN0 or (y)cN+ by two independent readers (R1, R2) with different experience levels. Results were correlated with histology on a node-by-node basis. RESULTS: Sensitivity, specificity and area under the receiver operating characteristics curve (AUC) were 94%, 79% and 0.89 for the more experienced R1 and 50%, 83% and 0.74 for the non-experienced R2. R2's performance improved considerably after a learning curve, to an AUC of 0.83. Misinterpretations mainly occurred in nodes located in the superior mesorectum, nodes located in between vessels and nodes containing micrometastases. CONCLUSIONS: This prospective study confirms the good diagnostic performance of gadofosveset MRI for nodal (re)staging in rectal cancer. KEY POINTS: • Gadofosveset-enhanced MRI shows high performance for nodal (re)staging in rectal cancer. • Gadofosveset MRI may facilitate better selection of patients for personalised treatment. • Results can be reproduced by non-expert readers. • Experience of 50-60 cases is required to achieve required expertise level. • Main pitfalls are nodes located between vessels and nodes containing micrometastases.

Gadofosveset-enhanced MRI for the assessment of rectal cancer lymph nodes: predictive criteria.

PURPOSE: To confirm the use of the nodal signal intensity (SI) and the 'chemical shift' artefact as diagnostic criteria for detecting nodal metastases from rectal cancer on gadofosveset contrast-enhanced MRI. METHODS: Thirty-three patients underwent a non-enhanced and gadofosveset-enhanced 3D-T1W GRE-MRI at 1.5T. For each lymph node, the SI of the middle part of the node (mSI) and white rim of the chemical shift artefact encircling the node (wSI) were measured on the non-enhanced and gadofosveset-enhanced images. Second, the aspect of the chemical shift artefact encircling the nodes was scored using a 4-point scale. Results were compared with histology on a node-by-node basis. RESULTS: 289 nodes (55 N+) were analysed. On gadofosveset-MRI, mSI and wSI were significantly higher for the benign than for the metastatic lymph nodes (p < 0.001). Areas under the ROC curve (AUC) for identification of metastases were 0.74 (mSI) and 0.73 (wSI). The chemical shift criterion rendered an AUC of 0.85. The combination of mSI and the chemical shift criterion resulted in an AUC of 0.88 and the rendered an AUC of 0.86-0.92 when subjectively (visually) assessed by two independent readers. CONCLUSIONS: Benign lymph nodes show significant contrast enhancement after gadofosveset injection, while metastatic nodes do not. The uptake of gadofosveset in the nodes also affects the chemical shift artefact encircling the nodes. Combined assessment of these two features on gadofosveset-enhanced MRI provides a high diagnostic performance for diagnosing metastatic lymph nodes in patients with rectal cancer.

Hyperferritinemia and liver iron content determined with MRI: Reintroduction of the liver iron index.

BACKGROUND: Hyperferritinemia is found in around 12 % of the general population. Analyzing the cause can be difficult. In case of doubt about the presence of major iron overload most guidelines advice to perform a MRI as a reliable non-invasive marker to measure liver iron concentration (LIC). In general, a LIC of ≥ 36 µmol/g dw is considered the be elevated however in hyperferritinemia associated with, for example, obesity or alcohol (over)consumption the LIC can be ≥ 36 µmol/g dw in abscence of major iron overload. So, unfortunately a clear cut-off value to differentiate iron overload from normal iron content is lacking. Previously the liver iron index (LII) (LIC measured in liver biopsy (LIC-b)/age (years)), was introduced to differentiate between patients with major (LII ≥ 2) and minor or no iron overload (LII < 2). Based on the good correlation between the LIC-b and LIC determined with MRI (LIC-MRI), our goal was to investigate whether a LII_MRI ≥ 2 is a good indicator of major iron overload, reflected by a significantly higher amount of iron needed to be mobilized to reach iron depletion. METHODS: We compared the amount of mobilized iron to reach depletion and inflammation-related characteristics in two groups: LII-MRI ≥ 2 versus LII-MRI <2 in 92 hyperferritinemia patients who underwent HFE genotyping and MRI-LIC determination. RESULTS: Significantly more iron needed to be mobilized to reach iron depletion in the LII ≥ 2 group (mean 4741, SD ± 4135 mg) versus the LII-MRI <2 group (mean 1340, SD ± 533 mg), P < 0.001. Furthermore, hyperferritinemia in LII-MRI < 2 patients was more often related to components of the metabolic syndrome while hyperferritinemia in LII-MRI ≥ 2 patients was more often related to HFE mutations. ROC curve analysis showed good performance of LII =2 as cut-off value. However the calculations showed that the optimal cut-off for the LII = 3.4. CONCLUSION: The LII-MRI with a cut-off value of 2 is an effective method to differentiate major from minor iron overload in patients with hyperferritinemia. But the LII-MRI = 3.4 seems a more promising diagnostic test for major iron overload.

BioXmark® liquid fiducials to enable radiotherapy tumor boosting in rectal cancer, a feasibility trial.

Background and purpose: Dose-escalation in rectal cancer (RCa) may result in an increased complete response rate and thereby enable omission of surgery and organ preservation. In order to implement dose-escalation, it is crucial to develop a technique that allows for accurate image-guided radiotherapy. The aim of the current study was to determine the performance of a novel liquid fiducial marker (BioXmark®) in RCa patients during the radiotherapy course by assessing its positional stability on daily cone-beam CT (CBCT), technical feasibility, visibility on different imaging modalities and safety. Materials and methods: Prospective, non-randomized, single-arm feasibility trial with inclusion of twenty patients referred for neoadjuvant chemoradiotherapy for locally advanced RCa. Primary study endpoint was positional stability on CBCT. Furthermore, technical aspects, safety and clinical performance of the marker, such as visibility on different imaging modalities, were evaluated. Results: Seventy-four markers from twenty patients were available for analysis. The marker was stable in 96% of the cases. One marker showed clinically relevant migration, one marker was lost before start of treatment and one marker was lost during treatment. Marker visibility was good on computed tomography (CT) and CBCT, and moderate on electronic portal imaging (EPI). Marker visibility on magnetic resonance imaging (MRI) was poor during response evaluation. Conclusion: The novel liquid fiducial marker demonstrated positional stability. We provide evidence of the feasibility of the novel fiducial marker for image-guided radiotherapy on daily cone beam CT for RCa patients.