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.

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.

Efficacy of postmortem CT and tissue sampling in establishing the cause of death in clinical practice: a prospective observational study.

AIMS: The aim of this study is to evaluate whether agreement with autopsy-determined cause of death (COD) increases by use of postmortem CT (PMCT) or PMCT in combination with postmortem sampling (PMS), when compared with clinical assessment only. METHODS: This prospective observational study included deceased patients from the intensive care unit and internal medicine wards between October 2013 and August 2017. The primary outcome was percentage agreement on COD between the reference standard (autopsy) and the alternative postmortem examinations (clinical assessment vs PMCT or PMCT+PMS). In addition, the COD of patient groups with and without conventional autopsy were compared with respect to involved organ systems and pathologies. RESULTS: Of 730 eligible cases, 144 could be included for analysis: 63 underwent PCMT without autopsy and 81 underwent both PMCT and autopsy. Agreement with autopsy-determined COD was significantly higher for both PMCT with PMS (42/57, 74%), and PMCT alone (53/81, 65%) than for clinical assessment (40/81, 51%; p=0.007 and p=0.03, respectively). The difference in agreement between PMCT with PMS and PMCT alone was not significant (p=0.13). The group with autopsy had a significantly higher prevalence of circulatory system involvement and perfusion disorders, and a lower prevalence of pulmonary system involvement. CONCLUSION: PMCT and PMS confer additional diagnostic value in establishing the COD. Shortcomings in detecting vascular occlusions and perfusion disorders and susceptibility to pulmonary postmortem changes could in future be improved by additional techniques. Both PMCT and PMS are feasible in clinical practice and an alternative when autopsy cannot be performed.

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.

Edema in critically ill patients leads to overestimation of skeletal muscle mass measurements using computed tomography scans.

OBJECTIVES: Changes in muscle mass and quality are important targets for nutritional intervention in critical illness. Effects of such interventions may be assessed using sequential computed tomography (CT) scans. However, fluid and lipid infiltration potentially affects muscle area measurements. The aim of this study was to evaluate changes in muscle mass and quality in critical illness with special emphasis on the influence of edema on this assessment. METHODS: Changes in skeletal muscle area index (SMI) and radiation attenuation (RA) at the level of vertebra L3 were analyzed using sequential CT scans of 77 patients with abdominal sepsis. Additionally, the relation between these changes and disease severity using the maximum Sequential Organ Failure Assessment (SOFA) score and change in edema were studied. RESULTS: SMI declined on average 0.35%/d (±1.22%; P = 0.013). However, SMI increased in 41.6% of the study population. Increasing edema formation was significantly associated with increased SMI and with a higher SOFA score. Muscle RA decreased during critical illness, but was not significantly associated with changes in SMI or changes in edema. CONCLUSION: In critically ill patients, edema affects skeletal muscle area measurements, which leads to an overestimation of skeletal muscle area. A higher SOFA score was associated with edema formation. Because both edema and fat infiltration may affect muscle RA, the separate effects of these on muscle quality are difficult to distinguish. When using abdominal CT scans to changes in muscle mass and quality in critically ill patients, researchers must be aware and careful with the interpretation of the results.

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.

Introduction of postmortem CT increases the postmortem examination rate without negatively impacting the rate of traditional autopsy in daily practice: an implementation study.

AIM: The aim of this implementation study was to assess the effect of postmortem CT (PMCT) and postmortem sampling (PMS) on (traditional) autopsy and postmortem examination rates. Additionally, the feasibility of PMCT and PMS in daily practice was assessed. METHODS: For a period of 23 months, PMCT and PMS were used as additional modalities to the autopsy at the Department of Internal Medicine. The next of kin provided consent for 123 postmortem examinations. Autopsy rates were derived from the Dutch Pathology Registry, and postmortem examination rates were calculated for the period before, during and after the study period, and the exclusion rate, table time, time interval to informing the referring clinicians with results and the time interval to the Multidisciplinary Mortality Review Board (MMRB) meeting were objectified to assess the feasibility. RESULTS: The postmortem examination rate increased (from 18.8% to 32.5%, p<0.001) without a decline in the autopsy rate. The autopsy rate did not change substantially after implementation (0.2% decrease). The exclusion rate was 2%, the table time was 23 min, and a median time interval of 4.1 hours between PMCT and discussing its results with the referring clinicians was observed. Additionally, more than 80% of the MMRB meetings were held within 8 weeks after the death of the patient. CONCLUSIONS: Our study shows that the implementation of a multidisciplinary postmortem examination is feasible in daily practice and does not adversely affect the autopsy rate, while increasing the postmortem examination rate.

Clinical Relevance of Unexpected Findings of Post-Mortem Computed Tomography in Hospitalized Patients: An Observational Study.

Background and objective: The current literature describing the use of minimally invasive autopsy in clinical care is mainly focused on the cause of death. However, the identification of unexpected findings is equally important for the evaluation and improvement of daily clinical care. The purpose of this study was to analyze unexpected post-mortem computed tomography (PMCT) findings of hospitalized patients and assess their clinical relevance. Materials and methods: This observational study included patients admitted to the internal medicine ward. Consent for PMCT and autopsy was requested from the next of kin. Decedents were included when consent for at least PMCT was obtained. Consent for autopsy was not obtained for all decedents. All findings reported by PMCT were coded with an International Classification of Diseases (ICD) code. Unexpected findings were identified and subsequently categorized for their clinical relevance by the Goldman classification. Goldman class I and III were considered clinically relevant. Additionally, correlation with autopsy results and ante-mortem imaging was performed. Results: In total, 120 decedents were included and evaluated for unexpected findings on PMCT. Of them, 57 decedents also underwent an autopsy. A total of 1020 findings were identified; 111 correlated with the cause of death (10.9%), 508 were previously reported (49.8%), 99 were interpreted as post-mortem changes (9.7%), and 302 were classified as unexpected findings (29.6%). After correlation with autopsy (in 57 decedents), 24 clinically relevant unexpected findings remained. These findings were reported in 18 of 57 decedents (32%). Interestingly, 25% of all unexpected findings were not reported by autopsy. Conclusion: Many unexpected findings are reported by PMCT in hospitalized patients, a substantial portion of which is clinically relevant. Additionally, PMCT is able to identify pathology and injuries not reported by conventional autopsy. A combination of PMCT and autopsy can thus be considered a more comprehensive and complete post-mortem examination.

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.

MRI predicts increased eligibility for sphincter preservation after CRT in low rectal cancer.

Chemoradiation increases the eligibility for sphincter preservation in low rectal cancer, as assessed by MRI. INTRODUCTION: We evaluated whether MRI can predict sphincter preservation after chemoradiation (CRT), and whether the feasibility of sphincter preservation increases after CRT, when compared with MRI before neoadjuvant treatment. METHODS: 85 patients with low rectal tumour (≤5 cm from anorectal junction (ARJ)) were included. Radiologist and a surgeon measured the tumour distance to ARJ, and assigned confidence level scores (CLS) for the feasibility of sphincter preserving surgery on MRI. Reference standard was the type of surgery, sphincter preserving vs. non-preserving. RESULTS: Tumour distance from the ARJ increased after CRT by 9 mm (p < 0.001). Eligibility for sphincter preservation increased by 21% for the radiologist and 25% for the surgeon, based on CLS. Cut-off for distance to the ARJ after CRT was 28 mm, aiming for optimal specificity. Diagnostic performance after CRT based on CLS yielded an AUC of 0.81 [95%CI 0.70-0.91] for the radiologist and 0.82 [95%CI 0.72-0.92] for the surgeon (p = 0.78). AUCs for tumour distance to the ARJ were 0.85 [95%CI 0.77-0.94] and 0.84 [95%CI 0.75-0.94], respectively (p = 0.84). Interobserver agreement for CLS was moderate before CRT (Κ 0.51; 95%CI 0.36-0.66) and after (K 0.54; 95%CI 0.39-0.69). Measurement of tumour distance to ARJ showed good agreement before (ICC 0.76; 95%CI 0.65-0.84) and after CRT (ICC 0.77; 95%CI 0.66-0.84). CONCLUSION: MRI can be a valuable adjunct in the decision making for sphincter preservation after CRT, with distance from the tumour to the ARJ as an accurate and reliable factor. CRT increases the tumour distance to the ARJ, leading to an estimated increase of sphincter preserving surgery in up to 21-25% of patients.

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.

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.

Muscle wasting associated co-morbidities, rather than sarcopenia are risk factors for hospital mortality in critical illness.

BACKGROUND: Low skeletal muscle mass on intensive care unit admission is related to increased mortality. It is however unknown whether this association is influenced by co-morbidities that are associated with skeletal muscle loss. The aim of this study was to investigate whether sarcopenia is an independent risk factor for hospital mortality in critical illness in the presence of co-morbidities associated with muscle wasting. METHODS: Data of 155 patients with abdominal sepsis were retrospectively analyzed. Skeletal muscle area was assessed using CT-scans at the level of vertebra L3. Demographic and clinical data were retrieved from electronic patient files. Sarcopenia was defined as a muscle area index below the 5th percentile of the general population. Uni- and multivariable analyses were performed to assess the association between sarcopenia and hospital mortality, correcting for age and comorbidities. RESULTS: The prevalence of sarcopenia was higher in patients that did not survive until hospital discharge. However, it appeared that this relation was confounded by the presence of chronic renal insufficiency and cancer. These were independent risk factors for hospital mortality, whereas sarcopenia was not. CONCLUSION: In critically ill patients with abdominal sepsis, muscle wasting associated co-morbidities rather than sarcopenia were risk factors for hospital mortality.

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.

The Apparent Diffusion Coefficient (ADC) is a useful biomarker in predicting metastatic colon cancer using the ADC-value of the primary tumor.

PURPOSE: To investigate the role of the apparent diffusion coefficient (ADC) as a potential imaging biomarker to predict metastasis (lymph node metastasis and distant metastasis) in colon cancer based on the ADC-value of the primary tumor. METHODS: Thirty patients (21M, 9F) were included retrospectively. All patients received a 1.5T MRI of the colon including T2 and DWI sequences. ADC maps were calculated for each patient. An expert reader manually delineated all colon tumors to measure mean ADC and histogram metrics (mean, min, max, median, standard deviation (SD), skewness, kurtosis, 5th-95th percentiles) were calculated. Advanced colon cancer was defined as lymph node mestastasis (N+) or distant metastasis (M+). The student Mann Whitney U-test was used to assess the differences between the ADC means of early and advanced colon cancer. To compare the accuracy of lymph node metastasis (N+) prediction based on morpholigical criteria versus ADC-value of the primary tumor, two blinded readers, determined the lymph node metastasis (N0 vs N+) based on morphological criteria. The sensitivity and specificity in predicting lymph node metastasis was calculated for both readers and for the ADC-value of the primary tumor, with histopathology results as the gold standard. RESULTS: There was a significant difference between the mean ADC-value of advanced versus early tumors (p = 0.002). The optimal cut off value was 1179 * 10-3 mm2/s with an area under the curve (AUC) of 0.83 and a sensitivity and specificity of 81% and 86% respectively to predict advanced tumors. Histogram analyses did not add any significant additional value. The sensitivity and specificity for the prediction of lymph node metastasis based on morphological criteria were 40% and 63% for reader 1 and 30% and 88% for reader 2 respectively. The primary tumor ADC-value using 1.179 * 10-3 mm2/s as threshold had a 100% sensitivity and specificity in predicting lymph node metastasis. CONCLUSION: The ADC-value of the primary tumor has the potential to predict advanced colon cancer, defined as lymph node metastasis or distant metastasis, with lower ADC values significantly associated with advanced tumors. Furthermore the ADC-value of the primary tumor increases the prediction accuracy of lymph node metastasis compared with morphological criteria.

18F-FDG PET/MRI in the diagnosis of an infected aortic aneurysm.

We report a case where an integrated whole body 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) is performed in the diagnostic work-up of a saccular aortic aneurysm. The integrated whole body 18F-FDG PET/MRI study answered all relevant diagnostic questions, clearly marking an infected aortic aneurysm, depicting the extent of the infected area in relation to the aortic branch vessels, and indicating the aortic lesion as the primary site of infection. The patient was successfully treated by open type V TAAA repair and pericardial graft replacement. Aortic wall infection was proven in cultures of the surgical specimen.

Correction: Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.

[This corrects the article DOI: 10.1371/journal.pone.0184197.].

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.