Publications by authors named "Frans C Bakers"

38 Publications

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

Eur Radiol 2021 Oct 16. Epub 2021 Oct 16.

Department of Radiology, The Netherlands Cancer Institute, POB 90203, 1006 BE, Amsterdam, The Netherlands.

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.
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http://dx.doi.org/10.1007/s00330-021-08251-8DOI Listing
October 2021

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

Nutrition 2021 09 7;89:111238. Epub 2021 Mar 7.

Department of Intensive Care Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands; School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, the Netherlands; Department of Surgery, Maastricht University Medical Centre, Maastricht, the Netherlands.

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.
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http://dx.doi.org/10.1016/j.nut.2021.111238DOI Listing
September 2021

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

Eur Radiol 2021 Sep 10;31(9):7031-7038. Epub 2021 Feb 10.

Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

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 (T2W/T2W/ADC/SUV/TLG/CT) 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.
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http://dx.doi.org/10.1007/s00330-021-07724-0DOI Listing
September 2021

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

Int J Environ Res Public Health 2020 10 18;17(20). Epub 2020 Oct 18.

Department of Radiology and Nuclear Medicine, Maastricht UMC, P. Debyelaan 25, 6229 HX Maastricht, The Netherlands.

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. 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. : 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. 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.
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http://dx.doi.org/10.3390/ijerph17207572DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589901PMC
October 2020

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

J Clin Pathol 2021 Mar 16;74(3):177-181. Epub 2020 Jul 16.

Department of Radiology and Nuclear Medicine, Maastricht Universitair Medisch Centrum+, Maastricht, The Netherlands.

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.
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http://dx.doi.org/10.1136/jclinpath-2020-206734DOI Listing
March 2021

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

J Gastroenterol Hepatol 2020 Nov 27;35(11):1902-1908. Epub 2020 Apr 27.

Division of Gastroenterology-Hepatology, Maastricht University Medical Centre+, Maastricht, The Netherlands.

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.
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http://dx.doi.org/10.1111/jgh.15068DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7687168PMC
November 2020

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

J Digit Imaging 2020 08;33(4):1002-1008

Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, Netherlands.

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.
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http://dx.doi.org/10.1007/s10278-020-00327-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7522136PMC
August 2020

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

Radiother Oncol 2020 04 15;145:223-228. Epub 2020 Feb 15.

Department of Radiology, The Netherlands Cancer Institute Amsterdam, The Netherlands. Electronic address:

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.
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http://dx.doi.org/10.1016/j.radonc.2020.01.014DOI Listing
April 2020

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

Eur Radiol 2020 May 7;30(5):2945-2954. Epub 2020 Feb 7.

Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

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 (MTV) 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.
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http://dx.doi.org/10.1007/s00330-019-06638-2DOI Listing
May 2020

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

J Crit Care 2020 04 26;56:31-36. Epub 2019 Nov 26.

Department of Intensive Care Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands; School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, the Netherlands; Department of Surgery, Maastricht University Medical Centre, Maastricht, the Netherlands.

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.
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http://dx.doi.org/10.1016/j.jcrc.2019.11.016DOI Listing
April 2020

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

Abdom Radiol (NY) 2020 03;45(3):632-643

Department of Radiology, The Netherlands Cancer Institute, PO Box 90203, 1006 BE, Amsterdam, The Netherlands.

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.
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http://dx.doi.org/10.1007/s00261-019-02321-8DOI Listing
March 2020

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

Eur Radiol 2020 Jan 19;30(1):272-280. Epub 2019 Aug 19.

Department of Radiology, Netherlands Cancer Institute, PO Box 90203, 1006 BE, Amsterdam, The Netherlands.

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.
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http://dx.doi.org/10.1007/s00330-019-06396-1DOI Listing
January 2020

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

PLoS One 2019 5;14(2):e0211830. Epub 2019 Feb 5.

Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0211830PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6363286PMC
November 2019

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

Cardiovasc Diagn Ther 2018 Apr;8(Suppl 1):S208-S211

Department of Nuclear Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands.

We report a case where an integrated whole body F-fluorodeoxyglucose (F-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 F-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.
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http://dx.doi.org/10.21037/cdt.2017.08.05DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949589PMC
April 2018

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

HPB (Oxford) 2018 08 5;20(8):715-720. Epub 2018 Mar 5.

Department of Surgery, Maastricht University Medical Centre, Maastricht, The Netherlands; NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, The Netherlands; Department of General, Visceral and Transplantation Surgery, RWTH University Hospital Aachen, Aachen, Germany.

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 (R = 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.
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http://dx.doi.org/10.1016/j.hpb.2018.02.378DOI Listing
August 2018

Author Correction: Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR.

Sci Rep 2018 02 2;8(1):2589. Epub 2018 Feb 2.

Department of Radiology, the Netherlands Cancer Institute, Amsterdam, The Netherlands.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.
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http://dx.doi.org/10.1038/s41598-018-20029-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797196PMC
February 2018

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.

Dis Colon Rectum 2018 Mar;61(3):328-337

Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands.

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.
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http://dx.doi.org/10.1097/DCR.0000000000000915DOI Listing
March 2018

Gas-induced susceptibility artefacts on diffusion-weighted MRI of the rectum at 1.5 T - Effect of applying a micro-enema to improve image quality.

Eur J Radiol 2018 Feb 28;99:131-137. Epub 2017 Dec 28.

Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. Electronic address:

Purpose: Assess whether application of a micro-enema can reduce gas-induced susceptibility artefacts in Single-shot Echo Planar Imaging (EPI) Diffusion-weighted imaging of the rectum at 1.5 T.

Materials And Methods: Retrospective analysis of n = 50 rectal cancer patients who each underwent multiple DWI-MRIs (1.5 T) from 2012 to 2016 as part of routine follow-up during a watch-and-wait approach after chemoradiotherapy. From March 2014 DWI-MRIs were routinely acquired after application of a preparatory micro-enema (Microlax; 5 ml; self-administered shortly before acquisition); before March 2014 no bowel preparation was given. In total, 335 scans were scored by an experienced reader for the presence/severity of gas-artefacts (on b1000 DWI), ranging from 0 (no artefact) to 5 (severe artefact). A score ≥3 (moderate-severe) was considered a clinically relevant artefact. A random sample of 100 scans was re-assessed by a second independent reader to study inter-observer effects. Scores were compared between the scans performed without and with a preparatory micro-enema using univariable and multivariable logistic regression taking into account potential confounding factors (age/gender, acquisition parameters, MRI-hardware, rectoscopy prior to MRI).

Results: Clinically relevant gas-artefacts were seen in 24.3% (no micro-enema) vs. 3.7% (micro-enema), odds ratios were 0.118 in univariable and 0.230 in multivariable regression (P = 0.0005 and 0.0291). Mean severity score (±SD) was 1.19 ± 1.71 (no-enema) vs 0.32 ± 0.77 (micro-enema), odds ratios were 0.321 (P < 0.0001) and 0.489 (P = 0.0461) in uni- and multivariable regression, respectively. Inter-observer agreement was excellent (κ0.85).

Conclusion: Use of a preparatory micro-enema shortly before rectal EPI-DWI examinations performed at 1.5 T MRI significantly reduces both the incidence and severity of gas-induced artefacts, compared to examinations performed without bowel preparation.
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http://dx.doi.org/10.1016/j.ejrad.2017.12.020DOI Listing
February 2018

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

PLoS One 2017 1;12(9):e0184197. Epub 2017 Sep 1.

Clinical Computational Imaging Group, Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal.

Purpose: The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer.

Material And Methods: Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2) at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG) and non-Gaussian (MNG and BNG) were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE). To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC) and F-ratio.

Results: All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area.

Conclusion: No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0184197PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593499PMC
October 2017

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR.

Sci Rep 2017 07 13;7(1):5301. Epub 2017 Jul 13.

Department of Radiology, the Netherlands Cancer Institute, Amsterdam, The Netherlands.

Multiparametric Magnetic Resonance Imaging (MRI) can provide detailed information of the physical characteristics of rectum tumours. Several investigations suggest that volumetric analyses on anatomical and functional MRI contain clinically valuable information. However, manual delineation of tumours is a time consuming procedure, as it requires a high level of expertise. Here, we evaluate deep learning methods for automatic localization and segmentation of rectal cancers on multiparametric MR imaging. MRI scans (1.5T, T2-weighted, and DWI) of 140 patients with locally advanced rectal cancer were included in our analysis, equally divided between discovery and validation datasets. Two expert radiologists segmented each tumor. A convolutional neural network (CNN) was trained on the multiparametric MRIs of the discovery set to classify each voxel into tumour or non-tumour. On the independent validation dataset, the CNN showed high segmentation accuracy for reader1 (Dice Similarity Coefficient (DSC = 0.68) and reader2 (DSC = 0.70). The area under the curve (AUC) of the resulting probability maps was very high for both readers, AUC = 0.99 (SD = 0.05). Our results demonstrate that deep learning can perform accurate localization and segmentation of rectal cancer in MR imaging in the majority of patients. Deep learning technologies have the potential to improve the speed and accuracy of MRI-based rectum segmentations.
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http://dx.doi.org/10.1038/s41598-017-05728-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509680PMC
July 2017

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

Eur Radiol 2017 Dec 30;27(12):4960-4969. Epub 2017 Jun 30.

GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.

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.
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http://dx.doi.org/10.1007/s00330-017-4853-5DOI Listing
December 2017

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

Eur Radiol 2017 Oct 13;27(10):4445-4454. Epub 2017 Apr 13.

Department of Radiology, The Netherlands Cancer Institute, PO Box 90203, 1006 BE, Amsterdam, The Netherlands.

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.
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http://dx.doi.org/10.1007/s00330-017-4830-zDOI Listing
October 2017

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

Dis Colon Rectum 2017 Apr;60(4):385-392

1 Department of Radiology, Catharina Hospital, Eindhoven, the Netherlands 2 GROW School of Oncology and Developmental Biology, University of Maastricht Medical Centre, Maastricht, the Netherlands 3 Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands 4 Department of Radiology, Maastricht University Medical Centre, Maastricht, the Netherlands 5 Department of Pathology, Maastricht University Medical Centre, Maastricht, the Netherlands 6 Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom.

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.
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http://dx.doi.org/10.1097/DCR.0000000000000794DOI Listing
April 2017

Measuring the apparent diffusion coefficient in primary rectal tumors: is there a benefit in performing histogram analyses?

Abdom Radiol (NY) 2017 06;42(6):1627-1636

Department of Radiology, The Netherlands Cancer Institute, P.O. Box 90203, 1006 BE, Amsterdam, The Netherlands.

Purpose: The apparent diffusion coefficient (ADC) is a potential prognostic imaging marker in rectal cancer. Typically, mean ADC values are used, derived from precise manual whole-volume tumor delineations by experts. The aim was first to explore whether non-precise circular delineation combined with histogram analysis can be a less cumbersome alternative to acquire similar ADC measurements and second to explore whether histogram analyses provide additional prognostic information.

Methods: Thirty-seven patients who underwent a primary staging MRI including diffusion-weighted imaging (DWI; b0, 25, 50, 100, 500, 1000; 1.5 T) were included. Volumes-of-interest (VOIs) were drawn on b1000-DWI: (a) precise delineation, manually tracing tumor boundaries (2 expert readers), and (b) non-precise delineation, drawing circular VOIs with a wide margin around the tumor (2 non-experts). Mean ADC and histogram metrics (mean, min, max, median, SD, skewness, kurtosis, 5th-95th percentiles) were derived from the VOIs and delineation time was recorded. Measurements were compared between the two methods and correlated with prognostic outcome parameters.

Results: Median delineation time reduced from 47-165 s (precise) to 21-43 s (non-precise). The 45th percentile of the non-precise delineation showed the best correlation with the mean ADC from the precise delineation as the reference standard (ICC 0.71-0.75). None of the mean ADC or histogram parameters showed significant prognostic value; only the total tumor volume (VOI) was significantly larger in patients with positive clinical N stage and mesorectal fascia involvement.

Conclusion: When performing non-precise tumor delineation, histogram analysis (in specific 45th ADC percentile) may be used as an alternative to obtain similar ADC values as with precise whole tumor delineation. Histogram analyses are not beneficial to obtain additional prognostic information.
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http://dx.doi.org/10.1007/s00261-017-1062-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486825PMC
June 2017

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

AJR Am J Roentgenol 2016 Nov 4;207(5):984-995. Epub 2016 Aug 4.

2 GROW School of Oncology and Developmental Biology, University of Maastricht, Maastricht, The Netherlands.

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.
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http://dx.doi.org/10.2214/AJR.15.15785DOI Listing
November 2016

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

Gynecol Oncol 2016 Jan 24;140(1):22-8. Epub 2015 Nov 24.

Department of Obstetrics and Gynecology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.

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.
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http://dx.doi.org/10.1016/j.ygyno.2015.11.022DOI Listing
January 2016

Pancreatic atrophy after allogeneic peripheral blood stem cell transplantation.

Br J Haematol 2016 Jan 25;172(2):155. Epub 2015 Aug 25.

Department of Haematology, Maastricht University Medical Centre, Maastricht, The Netherlands.

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http://dx.doi.org/10.1111/bjh.13643DOI Listing
January 2016

RECIST measurements in cancer treatment: is there a role for physician assistants? - A pilot study.

Cancer Imaging 2014 Apr 22;14:12. Epub 2014 Apr 22.

Background: Decision making in cancer treatment is influenced by standardized RECIST measurements which are subjective to interobserver variability. Aim of this pilot study was to evaluate whether it is feasible to transfer the radiologist's task of RECIST measurements to a trained radiology physician assistant and whether this influences diagnostic performance.

Methods: 177 lesions in twenty patients were measured on baseline and two follow-up CTs using RECIST 1.1: Arm A according to routine clinical practice where various radiologists read scans of the referred patients. Arm B according to the experimental setting where a radiology physician assistant performed RECIST measurements of target lesions defined by the radiologists on baseline scans. Performance and agreement were compared between groups.

Results: Standard deviation between lesion measurements of arm A and B was four millimeters. Interobserver agreement comparing response category classification was substantial, ĸ = 0.77 (95% CI: 0.66 - 0.87). Sensitivity and specificity for the radiology physician assistant for assessing progressive disease were 100% (95% CI: 61% - 100%) and 94% (95% CI: 81% - 98%) respectively.

Conclusion: RECIST measurements performed by a paramedic are a feasible alternative to standard practice. This could impact the workflow of radiological units, opening ways to re-assigning radiologists' important, standardized but time consuming tasks to paramedics.
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http://dx.doi.org/10.1186/1470-7330-14-12DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331818PMC
April 2014
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