MRI in addition to CT in patients scheduled for local therapy of colorectal liver metastases (CAMINO): an international, multicentre, prospective, diagnostic accuracy trial.

BACKGROUND: Guidelines are inconclusive on whether contrast-enhanced MRI using gadoxetic acid and diffusion-weighted imaging should be added routinely to CT in the investigation of patients with colorectal liver metastases who are scheduled for curative liver resection or thermal ablation, or both. Although contrast-enhanced MRI is reportedly superior than contrast-enhanced CT in the detection and characterisation of colorectal liver metastases, its effect on clinical patient management is unknown. We aimed to assess the clinical effect of an additional liver contrast-enhanced MRI on local treatment plan in patients with colorectal liver metastases amenable to local treatment, based on contrast-enhanced CT. METHODS: We did an international, multicentre, prospective, incremental diagnostic accuracy trial in 14 liver surgery centres in the Netherlands, Belgium, Norway, and Italy. Participants were aged 18 years or older with histological proof of colorectal cancer, a WHO performance status score of 0-4, and primary or recurrent colorectal liver metastases, who were scheduled for local therapy based on contrast-enhanced CT. All patients had contrast-enhanced CT and liver contrast-enhanced MRI including diffusion-weighted imaging and gadoxetic acid as a contrast agent before undergoing local therapy. The primary outcome was change in the local clinical treatment plan (decided by the individual clinics) on the basis of liver contrast-enhanced MRI findings, analysed in the intention-to-image population. The minimal clinically important difference in the proportion of patients who would have change in their local treatment plan due to an additional liver contrast-enhanced MRI was 10%. This study is closed and registered in the Netherlands Trial Register, NL8039. FINDINGS: Between Dec 17, 2019, and July 31, 2021, 325 patients with colorectal liver metastases were assessed for eligibility. 298 patients were enrolled and included in the intention-to-treat population, including 177 males (59%) and 121 females (41%) with planned local therapy based on contrast-enhanced CT. A change in the local treatment plan based on liver contrast-enhanced MRI findings was observed in 92 (31%; 95% CI 26-36) of 298 patients. Changes were made for 40 patients (13%) requiring more extensive local therapy, 11 patients (4%) requiring less extensive local therapy, and 34 patients (11%) in whom the indication for curative-intent local therapy was revoked, including 26 patients (9%) with too extensive disease and eight patients (3%) with benign lesions on liver contrast-enhanced MRI (confirmed by a median follow-up of 21·0 months [IQR 17·5-24·0]). INTERPRETATION: Liver contrast-enhanced MRI should be considered in all patients scheduled for local treatment for colorectal liver metastases on the basis of contrast-enhanced CT imaging. FUNDING: The Dutch Cancer Society and Bayer AG - Pharmaceuticals.

Outcomes and potential impact of a virtual hands-on training program on MRI staging confidence and performance in rectal cancer.

OBJECTIVES: To explore the potential impact of a dedicated virtual training course on MRI staging confidence and performance in rectal cancer. METHODS: Forty-two radiologists completed a stepwise virtual training course on rectal cancer MRI staging composed of a pre-course (baseline) test with 7 test cases (5 staging, 2 restaging), a 1-day online workshop, 1 month of individual case readings (n = 70 cases with online feedback), a live online feedback session supervised by two expert faculty members, and a post-course test. The ESGAR structured reporting templates for (re)staging were used throughout the course. Results of the pre-course and post-course test were compared in terms of group interobserver agreement (Krippendorf's alpha), staging confidence (perceived staging difficulty), and diagnostic accuracy (using an expert reference standard). RESULTS: Though results were largely not statistically significant, the majority of staging variables showed a mild increase in diagnostic accuracy after the course, ranging between + 2% and + 17%. A similar trend was observed for IOA which improved for nearly all variables when comparing the pre- and post-course. There was a significant decrease in the perceived difficulty level (p = 0.03), indicating an improved diagnostic confidence after completion of the course. CONCLUSIONS: Though exploratory in nature, our study results suggest that use of a dedicated virtual training course and web platform has potential to enhance staging performance, confidence, and interobserver agreement to assess rectal cancer on MRI virtual training and could thus be a good alternative (or addition) to in-person training. CLINICAL RELEVANCE STATEMENT: Rectal cancer MRI reporting quality is highly dependent on radiologists' expertise, stressing the need for dedicated training/teaching. This study shows promising results for a virtual web-based training program, which could be a good alternative (or addition) to in-person training. KEY POINTS: • Rectal cancer MRI reporting quality is highly dependent on radiologists' expertise, stressing the need for dedicated training and teaching. • Using a dedicated virtual training course and web-based platform, encouraging first results were achieved to improve staging accuracy, diagnostic confidence, and interobserver agreement. • These exploratory results suggest that virtual training could thus be a good alternative (or addition) to in-person training.

An International Expert-Based Consensus on the Definition of a Clinical Near-Complete Response After Neoadjuvant (Chemo)radiotherapy for Rectal Cancer.

BACKGROUND: A variety of definitions for a clinical near-complete response after neoadjuvant (chemo) radiotherapy for rectal cancer are currently used. This variety leads to inconsistency in clinical practice, long-term outcome, and trial enrollment. OBJECTIVE: The aim of this study was to reach expert-based consensus on the definition of a clinical near-complete response after (chemo) radiotherapy. DESIGN: A modified Delphi process, including a systematic review, 3 surveys, and 2 meetings, was performed with an international expert panel consisting of 7 surgeons and 4 radiologists. The surveys consisted of individual features, statements, and feature combinations (endoscopy, T2-weighted MRI, and diffusion-weighted MRI). SETTING: The modified Delphi process was performed in an online setting; all 3 surveys were completed online by the expert panel, and both meetings were hosted online. MAIN OUTCOME MEASURES: The main outcome was to reach consensus (80% or more agreement). RESULTS: The expert panel reached consensus on a 3-tier categorization of the near-complete response category based on the likelihood of the response to evolve into a clinical complete response after a longer waiting interval. The panelists agreed that a near-complete response is a temporary entity only to be used in the first 6 months after (chemo)radiotherapy. Furthermore, consensus was reached that the lymph node status should be considered when deciding on a near-complete response and that biopsies are not always needed when a near-complete response is found. No consensus was reached on whether primary staging characteristics have to be taken into account when deciding on a near-complete response. LIMITATIONS: This 3-tier subcategorization is expert-based; therefore, there is no supporting evidence for this subcategorization. Also, it is unclear whether this subcategorization can be generalized into clinical practice. CONCLUSIONS: Consensus was reached on the use of a 3-tier categorization of a near-complete response, which can be helpful in daily practice as guidance for treatment and to inform patients with a near-complete response on the likelihood of successful organ preservation. See Video Abstract. UN CONSENSO INTERNACIONAL BASADO EN EXPERTOS ACERCA DE LA DEFINICIN DE UNA RESPUESTA CLNICA CASI COMPLETA DESPUS DE QUIMIORADIOTERAPIA NEOADYUVANTE CONTRA EL CNCER DE RECTO: ANTECEDENTES:Actualmente, se utilizan una variedad de definiciones para una respuesta clínica casi completa después de quimioradioterapia neoadyuvante contra el cáncer de recto. Esta variedad resulta en inconsistencia en la práctica clínica, los resultados a largo plazo y la inscripción en ensayos.OBJETIVO:El objetivo de este estudio fue llegar a un consenso de expertos sobre la definición de una respuesta clínica casi completa después de quimioradioterapia.DISEÑO:Se realizó un proceso Delphi modificado que incluyó una revisión sistemática, 3 encuestas y 2 reuniones con un panel internacional de expertos compuesto por siete cirujanos y 4 radiólogos. Las encuestas consistieron en características individuales, declaraciones y combinaciones de características (endoscopía, T2W-MRI y DWI).AJUSTE:El proceso Delphi modificado se realizó en un entorno en línea; el panel de expertos completó las tres encuestas en línea y ambas reuniones se realizaron en línea.PRINCIPALES MEDIDAS DE RESULTADO:El resultado principal fue llegar a un consenso (≥80% de acuerdo).RESULTADOS:El panel de expertos llegó a un consenso sobre una categorización de tres niveles de la categoría de respuesta casi completa basada en la probabilidad de que la respuesta evolucione hacia una respuesta clínica completa después de un intervalo de espera más largo. Los panelistas coincidieron en que una respuesta casi completa es una entidad temporal que sólo debe utilizarse en los primeros 6 meses después de la quimioradioterapia. Además, se llegó a un consenso en que se debe considerar el estado de los nódulos linfáticos al decidir sobre una respuesta casi completa y que no siempre se necesitan biopsias cuando se encuentra una respuesta casi completa. No se llegó a un consenso sobre si se deben tener en cuenta las características primarias de estadificación al decidir una respuesta casi completa.LIMITACIONES:Esta subcategorización de 3 niveles está basada en expertos; por lo tanto, no hay evidencia que respalde esta subcategorización. Además, no está claro si esta subcategorización puede generalizarse a la práctica clínica.CONCLUSIONES:Se alcanzó consenso sobre el uso de una categorización de 3 niveles de una respuesta casi completa que puede ser útil en la práctica diaria como guía para el tratamiento y para informar a los pacientes con una respuesta casi completa sobre la probabilidad de una preservación exitosa del órgano. (Traducción - Dr. Aurian Garcia Gonzalez).

Whole-body MRI with diffusion-weighted imaging as an adjunct to18 F-fluorodeoxyglucose positron emission tomography and CT in patients with suspected recurrent colorectal cancer.

AIM: The aim was to explore how findings of whole-body MRI including diffusion-weighted imaging (DW-MRI) compared to the routine diagnostic workup with CT and/or 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT in patients with suspected recurrent colorectal cancer (CRC). METHOD: This was an exploratory retrospective analysis of 55 patients with a clinical suspicion of recurrent CRC who underwent DW-MRI following CT and/or FDG-PET/CT. Two readers in consensus interpreted all clinical imaging reports and converted each described lesion into a confidence score (1 = definitely benign to 5 = definitely malignant). DW-MRI findings were compared to the most recent previous CT or PET/CT. Any discrepant or additional DW-MRI findings were documented and compared with histology and/or clinical follow-up (if available). RESULTS: Whole-body MRI including diffusion-weighted imaging (DW-MRI) resulted in discrepant/additional findings in 26/55 (47%) cases; 23/37 (62%) compared to previous CT and 3/18 (17%) compared to previous PET/CT. These included 10 cases where DW-MRI converted previously inconclusive CT (n = 8) or PET/CT (n = 2) findings into a conclusive diagnosis, one where it contradicted a previous CT diagnosis of recurrence, five where DW-MRI diagnosed recurrent disease not previously reported on CT and 10 cases where DW-MRI detected additional lesions compared to CT (n = 9) or PET/CT (n = 1). Eighty-eight per cent of cases with discrepant/additional findings concerned patients with recurrent/metachronous peritoneal metastases. In total, DW-MRI resulted in 42 discrepant/additional lesions; the DW-MRI diagnosis was correct in 76% of these lesions and incorrect (false positive) in 7%. In the remaining 17%, no standard of reference was available. CONCLUSIONS: This explorative study suggests that DW-MRI may be of added value to patients with a clinical suspicion for recurrent CRC, in particular to identify patients with peritoneal metastases. DW-MRI mainly has potential as a 'problem-solver' in patients with inconclusive or negative findings on previous imaging (in particular CT) and to detect additional disease sites in patients already diagnosed with recurrent disease.

Comparison of MRI response evaluation methods in rectal cancer: a multicentre and multireader validation study.

OBJECTIVES: To compare four previously published methods for rectal tumor response evaluation after chemoradiotherapy on MRI. METHODS: Twenty-two radiologists (5 rectal MRI experts, 17 general/abdominal radiologists) retrospectively reviewed the post-chemoradiotherapy MRIs of 90 patients, scanned at 10 centers (with non-standardized protocols). They applied four response methods; two based on T2W-MRI only (MRI tumor regression grade (mrTRG); split-scar sign), and two based on T2W-MRI+DWI (modified-mrTRG; DWI-patterns). Image quality was graded using a 0-6-point score (including slice thickness and in-plane resolution; sequence angulation; DWI b-values, signal-to-noise, and artefacts); scores < 4 were classified below average. Mixed model linear regression was used to calculate average sensitivity/specificity/accuracy to predict a complete response (versus residual tumor) and assess the impact of reader experience and image quality. Group interobserver agreement (IOA) was calculated using Krippendorff's alpha. Readers were asked to indicate their preferred scoring method(s). RESULTS: Average sensitivity/specificity/accuracy was 57%/64%/62% (mrTRG), 36%/79%/66% (split-scar), 40%/79%/67% (modified-mrTRG), and 37%/82%/68% (DWI-patterns); mrTRG showed higher sensitivity but lower specificity and accuracy (p < 0.001) compared to the other methods. IOA was lower for the split scar method (0.18 vs. 0.39-0.43). Higher reader experience had a significant positive effect on diagnostic performance and IOA (except for the split scar sign); below-average imaging quality had a significant negative effect on diagnostic performance. DWI pattern was selected as the preferred method by 73% of readers. CONCLUSIONS: Methods incorporating DWI showed the most favorable results when combining diagnostic performance, IOA, and reader preference. Reader experience and image quality clearly impacted diagnostic performance emphasizing the need for state-of-the-art imaging and dedicated radiologist training. KEY POINTS: • In a multireader study comparing 4 MRI methods for rectal tumor response evaluation, those incorporating DWI showed the best results when combining diagnostic performance, IOA, and reader preference. • The most preferred method (by 73% of readers) was the "DWI patterns" approach with an accuracy of 68%, high specificity of 82%, and group IOA of 0.43. • Reader experience level and MRI quality had an evident effect on diagnostic performance and IOA.

Independent validation of CT radiomics models in colorectal liver metastases: predicting local tumour progression after ablation.

OBJECTIVES: Independent internal and external validation of three previously published CT-based radiomics models to predict local tumor progression (LTP) after thermal ablation of colorectal liver metastases (CRLM). MATERIALS AND METHODS: Patients with CRLM treated with thermal ablation were collected from two institutions to collect a new independent internal and external validation cohort. Ablation zones (AZ) were delineated on portal venous phase CT 2-8 weeks post-ablation. Radiomics features were extracted from the AZ and a 10 mm peri-ablational rim (PAR) of liver parenchyma around the AZ. Three previously published prediction models (clinical, radiomics, combined) were tested without retraining. LTP was defined as new tumor foci appearing next to the AZ up to 24 months post-ablation. RESULTS: The internal cohort included 39 patients with 68 CRLM and the external cohort 52 patients with 78 CRLM. 34/146 CRLM developed LTP after a median follow-up of 24 months (range 5-139). The median time to LTP was 8 months (range 2-22). The combined clinical-radiomics model yielded a c-statistic of 0.47 (95%CI 0.30-0.64) in the internal cohort and 0.50 (95%CI 0.38-0.62) in the external cohort, compared to 0.78 (95%CI 0.65-0.87) in the previously published original cohort. The radiomics model yielded c-statistics of 0.46 (95%CI 0.29-0.63) and 0.39 (95%CI 0.28-0.52), and the clinical model 0.51 (95%CI 0.34-0.68) and 0.51 (95%CI 0.39-0.63) in the internal and external cohort, respectively. CONCLUSION: The previously published results for prediction of LTP after thermal ablation of CRLM using clinical and radiomics models were not reproducible in independent internal and external validation. CLINICAL RELEVANCE STATEMENT: Local tumour progression after thermal ablation of CRLM cannot yet be predicted with the use of CT radiomics of the ablation zone and peri-ablational rim. These results underline the importance of validation of radiomics results to test for reproducibility in independent cohorts. KEY POINTS: • Previous research suggests CT radiomics models have the potential to predict local tumour progression after thermal ablation in colorectal liver metastases, but independent validation is lacking. • In internal and external validation, the previously published models were not able to predict local tumour progression after ablation. • Radiomics prediction models should be investigated in independent validation cohorts to check for reproducibility.

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.

Sense and nonsense of yT-staging on MRI after chemoradiotherapy in rectal cancer.

AIM: The aim of this work was to investigate the value of rectal cancer T-staging on MRI after chemoradiotherapy (ymrT-staging) in relation to the degree of fibrotic transformation of the tumour bed as assessed using the pathological tumour regression grade (pTRG) of Mandard as a standard of reference. METHOD: Twenty two radiologists, including five rectal MRI experts and 17 'nonexperts' (general/abdominal radiologists), evaluated the ymrT stage on the restaging MRIs of 90 rectal cancer patients after chemoradiotherapy. The ymrT stage was compared with the final ypT stage at histopathology; the percentages of correct staging (ymrT = ypT), understaging (ymrT < ypT) and overstaging (ymrT > ypT) were calculated and compared between patients with predominant tumour at histopathology (pTRG4-5) and patients with predominant fibrosis (pTRG1-3). Interobserver agreement (IOA) was computed using Krippendorff's alpha. RESULTS: Average ymrT/ypT stage concordance was 48% for the experts and 43% for the nonexperts; ymrT/ypT stage concordance was significantly higher in the pTRG4-5 subgroup (58% vs. 41% for the pTRG1-3 group; p = 0.01), with the best results for the MRI experts. Overstaging was the main source of error, especially in the pTRG1-3 subgroup (average overstaging rate 38%-44% vs. 13%-55% in the pTRG4-5 subgroup). IOA was higher for the expert versus nonexpert readers (α = 0.67 vs. α = 0.39). CONCLUSIONS: ymrT-staging is moderately accurate; accuracy is higher in poorly responding patients with predominant tumour but low in good responders with predominant fibrosis, resulting in significant overstaging. Radiologists should shift their focus from ymrT-staging to detecting gross residual (and progressive) disease, and identifying potential candidates for organ preservation who would benefit from further clinical and endoscopic evaluation to guide final treatment planning.

CT radiomics models are unable to predict new liver metastasis after successful thermal ablation of colorectal liver metastases.

BACKGROUND: Patients with colorectal liver metastases (CRLM) who undergo thermal ablation are at risk of developing new CRLM after ablation. Identification of these patients might enable individualized treatment. PURPOSE: To investigate whether an existing machine-learning model with radiomics features based on pre-ablation computed tomography (CT) images of patients with colorectal cancer can predict development of new CRLM. MATERIAL AND METHODS: In total, 94 patients with CRLM who were treated with thermal ablation were analyzed. Radiomics features were extracted from the healthy liver parenchyma of CT images in the portal venous phase, before thermal ablation. First, a previously developed radiomics model (Original model) was applied to the entire cohort to predict new CRLM after 6 and 24 months of follow-up. Next, new machine-learning models were developed (Radiomics, Clinical, and Combined), based on radiomics features, clinical features, or a combination of both. RESULTS: The external validation of the Original model reached an area under the curve (AUC) of 0.57 (95% confidence interval [CI]=0.56-0.58) and 0.52 (95% CI=0.51-0.53) for 6 and 24 months of follow-up. The new predictive radiomics models yielded a higher performance at 6 months compared to 24 months. For the prediction of CRLM at 6 months, the Combined model had slightly better performance (AUC=0.60; 95% CI=0.59-0.61) compared to the Radiomics and Clinical models (AUC=0.55-0.57), while all three models had a low performance for the prediction at 24 months (AUC=0.52-0.53). CONCLUSION: Both the Original and newly developed radiomics models were unable to predict new CLRM based on healthy liver parenchyma in patients who will undergo ablation for CRLM.

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

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

CT-based radiomics to distinguish progressive from stable neuroendocrine liver metastases treated with somatostatin analogues: an explorative study.

BACKGROUND: Accurate response evaluation in patients with neuroendocrine liver metastases (NELM) remains a challenge. Radiomics has shown promising results regarding response assessment. PURPOSE: To differentiate progressive (PD) from stable disease (SD) with radiomics in patients with NELM undergoing somatostatin analogue (SSA) treatment. MATERIAL AND METHODS: A total of 46 patients with histologically confirmed gastroenteropancreatic neuroendocrine tumors (GEP-NET) with ≥1 NELM and ≥2 computed tomography (CT) scans were included. Response was assessed with Response Evaluation Criteria in Solid Tumors (RECIST1.1). Hepatic target lesions were manually delineated and analyzed with radiomics. Radiomics features were extracted from each NELM on both arterial-phase (AP) and portal-venous-phase (PVP) CT. Multiple instance learning with regularized logistic regression via LASSO penalization (with threefold cross-validation) was used to classify response. Three models were computed: (i) AP model; (ii) PVP model; and (iii) AP + PVP model for a lesion-based and patient-based outcome. Next, clinical features were added to each model. RESULTS: In total, 19 (40%) patients had PD. Median follow-up was 13 months (range 1-50 months). Radiomics models could not accurately classify response (area under the curve 0.44-0.60). Adding clinical variables to the radiomics models did not significantly improve the performance of any model. CONCLUSION: Radiomics features were not able to accurately classify response of NELM on surveillance CT scans during SSA treatment.

Defining near-complete response following (chemo)radiotherapy for rectal cancer: systematic review.

BACKGROUND: A uniform definition of a clinical near-complete response (near-CR) after neoadjuvant (chemo)radiotherapy for rectal cancer is lacking. A clear definition is necessary for uniformity in clinical practice and trial enrolment for organ-preserving treatments. This review aimed to provide an overview of the terminology, criteria, and features used in the literature to define a near-CR. METHODS: A systematic review was performed based on the PRISMA statement. PubMed and Embase were searched up to May 2021 to identify the terminology, criteria, and features used to define a near-CR after (chemo)radiotherapy for rectal cancer. Studies with no clear cut-off point between a cCR and near-CR, studies using Response Evaluation Criteria In Solid Tumours, and studies including only complete responders were excluded. RESULTS: A total of 1876 articles were found, of which 23 were included. Patients were managed by watchful waiting and/or additional local treatment in 11 and 17 of 23 studies respectively. Response evaluation included digital rectal examination (DRE) and/or endoscopy with MRI in 18 studies. The majority of studies used the term 'near-complete response'. In most studies, minor irregularities or a smooth induration with DRE and a small flat ulcer on endoscopy were considered to indicate a near-CR. On MRI, five studies used features (obvious downstaging with or without heterogeneous/irregular fibrosis on T2-weighted MRI or small spot of high signal on diffusion-weighted imaging), five studies used TNM criteria (ycT2), and four used magnetic resonance tumour regression grade (mrTRG) (mrTRG1-2/mrTRG2) to describe a near-CR. CONCLUSION: The terminology, criteria, and features used to describe a near-CR vary substantially, which can partly be explained by the different treatment strategies patients are selected for (watchful waiting or additional local treatment). A reproducible definition of near-CR is required.

GEP-NET radiomics: a systematic review and radiomics quality score assessment.

OBJECTIVE: The number of radiomics studies in gastroenteropancreatic neuroendocrine tumours (GEP-NETs) is rapidly increasing. This systematic review aims to provide an overview of the available evidence of radiomics for clinical outcome measures in GEP-NETs, to understand which applications hold the most promise and which areas lack evidence. METHODS: PubMed, Embase, and Wiley/Cochrane Library databases were searched and a forward and backward reference check of the identified studies was executed. Inclusion criteria were (1) patients with GEP-NETs and (2) radiomics analysis on CT, MRI or PET. Two reviewers independently agreed on eligibility and assessed methodological quality with the radiomics quality score (RQS) and extracted outcome data. RESULTS: In total, 1364 unique studies were identified and 45 were included for analysis. Most studies focused on GEP-NET grade and differential diagnosis of GEP-NETs from other neoplasms, while only a minority analysed treatment response or long-term outcomes. Several studies were able to predict tumour grade or to differentiate GEP-NETs from other lesions with a good performance (AUCs 0.74-0.96 and AUCs 0.80-0.99, respectively). Only one study developed a model to predict recurrence in pancreas NETs (AUC 0.77). The included studies reached a mean RQS of 18%. CONCLUSION: Although radiomics for GEP-NETs is still a relatively new area, some promising models have been developed. Future research should focus on developing robust models for clinically relevant aims such as prediction of response or long-term outcome in GEP-NET, since evidence for these aims is still scarce. KEY POINTS: • The majority of radiomics studies in gastroenteropancreatic neuroendocrine tumours is of low quality. • Most evidence for radiomics is available for the identification of tumour grade or differentiation of gastroenteropancreatic neuroendocrine tumours from other neoplasms. • Radiomics for the prediction of response or long-term outcome in gastroenteropancreatic neuroendocrine tumours warrants further research.

Current controversies in TNM for the radiological staging of rectal cancer and how to deal with them: results of a global online survey and multidisciplinary expert consensus.

OBJECTIVES: To identify the main problem areas in the applicability of the current TNM staging system (8th ed.) for the radiological staging and reporting of rectal cancer and provide practice recommendations on how to handle them. METHODS: A global case-based online survey was conducted including 41 image-based rectal cancer cases focusing on various items included in the TNM system. Cases reaching < 80% agreement among survey respondents were identified as problem areas and discussed among an international expert panel, including 5 radiologists, 6 colorectal surgeons, 4 radiation oncologists, and 3 pathologists. RESULTS: Three hundred twenty-one respondents (from 32 countries) completed the survey. Sixteen problem areas were identified, related to cT staging in low-rectal cancers, definitions for cT4b and cM1a disease, definitions for mesorectal fascia (MRF) involvement, evaluation of lymph nodes versus tumor deposits, and staging of lateral lymph nodes. The expert panel recommended strategies on how to handle these, including advice on cT-stage categorization in case of involvement of different layers of the anal canal, specifications on which structures to include in the definition of cT4b disease, how to define MRF involvement by the primary tumor and other tumor-bearing structures, how to differentiate and report lymph nodes and tumor deposits on MRI, and how to anatomically localize and stage lateral lymph nodes. CONCLUSIONS: The recommendations derived from this global survey and expert panel discussion may serve as a practice guide and support tool for radiologists (and other clinicians) involved in the staging of rectal cancer and may contribute to improved consistency in radiological staging and reporting. KEY POINTS: • Via a case-based online survey (incl. 321 respondents from 32 countries), we identified 16 problem areas related to the applicability of the TNM staging system for the radiological staging and reporting of rectal cancer. • A multidisciplinary panel of experts recommended strategies on how to handle these problem areas, including advice on cT-stage categorization in case of involvement of different layers of the anal canal, specifications on which structures to include in the definition of cT4b disease, how to define mesorectal fascia involvement by the primary tumor and other tumor-bearing structures, how to differentiate and report lymph nodes and tumor deposits on MRI, and how to anatomically localize and stage lateral lymph nodes. • These recommendations may serve as a practice guide and support tool for radiologists (and other clinicians) involved in the staging of rectal cancer and may contribute to improved consistency in radiological staging and reporting.

The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation.

BACKGROUND: Accurate response evaluation is necessary to select complete responders (CRs) for a watch-and-wait approach. Deep learning may aid in this process, but so far has never been evaluated for this purpose. The aim was to evaluate the accuracy to assess response with deep learning methods based on endoscopic images in rectal cancer patients after neoadjuvant therapy. METHODS: Rectal cancer patients diagnosed between January 2012 and December 2015 and treated with neoadjuvant (chemo)radiotherapy were retrospectively selected from a single institute. All patients underwent flexible endoscopy for response evaluation. Diagnostic performance (accuracy, area under the receiver operator characteristics curve (AUC), positive- and negative predictive values, sensitivities and specificities) of different open accessible deep learning networks was calculated. Reference standard was histology after surgery, or long-term outcome (>2 years of follow-up) in a watch-and-wait policy. RESULTS: 226 patients were included for the study (117(52%) were non-CRs; 109(48%) were CRs). The accuracy, AUC, positive- and negative predictive values, sensitivity and specificity of the different models varied from 0.67-0.75%, 0.76-0.83%, 67-74%, 70-78%, 68-79% to 66-75%, respectively. Overall, EfficientNet-B2 was the most successful model with the highest diagnostic performance. CONCLUSIONS: This pilot study shows that deep learning has a modest accuracy (AUCs 0.76-0.83). This is not accurate enough for clinical decision making, and lower than what is generally reported by experienced endoscopists. Deep learning models can however be further improved and may become useful to assist endoscopists in evaluating the response. More well-designed prospective studies are required.

Predictive Value of Endoscopic Features for a Complete Response After Chemoradiotherapy for Rectal Cancer.

OBJECTIVE AND BACKGROUND: Watch-and-wait approach in rectal cancer relies on the identification of a clinical complete response (CR) after neoadjuvant (chemo)radiotherapy. This is mainly performed by rectal examination, magnetic resonance imaging, and endoscopy. Endoscopy has been less well studied, and the objective of the study is to assess the diagnostic value of endoscopy and the predictive value of endoscopic features for the identification of CR. PATIENTS AND METHODS: A total of 161 patients with primary rectal cancer undergoing flexible sigmoidoscopy for response assessment after neoadjuvant (chemo)radiotherapy between January 2012 and December 2015 at a single institution were evaluated retrospectively. Three independent readers scored endoscopic features and a confidence level score for a CR. Diagnostic performance of endoscopy and positive predictive value (PPV) of endoscopic features for a CR were calculated. If available, biopsy results were revealed to the reader and a change in confidence level was noted. Reference standard was histology after surgery, or long-term outcome in a watch-and-wait policy. RESULTS: Median time to endoscopy was 9 (interquartile range 8-12) weeks. Area under the receiver operator characteristic curve, sensitivity, specificity, PPV, and negative predictive value for a CR were 0.80 to 0.84, 72% to 94%, 61% to 85%, 63% to 78% and 80% to 89%, respectively. A flat scar was the most predictive feature of a CR (PPV 70%-80%). The PPV of small flat ulcers and large flat ulcers were 40% to 50% and 29% to 33%, respectively. The addition of biopsy results led to a significant change in confidence level score in 4% to 13% of patients. CONCLUSIONS: More than 70% of the patients with a luminal CR after neoadjuvant treatment for rectal cancer can be identified by endoscopy at ±9 weeks. Together with findings on digital rectal examination (DRE) and magnetic resonance imaging, specific endoscopic features can be used to select patients for an extended observation period to select for organ preservation.

Clinical response assessment on DW-MRI compared with FDG-PET/CT after neoadjuvant chemoradiotherapy in patients with oesophageal cancer.

PURPOSE: In about 30% of patients treated with neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection for locally advanced oesophageal cancer no vital tumour is found in the resection specimen. Accurate clinical response assessment is critical if deferral from surgery is considered in complete responders. Our study aimed to compare the performance of MRI and of FDG-PET/CT for the detection of residual disease after nCRT. METHODS: Patients with oesophageal cancer eligible for nCRT and oesophagectomy were prospectively included. All patients underwent FDG-PET/CT and MRI before and between 6 and 8 weeks after nCRT. Two radiologists scored the MRI scans, and two nuclear medicine physicians scored the FDG-PET/CT scans using a 5-point score for residual disease. Histopathology after oesophagectomy represented the reference standard. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated for detection of residual tumour (ypT+), residual nodal disease (ypN+), and any residual disease (ypT+Nx/ypT0N+). RESULTS: Seven out of 33 (21%) patients had a pathological complete response. The AUCs for individual readers to detect ypT+ were 0.71/0.70 on diffusion-weighted (DW)-MRI and 0.54/0.57 on FDG-PET/CT, and to detect ypN+ were 0.89/0.81 on DW-MRI and 0.75/0.71 on FDG-PET/CT. The AUCs/sensitivities/specificities for the individual readers to detect any residual disease were 0.74/92%/57% and 0.70/96%/43% on MRI; these were 0.49/69%/29% and 0.60/69%/43% on FDG-PET/CT, respectively. CONCLUSION: MRI reached higher diagnostic accuracies than FDG-PET/CT for the detection of residual tumour in oesophageal cancer patients at 6 to 8 weeks after nCRT.

Blood Molecular Genomic Analysis Predicts the Disease Course of Gastroenteropancreatic Neuroendocrine Tumor Patients: A Validation Study of the Predictive Value of the NETest®.

Reliable prediction of disease status is a major challenge in managing gastroenteropancreatic neuroendocrine tumors (GEP-NETs). The aim of the study was to validate the NETest®, a blood molecular genomic analysis, for predicting the course of disease in individual patients compared to chromogranin A (CgA). NETest® score (normal ≤20%) and CgA level (normal <100 µg/L) were measured in 152 GEP-NETs. The median follow-up was 36 (4-56) months. Progression-free survival was blindly assessed (Response Evaluation Criteria in Solid Tumors [RECIST] version 1.1). Optimal cutoffs (area under the receiver operating characteristic curve [AUC]), odds ratios, as well as negative and positive predictive values (NPVs/PPVs) were calculated for predicting stable disease (SD) and progressive disease (PD). Of the 152 GEP-NETs, 86% were NETest®-positive and 52% CgA-positive. -NETest® AUC was 0.78 versus CgA 0.73 (p = ns). The optimal cutoffs for predicting SD/PD were 33% for the NETest® and 140 µg/L for CgA. Multivariate analyses identified NETest® as the strongest predictor for PD (odds ratio: 5.7 [score: 34-79%]; 12.6 [score: ≥80%]) compared to CgA (odds ratio: 3.0), tumor grade (odds ratio: 3.1), or liver metastasis (odds ratio: 7.7). The NETest® NPV for SD was 87% at 12 months. The PPV for PD was 47 and 64% (scores 34-79% and ≥80%, respectively). NETest® metrics were comparable in the watchful waiting, treatment, and no evidence of disease (NED) subgroups. For CgA (>140 ng/mL), NPV and PPV were 83 and 52%. CgA could not predict PD in the watchful waiting or NED subgroups. The NETest® reliably predicted SD and was the strongest predictor of PD. CgA had lower utility. The -NETest® anticipates RECIST-defined disease status up to 1 year before imaging alterations are apparent.

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.

The evaluation of follow-up strategies of watch-and-wait patients with a complete response after neoadjuvant therapy in rectal cancer.

AIM: Many of the current follow-up schedules in a watch-and-wait approach include very frequent MRI and endoscopy examinations to ensure early detection of local regrowth (LR). The aim of this study was to analyse the occurrence and detection of LR in a watch-and-wait cohort and to suggest a more efficient follow-up schedule. METHOD: Rectal cancer patients with a clinical complete response after neoadjuvant therapy were prospectively and retrospectively included in a multicentre watch-and-wait registry between 2004 and 2018, with the current follow-up schedule with 3-monthly endoscopy and MRI in the first year and 6 monthly thereafter. A theoretical comparison was constructed for the detection of LR in the current follow-up schedule against four other hypothetical schedules. RESULTS: In all, 50/304 (16%) of patients developed a LR. The majority (98%) were detected at ≤2 years, located in the lumen (94%) and were visible on endoscopy (88%). The theoretical comparison of the different hypothetical schedules suggests that the optimal follow-up schedule should focus on the first 2 years with 3-monthly endoscopy and 3-6 monthly MRI. Longer intervals in the first 2 years will cause delays in diagnosis of LR ranging from 0 to 5 months. After 2 years, increasing the interval from 6 to 12 months did not cause important delays. CONCLUSION: The optimal follow-up schedule for a watch-and-wait policy in patients with a clinical complete response after chemoradiation for rectal cancer should include frequent endoscopy and to a lesser degree MRI in the first 2 years. Longer intervals, up to 12 months, can be considered after 2 years.