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

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

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

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

Funding Information: This study has received funding from the Dutch Cancer Society (project number 10138). Publisher Copyright: © 2023, The Author(s).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.Peer reviewe

Prediction and diagnosis of colorectal anastomotic leakage:A systematic review of literature

Although many studies have focused on the preoperative risk factors of anastomotic leakage after colorectal surgery (CAL), postoperative delay in diagnosis is common and harmful. This review provides a systematic overview of all available literature on diagnostic tools used for CAL. A systematic search of literature was undertaken using Medline, Embase, Cochrane and Web-of-Science libraries. Articles were selected when a diagnostic or prediction tool for CAL was described and tested. Two reviewers separately assessed the eligibility and level of evidence of the papers. Sixty-nine articles were selected (clinical methods: 11, laboratory tests: 12, drain fluid analysis: 12, intraoperative techniques: 22, radiology: 16). Clinical scoring leads to early awareness of probability of CAL and reduces delay of diagnosis. C-reactive protein measurement at postoperative day 3-4 is helpful. CAL patients are characterized by elevated cytokine levels in drain fluid in the very early postoperative phase in CAL patients. Intraoperative testing using the air leak test allows intraoperative repair of the anastomosis. Routine contrast enema is not recommended. If CAL is clinically suspected, rectal contrast-computer tomography is recommended by a few studies. In many studies a "no-test" control group was lacking, furthermore no golden standard for CAL is available. These two factors contributed to a relatively low level of evidence in the majority of the papers. This paper provides a systematic overview of literature on the available tools for diagnosing CAL. The study shows that colorectal surgery patients could benefit from some diagnostic interventions that can easily be performed in daily postoperative care

MRI and diffusion-weighted MRI to diagnose a local tumour regrowth during long-term follow-up of rectal cancer patients treated with organ preservation after chemoradiotherapy

OBJECTIVES: To assess the value of MRI and diffusion-weighted imaging (DWI) for diagnosing local tumour regrowth during follow-up of organ preservation treatment after chemoradiotherapy for rectal cancer. METHODS: Seventy-two patients underwent organ preservation treatment (chemoradiotherapy + transanal endoscopic microsurgery or "wait-and-see") and were followed with MRI including DWI (1.5 T) every 3 -months during the first year and 6 months during following years. Two readers scored each MRI for local regrowth using a confidence level, first on standard MRI, then on standard MRI+DWI. Histology and clinical follow-up were the standard reference. Receiver operating characteristic curves were constructed and areas under the curve (AUC) and corresponding accuracy figures calculated on a per-scan basis. RESULTS: Four hundred and forty MRIs were assessed. Twelve patients developed local regrowth. AUC/sensitivity/specificity for standard MRI were 0.95/58 %/98 % (R1) and 0.96/58 % /100 % (R2). For standard MRI+DWI, these numbers were 0.86/75 %/97 % (R1) and 0.98/75 %/100 % (R2). After adding DWI, the number of equivocal scores decreased from 22 to 7 (R1) and from 40 to 20 (R2). CONCLUSIONS: Although there was no overall improvement in diagnostic performance in terms of AUC, adding DWI improved the sensitivity of MRI for diagnosing local tumour regrowth and lowered the rate of equivocal MRIs. KEY POINTS: * DWI improves sensitivity for detecting local tumour regrowth after organ preservation treatment. * In particular, DWI can aid in detecting small local recurrence. * DWI reduces the number of equivocal scores

Innovative drugs, chemicals, and enzymes within the animal production chain

Abstract The alarming number of recently reported human illnesses with bacterial infections resistant to multiple antibacterial agents has become a serious concern in recent years. This phenomenon is a core challenge for both the medical and animal health communities, since the use of antibiotics has formed the cornerstone of modern medicine for treating bacterial infections. The empirical benefits of using antibiotics to address animal health issues in animal agriculture (using therapeutic doses) and increasing the overall productivity of animals (using sub-therapeutic doses) are well established. The use of antibiotics to enhance profitability margins in the animal production industry is still practiced worldwide. Although many technical and economic reasons gave rise to these practices, the continued emergence of antimicrobial resistant bacteria is furthering the need to reduce the use of medically important antibiotics. This will require improving on-farm management and biosecurity practices, and the development of effective antibiotic alternatives that will reduce the dependence on antibiotics within the animal industry in the foreseeable future. A number of approaches are being closely scrutinized and optimized to achieve this goal, including the development of promising antibiotic alternatives to control bacterial virulence through quorum-sensing disruption, the use of synthetic polymers and nanoparticles, the exploitation of recombinant enzymes/proteins (such as glucose oxidases, alkaline phosphatases and proteases), and the use of phytochemicals. This review explores the most recent approaches within this context and provides a summary of practical mitigation strategies for the extensive use of antibiotics within the animal production chain in addition to several future challenges that need to be addressed

Diagnostic accuracy of CT for local staging of colon cancer:A nationwide study in the Netherlands

OBJECTIVE: To determine the accuracy of computed tomography (CT)-based staging in selecting high-risk colon cancer patients who would benefit from neoadjuvant chemotherapy while avoiding overtreatment. METHODS: Data of adult patients diagnosed with non-metastatic primary colon cancer in 2005-2020, who underwent surgical resection without neoadjuvant chemotherapy, were retrospectively collected from the Netherlands Cancer Registry. Agreement between clinical and pathological evaluation for each T and N stage was calculated. Sensitivity and specificity analyses were conducted to predict T3-T4 and N1-N2 stages, with histopathology as the reference standard. RESULTS: Data from 44,471 patients (median age, 71 years, 50% female) were evaluated. We included 38,915 patients with complete T stage and 39,565 patients with complete N stage for analyses. The overall clinical-pathological agreement for T stage was 59% and for N stage 57%. The sensitivity and specificity of CT to detect T3-T4 tumours were 80% (95% confidence interval (CI): 0.79, 0.80) and 76% (95% CI: 0.75, 0.77), respectively, with a positive predictive value (PPV) of 92% (95% CI: 0.92, 0.92). The sensitivity and specificity of CT to detect N1-N2 category were 62% (95% CI: 0.61, 0.63) and 70% (95% CI: 0.69, 0.71), respectively, with PPV 60% (95% CI: 0.59, 0.60). CONCLUSION: CT-based staging shows limited accuracy in selecting colon cancer patients who would benefit from neoadjuvant therapy without risking overtreatment. Detection of lymph node metastases with CT remains unreliable