CT reconstruction with thick slices not only underestimates lymph node size but also reduces data reproducibility in colorectal cancer

Imaging standardisation in metastatic colorectal cancer: A joint EORTC-ESOI-ESGAR expert consensus recommendation

BACKGROUND

Treatment monitoring in metastatic colorectal cancer (mCRC) relies on imaging to evaluate the tumour burden. Response Evaluation Criteria in Solid Tumors provide a framework on reporting and interpretation of imaging findings yet offer no guidance on a standardised imaging protocol tailored to patients with mCRC. Imaging protocol heterogeneity remains a challenge for the reproducibility of conventional imaging end-points and is an obstacle for research on novel imaging end-points.

PATIENTS AND METHODS

Acknowledging the recently highlighted potential of radiomics and artificial intelligence tools as decision support for patient care in mCRC, a multidisciplinary, international and expert panel of imaging specialists was formed to find consensus on mCRC imaging protocols using the Delphi method.

RESULTS

Under the guidance of the European Organisation for Research and Treatment of Cancer (EORTC) Imaging and Gastrointestinal Tract Cancer Groups, the European Society of Oncologic Imaging (ESOI) and the European Society of Gastrointestinal and Abdominal Radiology (ESGAR), the EORTC-ESOI-ESGAR core imaging protocol was identified.

CONCLUSION

This consensus protocol attempts to promote standardisation and to diminish variations in patient preparation, scan acquisition and scan reconstruction. We anticipate that this standardisation will increase reproducibility of radiomics and artificial intelligence studies and serve as a catalyst for future research on imaging end-points. For ongoing and future mCRC trials, we encourage principal investigators to support the dissemination of these imaging standards across recruiting centres.

Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

Approximately 25% of the patients with muscle-invasive bladder cancer (MIBC) who are clinically node negative have occult lymph node metastases at radical cystectomy (RC) and pelvic lymph node dissection. The aim of this study was to evaluate preoperative CT-based radiomics to differentiate between pN+ and pN0 disease in patients with clinical stage cT2-T4aN0-N1M0 MIBC. Patients with cT2-T4aN0-N1M0 MIBC, of whom preoperative CT scans and pathology reports were available, were included from the prospective, multicenter CirGuidance trial. After manual segmentation of the lymph nodes, 564 radiomics features were extracted. A combination of different machine-learning methods was used to develop various decision models to differentiate between patients with pN+ and pN0 disease. A total of 209 patients (159 pN0; 50 pN+) were included, with a total of 3153 segmented lymph nodes. None of the individual radiomics features showed significant differences between pN+ and pN0 disease, and none of the radiomics models performed substantially better than random guessing. Hence, CT-based radiomics does not contribute to differentiation between pN+ and pN0 disease in patients with cT2-T4aN0-N1M0 MIBC.

Optimal criteria for predicting lymph node metastasis in esophageal squamous cell carcinoma by anatomical location using preoperative computed tomography: a retrospective cohort study

PURPOSE

Predicting lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) is critical for selecting appropriate treatments despite the low accuracy of computed tomography (CT) for detecting LNM. Variation in potential nodal sizes among locations or patients' clinicopathological background factors may impact the diagnostic quality. This study explored the optimal criteria and diagnostic ability of CT by location.

METHODS

We retrospectively reviewed preoperative CT scans of 229 patients undergoing curative esophagectomy. We classified nodal stations into six groups: Cervical (C), Right-upper mediastinal (U_R), Left-upper mediastinal (U_L), Middle mediastinal (M), Lower mediastinal (L), and Abdominal (A). We then measured the short-axial diameter (SAD) of the largest lymph node in each area. We used receiver operating characteristics analyses to evaluate the CT diagnostic ability and determined the cut-off values for the SAD in all groups.

RESULTS

Optimal cut-offs were 6.5 mm (M), 6 mm (C, L, and A), and 5 mm (U_R and U_L). Diagnostic abilities differed among locations, and U_R had the highest sensitivity. A multivariate analysis showed poor differentiation to be an independent risk factor for a false-negative diagnosis (p = 0.044).

CONCLUSIONS

Optimal criteria and diagnostic abilities for predicting LNM in ESCC varied among locations, and poor differentiation might contribute to failure to detect LNM.