Textural features based enhanced contrast CT images predicts prognosis to concurrent chemoradiotherapy in stage III esophageal squamous cell cancer

The gap before real clinical application of imaging-based machine-learning and radiomic models for chemoradiation outcome prediction in esophageal cancer: a systematic review and meta-analysis

BACKGROUND

Due to tumoral heterogeneity and the lack of robust biomarkers, the prediction of chemoradiotherapy response and prognosis in patients with esophageal cancer (EC) is challenging. The goal of this study was to assess the study quality and clinical value of machine learning and radiomic-based quantitative imaging studies for predicting the outcomes of EC patients after chemoradiotherapy.

MATERIALS AND METHODS

PubMed, Embase, and Cochrane were searched for eligible articles. The methodological quality and risk of bias were evaluated using the Radiomics Quality Score (RQS), Image Biomarkers Standardization Initiative (IBSI) Guideline, and Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement, as well as the modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. A meta-analysis of the evidence focusing on predicting chemoradiotherapy response and outcome in EC patients was implemented.

RESULTS

Forty-six studies were eligible for qualitative synthesis. The mean RQS score was 9.07, with an adherence rate of 42.52%. The adherence rates of the TRIPOD and IBSI were 61.70 and 43.17%, respectively. Ultimately, 24 studies were included in the meta-analysis, of which 16 studies had a pooled sensitivity, specificity, and area under the curve (AUC) of 0.83 (0.76-0.89), 0.83 (0.79-0.86), and 0.84 (0.81-0.87) in neoadjuvant chemoradiotherapy datasets, as well as 0.84 (0.75-0.93), 0.89 (0.83-0.93), and 0.93 (0.90-0.95) in definitive chemoradiotherapy datasets, respectively. Moreover, radiomics could distinguish patients from the low-risk and high-risk groups with different disease-free survival (DFS) (pooled hazard ratio: 3.43, 95% CI 2.39-4.92) and overall survival (pooled hazard ratio: 2.49, 95% CI 1.91-3.25). The results of subgroup and regression analyses showed that some of the heterogeneity was explained by the combination with clinical factors, sample size, and usage of the deep learning (DL) signature.

CONCLUSIONS

Noninvasive radiomics offers promising potential for optimizing treatment decision-making in EC patients. However, it is necessary to make scientific advancements in EC radiomics regarding reproducibility, clinical usefulness analysis, and open science categories. Improved model reporting of study objectives, blind assessment, and image processing steps are required to help promote real clinical applications of radiomics in EC research.

Prognostic value of fibroblast activation protein expressing tumor volume calculated from [68 Ga]Ga-FAPI PET/CT in patients with esophageal squamous cell carcinoma

BACKGROUND

This study aimed to investigate the prognostic value of semiquantitative parameters derived from [68 Ga]Ga-fibroblast activation protein inhibitor (FAPI) PET/CT for patients with esophageal squamous cell carcinoma (ESCC) treated with definitive chemoradiotherapy.

METHODS

We conducted a retrospective analysis on patients from a prospective parent study (NCT04416165). A total of 45 patients with locally advanced ESCC who underwent [68 Ga]Ga-FAPI from December 2019 to March 2021 were included. The maximum standard uptake value (SUVmax), gross tumor volume (GTV), and total lesion-FAPI (TL-FAPI) of the primary tumor were calculated from the corresponding PET/CT image. Unpaired parameters were compared using Student's t test or the Mann-Whitney U test. Paired parameters were compared using the paired t test or the Wilcoxon matched-pairs signed-rank test. Kaplan-Meier curves were generated to calculate progression-free survival (PFS) and overall survival (OS) rates, and Cox regression analysis was performed to determine which PET/CT parameters were prognostic factors for PFS and/or OS.

RESULTS

Thirty-four of the 45 patients met the criteria, and the median follow-up time was 24 months (16-29 months). SUVmax-FAPI, GTVFAPI, and TL-FAPI in patients with stage T4 tumors were significantly higher than those in patients with stage T2/T3 tumors (all P < 0.01). In the univariate Cox regression analysis, T stage, N stage, GTVFAPI, and TL-FAPI were associated with PFS, and T stage, GTVFAPI, and TL-FAPI were associated with OS. Upon multivariable analysis, GTVFAPI was an independent prognostic factor for both PFS (hazard ratio (HR), 5.76; 95% confidence interval (CI), 2.13-15.57, P = 0.001) and OS (HR, 4.96; 95% CI, 2.55-18.79, P = 0.001).

CONCLUSION

This pilot study revealed that [68 Ga]Ga-FAPI PET/CT may have prognostic value for patients with ESCC treated with definitive chemoradiotherapy. It may aid in personalized patient management by steering treatment modifications before therapy. Prospective studies with larger samples and longer observation periods are needed.

Methodological quality of machine learning-based quantitative imaging analysis studies in esophageal cancer: a systematic review of clinical outcome prediction after concurrent chemoradiotherapy

PURPOSE

Studies based on machine learning-based quantitative imaging techniques have gained much interest in cancer research. The aim of this review is to critically appraise the existing machine learning-based quantitative imaging analysis studies predicting outcomes of esophageal cancer after concurrent chemoradiotherapy in accordance with PRISMA guidelines.

METHODS

A systematic review was conducted in accordance with PRISMA guidelines. The citation search was performed via PubMed and Embase Ovid databases for literature published before April 2021. From each full-text article, study characteristics and model information were summarized. We proposed an appraisal matrix with 13 items to assess the methodological quality of each study based on recommended best-practices pertaining to quality.

RESULTS

Out of 244 identified records, 37 studies met the inclusion criteria. Study endpoints included prognosis, treatment response, and toxicity after concurrent chemoradiotherapy with reported discrimination metrics in validation datasets between 0.6 and 0.9, with wide variation in quality. A total of 30 studies published within the last 5 years were evaluated for methodological quality and we found 11 studies with at least 6 "good" item ratings.

CONCLUSION

A substantial number of studies lacked prospective registration, external validation, model calibration, and support for use in clinic. To further improve the predictive power of machine learning-based models and translate into real clinical applications in cancer research, appropriate methodologies, prospective registration, and multi-institution validation are recommended.

Addition of camrelizumab to docetaxel, cisplatin, and radiation therapy in patients with locally advanced esophageal squamous cell carcinoma: a phase 1b study

Patients with locally advanced esophageal squamous cell carcinoma (ESCC) show poor survival after concurrent chemoradiotherapy. This study investigated the safety and feasibility of combining concurrent chemoradiotherapy with the anti-PD-1 antibody camrelizumab as first-line treatment for these patients. In this phase 1b study (ClinicalTrials.gov NCT03671265), patients received concurrent chemotherapy (cisplatin [25 mg/m²] plus docetaxel [25 mg/m²] for 4 weeks) and radiotherapy (2.0 Gy/fraction, total 60 Gy) with camrelizumab (200 mg every 2 weeks for 32 weeks). Primary endpoints were safety and tolerability, and health-related quality of life. Secondary endpoints were radiological and pathological response rates, overall survival (OS), and progression-free survival (PFS). Candidate biomarkers in tumor and peripheral blood were monitored at baseline and after 40 Gy radiation. Twenty patients were enrolled. The most common treatment-related grade 3 adverse events included radiation esophagitis (20%) and esophageal fistula (10%). Serious treatment-related adverse events occurred in eight (40%) patients. No treatment-related deaths were reported. Health-related quality of life did not deteriorate. Thirteen (65%) patients had an objective response after 40 Gy radiation. At a median follow-up of 23.7 months (95% CI 21.9–24.5), OS and PFS time ranged from 8.2–28.5 and 4.0–28.5 months, respectively. The 12-month and 24-month OS rate was 85.0% and 69.6%; PFS rate was 80.0% and 65.0%. Tumor PD-L1 expression and CD11c⁺ dendritic cells and peripheral-blood IL-27, IL-15, Eotaxin-3, and IL-22 were associated with OS. First-line concurrent chemoradiotherapy plus camrelizumab had a manageable safety profile and promising antitumour efficacy for ESCC, and deserves further study.