Quantitative RECIST derived from multiparametric MRI in evaluating response of esophageal squamous cell carcinoma to neoadjuvant therapy.

OBJECTIVE

To develop a quantitative Response Evaluation Criteria in Solid Tumors (qRECIST) for evaluating response to neoadjuvant therapy (nT) in ESCCs relying on multiparametric (mp) MRI.

METHODS

Patients with cT2-T4a/N0-N3/M0 ESCC undergoing pre-nT and post-nT esophageal mpMRI before radical resection were prospectively included. Images were reviewed by two experienced radiologists. qRECIST was redefined using four methods including conventional criterion (cRECIST) and three model-dependent RECIST relying on quantitative MRI measurements at pre-nT, post-nT, and delta pre-post nT, respectively. Pathological tumor regression grades (TRGs) were used as a reference standard. The rates of agreement between four qRECIST methods and TRGs were determined with a Cronbach's alpha test, area under the curve (AUC), and a diagnostic odds ratio meta-analysis.

RESULTS

Ninety-one patients were enrolled. All four methods revealed high inter-reader agreements between the two radiologists, with a Kappa coefficient of 0.96, 0.87, 0.88, and 0.97 for cRECIST, pre-nT RECIST, post-nT RECIST, and delta RECIST, respectively. Among them, delta RECIST achieved the highest overall agreement rate (67.0% [61/91]) with TRGs, followed by post-nT RECIST (63.8% [58/91]), cRECIST (61.5% [56/91]), and pre-nT RECIST (36.3% [33/91]). Especially, delta RECIST achieved the highest accuracy (97.8% [89/91]) in distinguishing responders from non-responders, with 97.3% (34/35) for responders and 98.2% (55/56) for non-responders. Post-nT RECIST achieved the highest accuracy (93.4% [85/91]) in distinguishing complete responders from non-pCRs, with 77.8% (11/18) for pCRs and 94.5% (69/73) for non-pCRs.

CONCLUSION

The qRECIST with mpMRI can assess treatment-induced changes and may be used for early prediction of response to nT in ESCC patients.

KEY POINTS

• Quantitative mpMRI can reliably assess tumor response, and delta RECIST model had the best performance in evaluating response to nT in ESCCs, with an AUC of 0.98, 0.95, 0.80, and 0.82 for predicting TRG0, TRG1, TRG2, and TRG3, respectively. • In distinguishing responders from non-responders, the rate of agreement between delta RECIST and pathology was 97.3% (34/35) for responders and 98.2% (55/56) for non-responders, resulting in an overall agreement rate of 97.8% (89/91). • In distinguishing pCRs from non-pCR, the rate of agreement between MRI and pathology was 77.8% (11/18) for pCRs and 94.5% (69/73) for non- pCRs, resulting in an overall agreement rate of 91.2% (83/91).