A prospective study on neoadjuvant chemoradiotherapy plus anti-EGFR monoclonal antibody followed by surgery for locally advanced cervical cancer

Objective: Magnetic resonance–guided radiotherapy (MRgRT) represents an innovative approach for personalized radiotherapy treatments and its applications are being explored in various anatomical sites to fully understand its potential advantages. This study describes the first clinical experience of MRgRT application in patients with locally advanced cervical cancer (LACC) undergoing neoadjuvant chemoradiotherapy. The feasibility of the technique is evaluated and its toxicity profile and clinical outcomes are reported. Methods: Patients with LACC (International Federation of Gynecology and Obstetrics stage IIA–IVA) undergoing neoadjuvant chemoradiotherapy (CRT) on a 0.35T Tri-60-Co hybrid unit (ViewRay) were retrospectively compared with randomly selected patients treated with a standard linear accelerator. Total prescribed dose was 50.6 Gy (2.3 Gy/fraction) to planning target volume 1 (PTV1) and 39.6 Gy (1.8 Gy/fraction) to PTV2, delivered using a simultaneous integrated boost. Surgery was performed 8 weeks after the end of CRT. The effect of magnetic resonance guidance on replanning approaches, treatment-related toxicities, and pathologic response were assessed for each patient. Patient outcomes were noted and dosimetric comparisons performed between the 2 arms. Results: Nine patients with LACC treated from May 2018 to November 2018 were retrospectively enrolled and their records compared with the records of an equivalent cohort of randomly selected patients. Five replanning cases were performed in the MRgRT group and 0 in the linear accelerator group. Acute G1–G2 gastrointestinal toxicities were observed in 33.3% of MRgRT patients and in 55.5% of linear accelerator patients; acute G1–G2 genitourinary toxicities in 22.2% and 33.3%, respectively. No G3 toxicity was found except for neutropenia in 2 patients. No differences were observed in pathologic response between the 2 groups. Conclusions: Despite the retrospective nature of the observations and the low number of enrolled patients, the application of MRgRT in LACC appears to be safe and feasible with a favorable toxicity profile and response rates comparable to gold standard, supporting the setup of larger prospective studies to investigate the potentialities of this new technology.

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Pretreatment MRI Radiomics Based Response Prediction Model in Locally Advanced Cervical Cancer

Diagnostics ◽

10.3390/diagnostics11040631 ◽

2021 ◽

Vol 11 (4) ◽

pp. 631

Author(s):

Benedetta Gui ◽

Rosa Autorino ◽

Maura Miccò ◽

Alessia Nardangeli ◽

Adele Pesce ◽

...

Keyword(s):

Cervical Cancer ◽

Statistical Significance ◽

Univariate Analysis ◽

Locally Advanced ◽

Neoadjuvant Chemoradiotherapy ◽

Residual Tumour ◽

Advanced Cervical Cancer ◽

Treatment Pathways ◽

Surgical Specimen ◽

Locally Advanced Cervical Cancer

The aim of this study was to create a radiomics model for Locally Advanced Cervical Cancer (LACC) patients to predict pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NACRT) analysing T2-weighted 1.5 T magnetic resonance imaging (MRI) acquired before treatment start. Patients with LACC and an International Federation of Gynecology and Obstetrics stage from IB2 to IVA at diagnosis were retrospectively enrolled for this study. All patients underwent NACRT, followed by radical surgery; pCR―assessed on surgical specimen―was defined as absence of any residual tumour. Finally, 1889 features were extracted from MR images; features showing statistical significance in predicting pCR at the univariate analysis were selected following an iterative method, which was ad-hoc developed for this study. Based on this method, 15 different classifiers were trained considering the most significant features selected. Model selection was carried out using the area under the receiver operating characteristic curve (AUC) as target metrics. One hundred eighty-three patients from two institutions were analysed. The model, showing the highest performance with an AUC of 0.80, was the random forest method initialised with default parameters. Radiomics appeared to be a reliable tool in pCR prediction for LACC patients undergoing NACRT, supporting the identification of patient risk groups, which paves treatment pathways tailored according to the predicted outcome.

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