Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images

Davide Cusumano; Luca Russo; Benedetta Gui; Rosa Autorino; Luca Boldrini; Luca D'Erme; Salvatore Persiani; Francesco Catucci; Sara Broggi; Giulia Panza; Alessia Nardangeli; Maura Campitelli; Maria Gabriella Ferrandina; Gabriella Macchia; Claudio Fiorino; Vincenzo Valentini; Giovanni Scambia; Riccardo Manfredi; Maria Antonietta Gambacorta

doi:10.1016/j.radonc.2022.07.001

Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images

Davide Cusumano, Luca Russo, Benedetta Gui, Rosa Autorino, Luca Boldrini, Luca D'Erme, Salvatore Persiani, Francesco Catucci, Sara Broggi, Giulia Panza, Alessia Nardangeli, Maura Campitelli, Maria Gabriella Ferrandina, Gabriella Macchia, Claudio Fiorino, Vincenzo Valentini, Giovanni Scambia, Riccardo Manfredi, Maria Antonietta Gambacorta

Risultato della ricerca: Contributo in rivista › Articolo

Abstract

Background and Purpose: Early Regression Index (ERITCP) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based param-eters such as tumor volumes and apparent coefficient diffusion (ADC).Materials and Methods: A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERITCP was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERITCP, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes.Results: ERITCP and GTV volumes calculated on DW MR images (ERIDWI and Vmid_DWI) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival. Conclusion: This study identified ERITCP and Vmid as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.(c) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 174 (2022) 30-36

Lingua originale	Inglese
pagine (da-a)	30-36
Numero di pagine	7
Rivista	Radiotherapy and Oncology
Volume	174
DOI	https://doi.org/10.1016/j.radonc.2022.07.001
Stato di pubblicazione	Pubblicato - 2022

Keywords

Cervical Cancer
Image-based biomarker
Predictive model
Radiomics

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Cusumano, D., Russo, L., Gui, B., Autorino, R., Boldrini, L., D'Erme, L., Persiani, S., Catucci, F., Broggi, S., Panza, G., Nardangeli, A., Campitelli, M., Ferrandina, M. G., Macchia, G., Fiorino, C., Valentini, V., Scambia, G., Manfredi, R., & Gambacorta, M. A. (2022). Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images. Radiotherapy and Oncology, 174, 30-36. https://doi.org/10.1016/j.radonc.2022.07.001

@article{1abd7771e1814e1095a155d701fd700d,

title = "Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images",

abstract = "Background and Purpose: Early Regression Index (ERITCP) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based param-eters such as tumor volumes and apparent coefficient diffusion (ADC).Materials and Methods: A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERITCP was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERITCP, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes.Results: ERITCP and GTV volumes calculated on DW MR images (ERIDWI and Vmid_DWI) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival. Conclusion: This study identified ERITCP and Vmid as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.(c) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 174 (2022) 30-36",

keywords = "Cervical Cancer, Image-based biomarker, Predictive model, Radiomics, Cervical Cancer, Image-based biomarker, Predictive model, Radiomics",

author = "Davide Cusumano and Luca Russo and Benedetta Gui and Rosa Autorino and Luca Boldrini and Luca D'Erme and Salvatore Persiani and Francesco Catucci and Sara Broggi and Giulia Panza and Alessia Nardangeli and Maura Campitelli and Ferrandina, {Maria Gabriella} and Gabriella Macchia and Claudio Fiorino and Vincenzo Valentini and Giovanni Scambia and Riccardo Manfredi and Gambacorta, {Maria Antonietta}",

year = "2022",

doi = "10.1016/j.radonc.2022.07.001",

language = "English",

volume = "174",

pages = "30--36",

journal = "Radiotherapy and Oncology",

issn = "0167-8140",

publisher = "Elsevier Ireland Ltd",

}

Cusumano, D, Russo, L, Gui, B, Autorino, R, Boldrini, L, D'Erme, L, Persiani, S, Catucci, F, Broggi, S, Panza, G, Nardangeli, A, Campitelli, M, Ferrandina, MG, Macchia, G, Fiorino, C, Valentini, V, Scambia, G, Manfredi, R & Gambacorta, MA 2022, 'Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images', Radiotherapy and Oncology, vol. 174, pagg. 30-36. https://doi.org/10.1016/j.radonc.2022.07.001

TY - JOUR

T1 - Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images

AU - Cusumano, Davide

AU - Russo, Luca

AU - Gui, Benedetta

AU - Autorino, Rosa

AU - Boldrini, Luca

AU - D'Erme, Luca

AU - Persiani, Salvatore

AU - Catucci, Francesco

AU - Broggi, Sara

AU - Panza, Giulia

AU - Nardangeli, Alessia

AU - Campitelli, Maura

AU - Ferrandina, Maria Gabriella

AU - Macchia, Gabriella

AU - Fiorino, Claudio

AU - Valentini, Vincenzo

AU - Scambia, Giovanni

AU - Manfredi, Riccardo

AU - Gambacorta, Maria Antonietta

PY - 2022

Y1 - 2022

N2 - Background and Purpose: Early Regression Index (ERITCP) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based param-eters such as tumor volumes and apparent coefficient diffusion (ADC).Materials and Methods: A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERITCP was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERITCP, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes.Results: ERITCP and GTV volumes calculated on DW MR images (ERIDWI and Vmid_DWI) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival. Conclusion: This study identified ERITCP and Vmid as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.(c) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 174 (2022) 30-36

AB - Background and Purpose: Early Regression Index (ERITCP) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based param-eters such as tumor volumes and apparent coefficient diffusion (ADC).Materials and Methods: A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERITCP was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERITCP, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes.Results: ERITCP and GTV volumes calculated on DW MR images (ERIDWI and Vmid_DWI) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival. Conclusion: This study identified ERITCP and Vmid as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.(c) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 174 (2022) 30-36

KW - Cervical Cancer

KW - Image-based biomarker

KW - Predictive model

KW - Radiomics

KW - Cervical Cancer

KW - Image-based biomarker

KW - Predictive model

KW - Radiomics

UR - http://hdl.handle.net/10807/232232

U2 - 10.1016/j.radonc.2022.07.001

DO - 10.1016/j.radonc.2022.07.001

M3 - Article

SN - 0167-8140

VL - 174

SP - 30

EP - 36

JO - Radiotherapy and Oncology

JF - Radiotherapy and Oncology

ER -

Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images

Abstract

Keywords

OSS delle Nazioni Unite

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