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Texture analysis versus conventional MRI prognostic factors in predicting tumor response to neoadjuvant chemotherapy in patients with locally advanced cancer of the uterine cervix

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Abstract

Introduction

To determine the performance of texture analysis and conventional MRI parameters in predicting tumoral response to neoadjuvant chemotherapy and to assess whether a relationship exists between texture tissue heterogeneity and histological type of uterine cervix cancer.

Method and materials

Twenty-eight patients with local advanced cervical cancer (FIGO IB2-IIIB), underwent MRI before chemotherapy. Texture analysis parameters were quantified on T2-weighted sequences, as well as the maximum diameter expressed in mm. ADC values were obtained on the ADC map. Statistical analysis included unpaired t test and ROC curve.

Results

No statistical correlation was found between conventional parameters and response to NACT. Mean and skewness showed a strong correlation with the histological type: Adenocarcinomas presented higher mean and skewness values (69.8 ± 10.5 and 0.55 ± 0.19) in comparison with squamous cell carcinomas. Using a cutoff value ≥ 29 for mean it was possible to differentiate the two histological types with a sensitivity of 100% and a specificity of 81%. Kurtosis showed a positive correlation with tumor response to NACT resulting higher in responders (v.m. 5.7 ± 1.1) in comparison with non-responders (2.3 ± 0.5). The optimal Kurtosis cutoff value for the identification of non-responders tumors was ≤ 3.7 with a sensitivity of 92% and a specificity of 75%.

Conclusion

Texture analysis applied to T2-weighted images of uterine cervical cancer exceeded the role of conventional prognostic factors in predicting tumoral response; moreover, they showed a potential role to differentiate histological tumor types.

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Abbreviations

NACT:

Neoadjuvant chemotherapy

LACC:

Local advanced cervical cancer

FIGO:

International Federation of Gynecology and Obstetrics

MR:

Magnetic Resonance

TA:

Texture analysis

ROC:

Receiver operating characteristic

AUC:

Area under the curve

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Authors and Affiliations

  1. Department of Radiological Sciences, Oncology and Pathology, Diagnostic Imaging Unit, “Sapienza” - University of Rome, Viale Regina Margherita, 328, 00100, Rome, Italy

    Maria Ciolina, Valeria Vinci, Laura Villani, Silvia Gigli, Matteo Saldari, Carlo Catalano & Lucia Manganaro

  2. Department of Gynecology, Obstetrics and Urology, Sapienza University of Rome, Rome, Italy

    Pierluigi Benedetti Panici & Giorgia Perniola

  3. Department of Radiology, Sant’ Andrea Hospital, Faculty of Medicine and Psychology, “Sapienza” University of Rome, Rome, Italy

    Andrea Laghi

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  1. Maria Ciolina
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  2. Valeria Vinci
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  3. Laura Villani
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Correspondence to Lucia Manganaro.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Ciolina, M., Vinci, V., Villani, L. et al. Texture analysis versus conventional MRI prognostic factors in predicting tumor response to neoadjuvant chemotherapy in patients with locally advanced cancer of the uterine cervix. Radiol med 124, 955–964 (2019). https://doi.org/10.1007/s11547-019-01055-3

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