Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Oct 7:11:704607.
doi: 10.3389/fonc.2021.704607. eCollection 2021.

Exploring CT Texture Parameters as Predictive and Response Imaging Biomarkers of Survival in Patients With Metastatic Melanoma Treated With PD-1 Inhibitor Nivolumab: A Pilot Study Using a Delta-Radiomics Approach

Antonino Guerrisi  1 , Michelangelo Russillo  2 , Emiliano Loi  3 , Balaji Ganeshan  4 , Sara Ungania  3 , Flora Desiderio  1 , Vicente Bruzzaniti  3 , Italia Falcone  2 , Davide Renna  5 , Virginia Ferraresi  2 , Mauro Caterino  1 , Francesco Maria Solivetti  1 , Francesco Cognetti  2 , Aldo Morrone  6
Affiliations

Exploring CT Texture Parameters as Predictive and Response Imaging Biomarkers of Survival in Patients With Metastatic Melanoma Treated With PD-1 Inhibitor Nivolumab: A Pilot Study Using a Delta-Radiomics Approach

Antonino Guerrisi et al. Front Oncol. .

Abstract

In the era of artificial intelligence and precision medicine, the use of quantitative imaging methodological approaches could improve the cancer patient's therapeutic approaches. Specifically, our pilot study aims to explore whether CT texture features on both baseline and first post-treatment contrast-enhanced CT may act as a predictor of overall survival (OS) and progression-free survival (PFS) in metastatic melanoma (MM) patients treated with the PD-1 inhibitor Nivolumab. Ninety-four lesions from 32 patients treated with Nivolumab were analyzed. Manual segmentation was performed using a free-hand polygon approach by drawing a region of interest (ROI) around each target lesion (up to five lesions were selected per patient according to RECIST 1.1). Filtration-histogram-based texture analysis was employed using a commercially available research software called TexRAD (Feedback Medical Ltd, London, UK; https://fbkmed.com/texrad-landing-2/) Percentage changes in texture features were calculated to perform delta-radiomics analysis. Texture feature kurtosis at fine and medium filter scale predicted OS and PFS. A higher kurtosis is correlated with good prognosis; kurtosis values greater than 1.11 for SSF = 2 and 1.20 for SSF = 3 were indicators of higher OS (fine texture: 192 HR = 0.56, 95% CI = 0.32-0.96, p = 0.03; medium texture: HR = 0.54, 95% CI = 0.29-0.99, p = 0.04) and PFS (fine texture: HR = 0.53, 95% CI = 0.29-0.95, p = 0.03; medium texture: HR = 0.49, 209 95% CI = 0.25-0.96, p = 0.03). In delta-radiomics analysis, the entropy percentage variation correlated with OS and PFS. Increasing entropy indicates a worse outcome. An entropy variation greater than 5% was an indicator of bad prognosis. CT delta-texture analysis quantified as entropy predicted OS and PFS. Baseline CT texture quantified as kurtosis also predicted survival baseline. Further studies with larger cohorts are mandatory to confirm these promising exploratory results.

Keywords: biomarker; image analysis; immunotherapy; melanoma; precision medicine; radiomics; x-ray computed tomography.

PubMed Disclaimer

Conflict of interest statement

One of the authors, BG, (who was not a data controller for this study) is the co-founder/co-inventor of TexRAD texture analysis software used in this study and a shareholder (not an employee) of Feedback Plc., a UK based company that owns, develops, and markets the TexRAD texture analysis software. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Schematic characteristics of patients enrolled in the study.
Figure 2
Figure 2
CT axial image with right inguinal lymph node segmented in 2D (A) and the resulting. Illustration of different image filtration as part of CTTA at (B) fine (SSF = 2mm), (C) medium (SSF = 4mm) and (D) coarse (SSF = 6mm) texture scales.
Figure 3
Figure 3
The figure compares survival curve for baseline CT texture parameter kurtosis at fine (SSF = 2) and medium (SSF = 3) texture scales and delta-analysis quantified Perc-ENTRO at medium (SSF = 4) and coarse (SSF = 6) scales for OS. Patients in the good prognostic group, as identified by baseline kurtosis are fine (SSF = 2) and medium (SSF = 3) texture scales, had an improved median survival of around 17 (A) and 10 months (B) respectively, compared to the poor prognostic group. Furthermore, the good prognostic group, which was defined using Kurtosis, demonstrated zero mortality. Patients in the good prognostic group, as identified by Perc-ENTRO at medium and coarse scales, improved median survival by around 11 months (C, D) compared to the poor prognostic group.
Figure 4
Figure 4
The figure compares survival curves for baseline CT texture parameter kurtosis at fine (SSF = 2) and medium (SSF = 3) texture scales, and delta-analysis quantified Perc-ENTRO at medium and coarse scales for PFS. Patients in the good prognostic group, as identified by baseline kurtosis at fine (SSF = 2) and medium (SSF = 3) texture scales, had an improved median PFS of around 28 (A) and 13 months (B) respectively, compared to the respective poor prognostic group. Furthermore, the good prognostic group defined using Kurtosis demonstrated zero progression. Patients in the good prognostic group, as identified by Perc-ENTRO, had an improved median PFS of around 8 months (C, D) compared to the poor prognostic group.
See this image and copyright information in PMC

References

    1. Emens LA, Ascierto PA, Darcy PK, Demaria S, Eggermont AMM, Redmond WL, et al. . Cancer Immunotherapy: Opportunities and Challenges in the Rapidly Evolving Clinical Landscape. Eur J Cancer (2017) 81:116–29. doi: 10.1016/j.ejca.2017.01.035 - DOI - PubMed
    1. Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Rutkowski P, Lao CD, et al. . Five-Year Survival With Combined Nivolumab and Ipilimumab in Advanced Melanoma. N Engl J Med (2019) 381(16):1535–46. doi: 10.1056/NEJMoa1910836 - DOI - PubMed
    1. Shah DJ, Dronca RS. Latest Advances in Chemotherapeutic, Targeted, and Immune Approaches in the Treatment of Metastatic Melanoma. Mayo Clin Proc (2014) 89(4):504–19. doi: 10.1016/j.mayocp.2014.02.002 - DOI - PMC - PubMed
    1. Ascierto PA, Long GV, Robert C, Brady B, Dutriaux C, Di Giacomo AM, et al. . Survival Outcomes in Patients With Previously Untreated BRAF Wild-Type Advanced Melanoma Treated With Nivolumab Therapy: Three-Year Follow-Up of a Randomized Phase 3 Trial. JAMA Oncol (2019) 5(2):187–94. doi: 10.1001/jamaoncol.2018.4514 - DOI - PMC - PubMed
    1. Johnson DB, Peng C, Sosman JA. Nivolumab in Melanoma: Latest Evidence and Clinical Potential. Ther Adv Med Oncol (2015) 7(2):97–106. doi: 10.1177/1758834014567469 - DOI - PMC - PubMed