» Articles » PMID: 38248772

Prognostic Value of Radiomic Analysis Using Pre- and Post-Treatment F-FDG-PET/CT in Patients with Laryngeal Cancer and Hypopharyngeal Cancer

Overview
Journal J Pers Med
Date 2024 Jan 22
PMID 38248772
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The prognostic value of conducting F-FDG PET/CT imaging has yielded different results in patients with laryngeal cancer and hypopharyngeal cancer, but these results are controversial, and there is a lack of dedicated studies on each type of cancer. This study aimed to evaluate whether combining radiomic analysis of pre- and post-treatment F-FDG PET/CT imaging features and clinical parameters has additional prognostic value in patients with laryngeal cancer and hypopharyngeal cancer.

Methods: From 2008 to 2016, data on patients diagnosed with cancer of the larynx and hypopharynx were retrospectively collected. The patients underwent pre- and post-treatment F-FDG PET/CT imaging. The values of ΔPre-Post PET were measured from the texture features. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select the most predictive features to formulate a Rad-score for both progression-free survival (PFS) and overall survival (OS). Kaplan-Meier curve analysis and Cox regression were employed to assess PFS and OS. Then, the concordance index (C-index) and calibration plot were used to evaluate the performance of the radiomics nomogram.

Results: Study data were collected for a total of 91 patients. The mean follow-up period was 71.5 mo. (8.4-147.3). The Rad-score was formulated based on the texture parameters and was significantly associated with both PFS ( = 0.024) and OS ( = 0.009). When predicting PFS, only the Rad-score demonstrated a significant association (HR 2.1509, 95% CI [1.100-4.207], = 0.025). On the other hand, age (HR 1.116, 95% CI [1.041-1.197], = 0.002) and Rad-score (HR 33.885, 95% CI [2.891-397.175], = 0.005) exhibited associations with OS. The Rad-score value showed good discrimination when it was combined with clinical parameters in both PFS (C-index 0.802-0.889) and OS (C-index 0.860-0.958). The calibration plots also showed a good agreement between the observed and predicted survival probabilities.

Conclusions: Combining clinical parameters with radiomics analysis of pre- and post-treatment F-FDG PET/CT parameters in patients with laryngeal cancer and hypopharyngeal cancer might have additional prognostic value.

Citing Articles

Correction: Choi et al. Prognostic Value of Radiomic Analysis Using Pre- and Post-Treatment F-FDG-PET/CT in Patients with Laryngeal Cancer and Hypopharyngeal Cancer. 2024, , 71.

Choi J, Choi J, Woo S, Moon J, Lim C, Park S J Pers Med. 2025; 15(2).

PMID: 39997352 PMC: 11856748. DOI: 10.3390/jpm15020074.


Role of F-FDG PET/CT in Head and Neck Squamous Cell Carcinoma: Current Evidence and Innovative Applications.

Caldarella C, De Risi M, Massaccesi M, Micciche F, Bussu F, Galli J Cancers (Basel). 2024; 16(10).

PMID: 38791983 PMC: 11119768. DOI: 10.3390/cancers16101905.

References
1.
Feliciani G, Fioroni F, Grassi E, Bertolini M, Rosca A, Timon G . Radiomic Profiling of Head and Neck Cancer: F-FDG PET Texture Analysis as Predictor of Patient Survival. Contrast Media Mol Imaging. 2018; 2018:3574310. PMC: 6180924. DOI: 10.1155/2018/3574310. View

2.
Wang L, Wu X, Tian R, Ma H, Jiang Z, Zhao W . MRI-based pre-Radiomics and delta-Radiomics models accurately predict the post-treatment response of rectal adenocarcinoma to neoadjuvant chemoradiotherapy. Front Oncol. 2023; 13:1133008. PMC: 10013156. DOI: 10.3389/fonc.2023.1133008. View

3.
Guezennec C, Robin P, Orlhac F, Bourhis D, Delcroix O, Gobel Y . Prognostic value of textural indices extracted from pretherapeutic 18-F FDG-PET/CT in head and neck squamous cell carcinoma. Head Neck. 2018; 41(2):495-502. DOI: 10.1002/hed.25433. View

4.
Kakava K, Karelas I, Koutrafouris I, Damianidis S, Stampouloglou P, Papadakis G . Relationship between ABO blood groups and head and neck cancer among Greek patients. J BUON. 2016; 21(3):594-6. View

5.
Scalco E, Rizzo G . Texture analysis of medical images for radiotherapy applications. Br J Radiol. 2016; 90(1070):20160642. PMC: 5685100. DOI: 10.1259/bjr.20160642. View