The Role of Baseline PET/CT Parameters in Predicting Treatment Response in Patients with Locally Advanced Rectal Cancer Undergoing Total Neoadjuvant Therapy
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background and Objectives: Total neoadjuvant therapy (TNT) for locally advanced rectal cancer (LARC) offers significant advantages in terms of pathologic response and long-term survival; however, it is still unclear which patients will benefit the most from this treatment. This study aims to investigate the role of metabolic parameters on pretreatment positron emission tomography–computed tomography (PET/CT) images in predicting treatment response after TNT. Materials and Methods: The research was conducted using a single-center, retrospective design. Patients treated with total neoadjuvant therapy are included if they have locally advanced rectal cancer (cT3/T4-N0 or cTany-N1/N2). The patient group was categorized into two groups: CR and non-CR. Clinicopathologic features, PET/CT parameters, CA19-9, and CEA values were compared between these two groups. Results: In total, 52 patients were included. The CR group had 21 patients, and the non-CR group had 31 patients. The analysis demonstrated that the CR group had significantly lower metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than the non-CR group (p = 0.022 vs. p = 0.003, p < 0.05). Also, CA19-9 values were lower than the non-CR group, and this difference was statistically remarkable (p = 0.40, p < 0.05). Conclusions: MTV and TLG parameters in PET/CT for pretreatment staging and pretreatment blood CA 19-9 levels are prognostic factors for predicting treatment response, and they may play a crucial role in choosing treatment. Comprehensive research is warranted on this subject with a larger patient population.
Source: Medicina
Authors: Ali Kaan Güren, Zilan Başkan, Zeynep Ceren Balaban Genç, Tuğçe Bulun Akyol, Erkam Kocaaslan, Yeşim Ağyol, Pınar Erel, Burak Paçacı, Mustafa Alperen Tunç, Ahmet Demirel, Nargiz Majidova, Nadiye Sever, Abdussamet Çelebi, Selver Işık, Murat Sarı, Osman Köstek, Salih Özgüven, Hilal Alkış, Mustafa Adli, İbrahim Vedat Bayoğlu
Institution: Marmara University
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,654
Funder: Marmara Üniversitesi
OpenAlex ID: W4413104112
