The Application of the T1WI Sequence in High-Grade Serous Ovarian Cancer

Abstract

T1-weighted magnetic resonance imaging (T1WI) sequences are emerging as a powerful tool for the assessment of high-grade serous ovarian cancer (HGSOC), providing unique insights into tumour biology, the composition of the microenvironment, and treatment response. The intrinsic T1 signal changes in HGSOC arise from intrinsic pathophysiological features such as intratumoural haemorrhage, necrosis and increased protein content; these factors shorten T1 relaxation times and are independent of contrast agent administration. Following contrast administration, dynamic T1 changes reflect vascular remodelling and extracellular matrix expansion—hallmark features of aggressive disease—whilst genomic instability (particularly BRCA-associated phenotypes) further modulates T1-visible tissue characteristics. Technological advances have driven the evolution of T1 assessment from qualitative imaging towards quantitative pixel-level T1 mapping and dynamic contrast-enhanced (DCE) modelling, thereby enabling the extraction of pharmacokinetic parameters associated with tumour biology. The integration of synthetic MRI with machine learning algorithms has significantly improved the reproducibility and accuracy of T1 feature quantification. Clinically, pre-treatment T1 metrics show promise in predicting platinum resistance, whilst early post-contrast T1 kinetics during neoadjuvant chemotherapy correlate with treatment response and progression-free survival, often demonstrating superior predictive value compared to CA-125 trends. Compared with diffusion-weighted imaging, FDG-PET/CT and conventional CT, T1-based detection methods exhibit higher specificity in identifying microenvironmental features, can reduce inflammatory false positives, and improve the detection rate of peritoneal lesions by enhancing soft tissue contrast. Practical application requires standardisation of protocols regarding timing, fat suppression and magnetic field strength, whilst consensus must be reached on the definition of regions of interest and clinically relevant thresholds. Despite these advances, challenges remain, including inter-platform variability, interference from iron deposition and ascites, and a lack of prospective, multicentre validation, which hinder its inclusion in current guidelines. Looking ahead, AI-driven radiomics, multi-parametric MRI features, and the role of T1 sequences as dynamic biomarkers for anti-angiogenic therapies will position T1 sequences at the forefront of precision oncology and therapeutic diagnostic strategies for HGSOC.