Keyword: Biopsy

ABSTRACT: Cancer behaves as a dynamic evolutionary system, whereas conventional tissue biopsy and imaging provide incomplete temporal information about how a tumour is changing. This review critically examines whether longitudinal liquid-biopsy measurement, combined with artificial intelligence (AI), can move oncology from tumour monitoring toward genuine prediction of cancer evolution and treatment resistance. We synthesise mechanistic, clinical, and computational evidence on circulating tumour DNA, circulating tumour cells, extracellular vesicles, and multimodal liquid-biopsy platforms, together with AI approaches applied to longitudinal cancer data, drawing on landmark and recent studies across colorectal, lung, breast, and ovarian cancer. Current evidence distinguishes three increasingly demanding tasks: early detection, longitudinal monitoring, and genuine forecasting. Longitudinal circulating tumour DNA analysis can detect molecular progression and emerging resistance mutations months before radiographic progression, and machine-learning models can stratify survival using serial biomarker metrics; however, most published "AI prediction" studies demonstrate earlier detection or prognostic association rather than prospectively validated forecasting of a future, patient-specific event. Biological variability in tumour shedding, analytical noise, small and irregularly sampled longitudinal datasets, overfitting, data leakage, weak external validation, and limited interpretability constrain the transition from detection to actionable prediction. AI-enabled liquid biopsy has genuine potential to forecast tumour trajectories, but current evidence is considerably stronger for molecular monitoring and early detection than for prospectively validated, clinically actionable prediction. Realising this potential will require standardised assays, prospective longitudinal cohorts with predefined prediction horizons, rigorous external and temporal validation, calibrated and interpretable models, and interventional trials linking predictions to treatment decisions before AI-enabled liquid biopsy can be considered ready to guide clinical care.

ABSTRACT: Introduction: Pediatric nodular thyroid disease is associated with an elevated probability of malignant transformation (20% to 26%), necessitating precise preoperative diagnostic triage (1). International consensus guidelines establish ultrasound-based risk stratification using the Thyroid Imaging Reporting and Data System (TI-RADS) alongside fine-needle aspiration biopsy (FNAB) with cytopathological evaluation under the Bethesda System as pivotal clinical instruments guiding the choice between observation and surgical intervention (1,2). This study aimed to evaluate the impact of TI-RADS and cytopathological classification on the selection of surgical versus observational management strategies in pediatric patients with thyroid nodules.
Materials and Methods: A consecutive retrospective analysis was conducted on 15 patients aged 10 to 17 years with thyroid nodules evaluated between October 2024 and July 2026 at an ambulatory surgical center. Inclusion criteria encompassed age under 18 years, ultrasonographic confirmation of a nodular lesion, and completion of fine-needle aspiration biopsy. No exclusion criteria were applied. The diagnostic workup incorporated sonography with TI-RADS categorization, ultrasound-guided biopsy with cytopathological reporting according to the Bethesda System (2,3), and serological assessment of thyroid-stimulating hormone (TSH), free thyroxine, antithyroid antibodies, and calcitonin. Data analysis relied on the calculation of relative frequencies and proportions. The study was conducted in accordance with the principles of the Helsinki Declaration; retrospective analysis of anonymized data did not require informed consent.
Results: Female adolescents constituted the majority of the cohort (86.7%; 13/15), with an overall mean age of 14.8 ± 2.3 years, consistent with the age distribution of thyroid pathology in adolescents (1). Ultrasound stratification revealed TI-RADS 2–3 in 73.3% (11/15) and TI-RADS 4 in 26.7% (4/15). Initial cytopathological classification yielded category I in 40.0% (6/15), category III in 26.7% (4/15), category IV in 26.7% (4/15), and category V in 6.7% (1/15). The proportion of non-diagnostic aspirates was related to the presence of cystic elements within this cohort (4). Hormonal profiling demonstrated euthyroidism in all evaluated cases with a median thyroid-stimulating hormone concentration of 2.1 mIU/L. Conservative dynamic surveillance at three- to six-month intervals was chosen for 93.3% of children (14/15). In one adolescent (6.7%; 1/15) presenting concordant TI-RADS 4 and category IV cytology, total thyroidectomy with regional lymph node clearance was performed; postoperative histopathology confirmed metastatic papillary thyroid carcinoma (1,5). The overall confirmed malignancy rate was 6.7%, which aligns with literature data for pediatric populations (5% to 26%) (1,5).
Conclusions: Combined application of TI-RADS sonographic stratification and Bethesda-based biopsy enables reliable triage of pediatric patients. The substantial proportion of category I aspirates (40.0%) mandates repeat aspiration for cystic lesions, whereas concordance between TI-RADS 4 sonographic criteria and neoplastic cytology constitutes a direct indication for surgical intervention.

ABSTRACT: Liquid biopsies have developed as a revolutionary technique in cancer diagnosis, treatment evaluation, and the detection of therapeutic resistance. Unlike traditional tissue biopsies, which are invasive and limited to a single temporal analysis, liquid biopsies offer a non-invasive, real-time evaluation of tumour dynamics through the analysis of biomarkers such as circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), exosomes, and microRNAs. This approach enables continuous monitoring of tumour advancement, allowing for the early detection of cancer, the tracking of minimal residual disease, and the identification of emerging resistance mutations. As cancers advance and acquire resistance to therapies, liquid biopsy provides critical information that enables clinicians to customise treatment strategies and improve outcomes. Despite challenges such as sensitivity limitations in early-stage cancers and the necessity for standardised testing protocols, technological advancements, including next-generation sequencing (NGS), CRISPR, and AI-driven analytics, are enhancing the precision and accessibility of liquid biopsies. Through ongoing validation and cost-reduction efforts, liquid biopsies are set to become essential to precision oncology, offering a transformative approach to cancer therapy that could improve patient outcomes and foster equitable healthcare globally.