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Predicting the Unpredictable: AI-Driven Prognosis in Pancreatic Neuroendocrine Neoplasms

  • Elettra Merola,
  • Emanuela Pirino and
  • Alberto Brolese
  • + 7 authors

The clinical management of Pancreatic Neuroendocrine Neoplasms (Pan-NENs) is complicated by the disease’s intrinsic variability, which creates significant hurdles for accurate risk profiling and the standardization of treatment protocols. Recently, Artificial Intelligence (AI) has offered a promising avenue to address these challenges. By integrating and processing high-dimensional multimodal datasets (encompassing clinical history, radiomics, and pathology), these computational tools can refine survival forecasts and support the development of personalized medicine. However, the transition from experimental success to routine clinical use is currently obstructed by reliance on limited, retrospective cohorts that lack external validation, alongside unresolved concerns regarding algorithmic transparency and ethical governance. This review evaluates the current landscape of AI-driven prognostic modeling for Pan-NENs and critically examines the pathway towards their reliable integration into clinical practice.

19 January 2026

AI-driven prognostic modeling in Pan-NENs: from multimodal data to clinical application. CT: Computed Tomography; CEUS: Contrast-Enhanced Ultrasound; PET: Positron Emission Tomography; AURKA: Aurora Kinase A; DAXX: Death Domain Associated Protein; VCAN: Versican Core Protein; ML: Machine Learning; DL: Deep Learning; XGBoost: eXtreme Gradient Boosting; EACCD: Ensemble Algorithm for Clustering Cancer Data.

Experience of a Referral Center with Desmoid Tumors, Part 2: A Retrospective Analysis of 109 Cases

  • Alvarez Alvarez Rosa,
  • Agra Pujol Carolina and
  • Gutiérrez-Ortiz de la Tabla Ana
  • + 11 authors

Background: Desmoid tumors (DTs) are rare, locally aggressive fibroblastic neoplasms with highly heterogeneous clinical behavior. The present work constitutes the second part of a two-part project, following our previously published multidisciplinary review of the diagnostic and therapeutic landscape of DTs. It provides a comprehensive analysis of our institutional experience as a national reference center for sarcoma. We aim to describe real-world diagnostic pathways, management strategies, and clinical outcomes in a high-volume cohort. Methods: We conducted a retrospective cohort study that included patients diagnosed with DT at our center between 2014 and 2024. Demographic, clinical, molecular, treatment, and outcome data were collected. Management strategies were analyzed according to tumor location, symptoms, progression patterns, and multidisciplinary decision-making. Outcomes included response rates, event-free survival (EFS), need for active treatment, response to systemic therapy, and recurrence after local treatments. Results: A total of 109 patients were included (median age 36.8 years; 56.9% women). Somatic CTNNB1 mutations were identified in 23 of 29 tested patients, predominantly T41A, while germline alterations were found in 18 patients, mainly in APC. Initial management was conservative in 40.4% of patients and active in 59.6%, primarily through surgery. After a median follow-up of 41.5 months, 44.9% of patients experienced disease progression. Among patients managed with active surveillance, spontaneous regression occurred in 22.2%, and 58% remained treatment-free. Surgical relapse occurred in 35.8% of patients undergoing upfront resection, with major postoperative complications limited to externally operated cases. Cryoablation achieved radiological responses in most evaluable patients, while systemic therapies showed clinical activity but relevant toxicity, particularly with tyrosine kinase inhibitors. The median EFS for the whole cohort was 57 months. Conservative initial management and R1/2 surgical margins were independently associated with worse EFS. Conclusions: Our results support a personalized, multidisciplinary management strategy for DTs, prioritizing conservative approaches when appropriate and reserving active treatments for progressive or symptomatic disease. Outcomes achieved in a specialized referral center are comparable to those reported in large international retrospective series, underscoring the value of expert multidisciplinary care in optimizing DT management.

19 January 2026

Brain metastases (BMs) represent the most common intracranial malignancy in adults, affecting up to 50% of patients with solid tumours [...]

19 January 2026

Quantitative Imaging Advances in HPV-Positive Oropharyngeal Carcinoma

  • Dermot Farrell,
  • Houda Bahig and
  • Sweet Ping Ng
  • + 14 authors

HPV-positive OPSCC shows a favourable prognosis, prompting evaluation of de-escalated and adaptive strategies. Quantitative imaging may provide scalable biomarkers to individualise care. Quantitative imaging can support baseline risk stratification, early on-treatment decision-making, and posttreatment surveillance in HPV-positive OPSCC. Real-world translation requires standardised reporting, calibration/harmonisation across centres, rigorous model validation, and workflow integration with radiotherapy planning. Quantitative MRI, CT, and PET, augmented by radiomics and AI, show convergent promise as non-invasive biomarkers to enable safe individualisation of therapy in HPV-positive OPSCC, contingent on methodological rigour and prospective, externally validated studies. Despite this promise, clinical translation faces substantial barriers, including limited external validation, heterogeneous methodologies, and the need for standardised, prospectively validated pipelines.

19 January 2026

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Management of Pancreatic Cancer
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Editors: Traian Dumitrascu
Advances in Pediatric and Adolescent Psycho-Oncology
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Editors: Lori Wiener, Amanda L. Thompson

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Cancers - ISSN 2072-6694