Nicolae Verga

Background: Brain tumors represent a major cause of neurological morbidity and mortality, often requiring radiotherapy as a central component of treatment. While advances in radiation techniques have improved tumor control, increasing attention has been directed toward radiation-induced effects on healthy brain tissue, particularly regarding neuronal function and cognitive outcomes. Objective: This review aims to provide a structured synthesis of current evidence on radiation-induced neuronal dysfunction, integrating dose–volume parameters, neuroimaging biomarkers, and clinical neurological manifestations. Methods: A structured literature review was conducted using electronic databases including PubMed, Scopus, and Web of Science. Relevant studies evaluating dose–volume effects, neuroimaging findings, and clinical outcomes following cranial radiotherapy were included. Results: Dose–volume histogram (DVH) parameters, including mean brain dose and intermediate-dose volumes (V10–V30), as well as hippocampal dose, were identified as key factors associated with cognitive decline and neuronal dysfunction. Conventional MRI detects structural changes such as white matter injury and radionecrosis, while advanced techniques including diffusion tensor imaging (DTI) and functional MRI (fMRI) reveal microstructural damage and network disruption. These imaging findings correlate with a spectrum of clinical manifestations ranging from subtle cognitive impairment to significant neurological deficits. Conclusions: Radiation-induced neuronal dysfunction represents a complex and multifactorial process that extends beyond localized tissue injury. Integrating dose–volume considerations with advanced imaging biomarkers may improve risk stratification and support the development of neuroprotective strategies in patients undergoing cranial radiotherapy.

The Systems Theory provides a valuable conceptual framework for analyzing biological complexity, particularly in oncology, where the multiple interactions between biological subsystems can influence tumor initiation, progression, and treatment response. This approach facilitates the integration of data derived from genomics, metabolomics, routine medical analyses, and the clinical examination of the patient, thus overcoming the limitations of the reductionist model. By applying the principles of living systems, new tumor vulnerabilities can be identified, as well as models of cellular, metabolic, and informational organization. The use of systems theory in oncology may contribute to the development of personalized and precision medicine, improving diagnostic and prognostic methods, and enhancing the efficiency of personalized therapies with the aim of improving therapeutic outcomes and the patient’s quality of life.

Background and clinical significance: Phyllodes tumors (PTs) are rare stromal neoplasms originating in the connective tissue of the breast, distinct from carcinomas that arise from the ducts or lobules. These tumors exhibit a broad spectrum of morphologic features and are traditionally classified as benign, borderline, or malignant. Case presentation: We present the case of a 71-year-old female diagnosed with a malignant PT and treated at our hospital. The patient noticed a gradually enlarging lump in her right breast over several months. Mammography was inconclusive, but an ultrasound later revealed a lobulated, firm mass, classified as BIRADS 5. Physical examination identified a 20 cm mass, and core needle biopsy suggested a borderline PT. Following lumpectomy, pathology confirmed a malignant tumor with narrow surgical margins (0.1 cm). Although mastectomy was recommended to achieve wider margins, the patient opted for adjuvant radiotherapy. She received 50 Gy in 25 fractions to the whole breast, followed by a 16 Gy boost to the tumor bed in 8 fractions. The treatment was well tolerated and completed successfully. Initially, the patient’s therapeutic management was delayed due to a combination of personal and organizational factors. However, the process was later streamlined through the use of a novel digital tool developed to facilitate the entire patient journey within our hospital system. Conclusions: This case highlights the diagnostic complexities of PTs, the critical need for effective collaboration between specialties, and the importance of timely treatment planning for optimal patient outcomes.

Rectal cancer (RC) presents significant challenges in diagnosis and treatment, with increasing incidence among younger populations. Treatment approaches, particularly for locally advanced rectal cancer (LARC), have evolved, notably with the introduction of total neoadjuvant therapy (TNT). TNT combines neoadjuvant chemotherapy and chemoradiotherapy before surgery, improving overall survival and reducing both metastasis and local recurrence rates compared to traditional methods, while enabling more patients to complete the full oncological treatment. Clinical trials, such as RAPIDO, OPRA, and PRODIGE 23, have demonstrated the effectiveness of TNT in tumor downstaging and complete pathological responses, offering better outcomes for patients; however, debates persist regarding the role of neoadjuvant radiotherapy, with novel strategies exploring its omission in specific cases to reduce toxicity and enhance quality of life. In addition, organ preservation strategies, such as the watch-and-wait (WW) approach, have emerged as viable options for patients with a complete response to neoadjuvant therapy. Future directions point towards personalized treatment plans incorporating radiogenomics and the integration of artificial intelligence into diagnostics to optimize patient outcomes. This review aims to synthesize current treatment strategies and ongoing advancements in rectal cancer management, providing insights into potential future innovations.

Biomarkers in colorectal cancer (CRC) are of great interest in the current literature due to improvements in techniques such as liquid biopsy and next-generation sequencing (NGS). However, screening methods vary globally, with multi-target stool DNA (mt-sDNA) predominantly used in the USA and, more recently, the Cologuard Plus; biomarkers such as the Galectins family and septins show promise in early detection. Gut microbiome assessments, such as Fusobacterium nucleatum, are under intense exploration. Diagnostic tests, such as circulating DNA analysis via NGS, exhibit effectiveness and are being increasingly adopted. Circulating tumor cells emerge as potential alternatives to traditional methods in terms of diagnosis and prognosis. Predictive biomarkers are well established in guidelines; nonetheless, with the aid of machine learning and artificial intelligence, these biomarkers may be improved. This review critically explores the actual dynamic landscape of CRC biomarkers and future, promising biomarkers involved in screening, diagnosis, and prognosis.