Search Results (89)

Background: Clinical imaging is an important part of health care providing physicians with great assistance in patients treatment. In fact, segmentation and grading of tumors can help doctors assess the severity of the cancer at an early stage and increase the chances of cure. Despite that Deep Learning for cancer diagnosis has achieved clinically acceptable accuracy, there still remains challenging tasks, especially in the context of insufficient labeled data and the subsequent need for expensive computational ressources. Objective: This paper presents a lightweight classification and segmentation deep learning model to assist in the identification of cancerous tumors with high accuracy despite the scarcity of medical data. Methods: We propose a multi-task architecture for classification and segmentation of cancerous tumors in the Brain, Skin, Prostate and lungs. The model is based on the UNet architecture with different pre-trained deep learning models (VGG 16 and MobileNetv2) as a backbone. The multi-task model is validated on relatively small datasets (slightly exceed 1200 images) that are diverse in terms of modalities (IRM, X-Ray, Dermoscopic and Digital Histopathology), number of classes, shapes, and sizes of cancer pathologies using the accuracy and dice coefficient as statistical metrics. Results: Experiments show that the multi-task approach improve the learning efficiency and the prediction accuracy for the segmentation and classification tasks, compared to training the individual models separately. The multi-task architecture reached a classification accuracy of 86%, 90%, 88%, and 87% respectively for Skin Lesion, Brain Tumor, Prostate Cancer and Pneumothorax. For the segmentation tasks we were able to achieve high precisions respectively 95%, 98% for the Skin Lesion and Brain Tumor segmentation and a 99% precise segmentation for both Prostate cancer and Pneumothorax. Proving that the multi-task solution is more efficient than single-task networks. Full article

Since its development in 1904, radical prostatectomy (RP) has remained a fundamental surgical option in the management of localised prostate cancer. Over time, continuous advancements in surgical techniques have improved oncological outcomes while reducing functional complications. This narrative review explores the evolution of RP, depicting its progression from the traditional open approach to minimally invasive laparoscopic and robotic-assisted techniques. Key developments in RP techniques, including nerve-sparing, bladder neck-sparing and Retzius-sparing techniques as well as enhanced perioperative management, have contributed to reduced postoperative complications, namely incontinence and erectile dysfunction. Additionally, technological innovations such as augmented reality, utilising indocyanine green for improved visualisation of prostatic boundaries and illuminare-1 to easily identify nerves intraoperatively, artificial intelligence, and novel molecular imaging technologies such as PSMA PETs for improved margin assessment are shaping the future of RPs. Despite these advancements, challenges persist, including a steep learning curve associated with newer techniques, disparities in access due to cost considerations, and a lack of standardised outcome measures across different surgical approaches. This review provides insight into current trends, ongoing challenges, and future directions that may further refine surgical precision, enhance patient safety, and improve long-term treatment success in prostate cancer management. Full article

Purpose/Objective: The clinical implementation of MR-guided radiotherapy on MR-linacs (MRL) hasrapidly increased in recent years. The advantages represented by the MR-based daily online plan adaptation and real-time monitoring have been exploited for different tumor sites. Nevertheless, some concerns remain, mainly related to the longer treatment time and limited patient eligibility. We report here the experience of our center, where a 1.5T MRL was clinically implemented in 2019 and, since then, more than 1200 patients have been treated. Material and Methods: The first 1000 patients treated at the MRL in our department were selected. Technical information such as treatment time and adaptive technic have been prospectively recorded, while toxicity data were retrospectively collected. Results: Between October 2019 and June 2024, 1000 patients for a total of 1061 treatment courses were included. Prostate and prostate bed were irradiated in 57.1% and 10.2% of the cases, respectively, including regional pelvic lymphnodes in 4.7%. Other frequent treated sites were lymph node metastases, pancreas and liver. The most frequent prescribed doses were 36.25 Gy (31%), 35 Gy (28.3%) and 30 Gy (9.4%) in five fractions. On a total of 9076 administered fractions, 80.8% were performed with adapt-to-shape and 19.2% with adapt-to-position method. The mean in-room time was 38 min (range, 18–103), with 74.4% of patients completing the session within 40 min. Acute grade (G) 3 toxicity was recorded in 1.6% of the cases, while, on a total of 858 patients available for late toxicity, G3 was recorded in 0.3% of the cases, with no >G3. Conclusions: Our real-world experience of an early-adopter center confirms that MRL treatments are feasible for different tumor entities in several anatomical sites. We showed that most of the patients could be treated within 40 min and showed low toxicity rates. Protocols for dose escalation and margin reduction, by adopting new comprehensive motion monitoring strategies, are under development. Full article

The tumor microenvironment (TME) plays a pivotal role in shaping immunometabolism in prostate cancer, influencing disease progression and therapeutic response. This review examines the dynamic interactions between tumor cells and immune cells within the prostate cancer TME, focusing on how metabolic reprogramming of both tumor and immune cells drives immunosuppression. Key immune players, including T-cells, macrophages, and myeloid-derived suppressor cells, undergo metabolic adaptations influenced by hypoxia, nutrient deprivation, and signaling from tumor cells. Additionally, we discuss the metabolic pathways involved, such as glycolysis and oxidative phosphorylation, and how these processes are exploited by cancer cells to evade immune surveillance. Furthermore, this review highlights potential therapeutic strategies targeting immunometabolism, including metabolic inhibitors and their combination with immunotherapies. A deeper understanding of the complex role of immunometabolism in prostate cancer will not only provide insights into the tumor’s immune evasion mechanisms but also facilitate the development of novel treatment approaches that enhance the efficacy of current therapies. Full article

Purpose: Image-guided radiotherapy (IGRT) has been widely implemented in the treatment of prostate cancer, offering a number of advantages regarding the precision of dose delivery. This study provides an overview of factors, clinical and physical alike, that increase treatment accuracy in prostate cancer radiotherapy in the context of IGRT. The following aspects are explored based on recent literature: the radiotherapy technique used in conjunction with IGRT, the type and frequency of IGRT, the impact of radiotherapy technique/IGRT on target dosimetry and organs at risk, the influence of IGRT on planning target volume margins, the impact of treatment time on dosimetric outcome and clinical outcomes using IGRT repositioning or an online adaptive plan. Methods: A systematic search of the literature was conducted within Pubmed/Medline databases to find relevant studies. Of the 152 articles fulfilling the initial search criteria, 79 were selected for final analysis. Results: The frequency of image guidance, the treatment regimen and the radiation technique are important factors that contribute to the optimization and personalization of the treatment plan. The daily anatomy and volume of the bladder and rectum can vary considerably, which can significantly impact the dosimetric effects on these organs. When used in conjunction with volumetric modulated arc therapy, IGRT allows for shaping the dose distribution to avoid nearby critical structures such as the bladder and rectum. Conclusions: Precise tumor targeting via IGRT can result in fewer geometric uncertainties, thereby improving treatment outcome both in terms of superior target coverage and sparing organs at risk. Full article

Epidemiological studies report inconsistent findings regarding the association between dietary polyunsaturated fatty acid (PUFA) intake and cancer risk. Genetic variations—particularly single-nucleotide polymorphisms (SNPs) in the FADS1 and FADS2 genes—affect PUFA metabolism, linking circulating PUFA levels to the risk of several cancers, including breast, colorectal, prostate, and pancreatic cancers. This review aimed to investigate the relationship between FADS1 and FADS2 gene variants and dietary intake, supplementation, or intervention with omega-3 fatty acids, gamma-linolenic acid (GLA), or their combination in cancer patients. A secondary objective was to examine genetically determined fatty acid profiles—shaped by FADS1 and FADS2 polymorphisms—in cancer patients without intervention and their potential association with PUFA-related cancer risk. A systematic search of the Scopus, PubMed, and Web of Science databases (up to 2024) identified 11 eligible studies out of 298 initial records. Analysis of the available literature suggests that specific FADS genotypes influence long-chain PUFA (LC-PUFA) concentrations in blood and tissues and that altered LC-PUFA levels may contribute to cancer development. The most consistent association identified is between the rs174537 variant and altered PUFA metabolism in prostate and breast cancer. However, conclusive evidence is lacking on the impact of dietary patterns on FADS desaturase activity or expression. Only one study has examined omega-3 supplementation in relation to FADS gene variants in prostate cancer patients, while the effects of GLA supplementation remain unexplored. Given the relative novelty of this research area and the limited number of studies, future investigations should integrate dietary PUFA intake, genetic variation in PUFA-metabolizing enzymes, and potential gene–nutrient interactions involving FADS gene polymorphisms and PUFAs to clarify their role in cancer risk. Full article

Background: Nuclei segmentation is the first stage of automated microscopic image analysis. The cell nucleus is a crucial aspect in segmenting to gain more insight into cell characteristics and functions that enable computer-aided pathology for early disease detection, such as prostate cancer, breast cancer, brain tumors, and other diagnoses. Nucleus segmentation remains a challenging task despite significant advancements in automated methods. Traditional techniques, such as Otsu thresholding and watershed approaches, are ineffective in challenging scenarios. However, deep learning-based methods exhibit remarkable results across various biological imaging modalities, including computational pathology. Methods: This work explores machine learning approaches for nuclei segmentation by evaluating the quality of nuclei image segmentation. We employed several methods, including K-means clustering, Random Forest (RF), Support Vector Machine (SVM) with handcrafted features, and Logistic Regression (LR) using features derived from Convolutional Neural Networks (CNNs). Handcrafted features extract attributes like the shape, texture, and intensity of nuclei and are meticulously developed based on specialized knowledge. Conversely, CNN-based features are automatically acquired representations that identify complex patterns in nuclei images. To assess how effectively these techniques segment cell nuclei, their performance is evaluated. Results: Experimental results show that Logistic Regression based on CNN-derived features outperforms the other techniques, achieving an accuracy of 96.90%, a Dice coefficient of 74.24, and a Jaccard coefficient of 55.61. In contrast, the Random Forest, Support Vector Machine, and K-means algorithms yielded lower segmentation performance metrics. Conclusions: The conclusions suggest that leveraging CNN-based features in conjunction with Logistic Regression significantly enhances the accuracy of cell nuclei segmentation in pathological images. This approach holds promise for refining computer-aided pathology workflows, potentially leading to more reliable and earlier disease diagnoses. Full article

In the context of the global food system transformation towards sustainable and healthy diets, risk–benefit assessment supported by quantitative dose–response relationships between nutrients and health outcomes is crucial for evaluating the public health impact of dietary modifications, particularly those involving novel foods. The primary aim of this review was to establish a foundational basis for RBA by compiling and synthesising quantitative dose–response relationships identified through a comprehensive literature review. This review encompassed the last 15 years up to March 2025, utilising databases such as PubMed, Scopus, and Web of Science. This review prioritised recent meta-analyses of observational studies and randomised controlled trials with a low risk of bias, as assessed using the ROBIS tool. This review identified significant dose–response relationships across 12 nutrients and their associations with various health outcomes. While dietary fibre has demonstrated broad protective effects, cereal fibre has been found to be the most beneficial for colorectal cancer prevention. Calcium has been shown to have inverse associations with several cancers, although high dairy intake may increase the risk of prostate cancer. Haem iron was linked to an increased risk of several chronic diseases, whereas non-haem iron showed less consistent associations. Zinc exhibited a potential U-shaped relationship with colorectal cancer risk. These findings underscore the complexity of nutrient–health relationships, highlighting the importance of considering dose–response gradients and nutrient sources. Although this overview primarily summarises quantitative associations without exploring in-depth mechanistic or population-specific details, it underscores the complexity of nutrient effects, including nonlinearity and source dependency. This analysis offers a valuable foundation for future risk–benefit assessments of various food scenarios, thereby informing dietary recommendations and public health strategies. Full article

Untapped bioactive compounds from microbial endophytes offer a promising solution to counter antimicrobial and chemotherapeutic drug resistance when complexed as silver nanoparticles (AgNPs). AgNPs were biosynthesized using cell-free supernatants from endophytic Streptomyces sp. KE4D and Bacillus safensis KE4K isolated from the Kenyan medicinal plant Teclea nobilis, following fermentation in three different media. Bacterial extracts were analyzed using gas chromatography–mass spectrometry. AgNPs were characterized using Fourier-transform infrared spectroscopy and high-resolution transmission electron microscopy. Antimicrobial activity was assessed using agar well diffusion assays, and quorum sensing inhibition (QSI) was investigated using Chromobacterium violaceum. Anti-cancer potential was evaluated against breast (MCF-7) and prostate cancer (DU-145) cell lines using MTT assays. AgNPs were 5–55 nm in size, with KE4D AgNPs being spherical and KE4K AgNPs exhibiting various shapes. Cyclopropane acetic acids and fatty acids were identified as possible capping agents. Medium-dependent antimicrobial activity was observed, with medium Mannitol and medium 5294 AgNPs displaying stronger activity, particularly against Gram-negative indicators. KE4D medium 5294 AgNPs demonstrated 85.12% violacein inhibition at 140 µg/mL and better QSI activity, whilst KE4K AgNPs were better antimicrobials. The AgNPs IC₅₀ values were <3.5 µg/mL for MCF-7 and <2.5 µg/mL for DU-145 cells. The bioactivity of biosynthesized AgNPs is influenced by the bacterial isolate and fermentation medium, suggesting that AgNP synthesis can be tailored for specific bioactivity. Full article

Background/Objectives: Locoregional therapies (LRTs), including transarterial embolization (TAE), transarterial chemoembolization (TACE), and transarterial radioembolization (TARE), have become integral in the management of hepatocellular carcinoma (HCC) in recent decades and continue to shape evolving treatment strategies. While their role in liver tumor management is well established, their potential for treating extrahepatic malignancies is gaining increasing attention. Notably, growing research has highlighted the promising applications of TAE, TACE, and TARE in extrahepatic cancers such as glioblastoma (GBM), soft tissue sarcomas (STSs), prostate cancer (PCa), pancreatic cancer, and renal cell carcinoma (RCC). This review aims to explore these novel applications, providing a comprehensive summary of the current literature, examining clinical outcomes, and discussing future directions for integrating these techniques into broader oncologic treatment strategies. Methods: A systematic literature review was conducted focusing on LRTs such as TAE, TACE, and TARE in extrahepatic malignancies. Studies published between May 1998 and December 2024 were included, emphasizing outcomes in GBM, STS, PCa, pancreatic cancer, and RCC. Data extraction prioritized clinical outcomes, safety profiles, and procedural efficacy. Results: LRTs demonstrated significant potential in managing extrahepatic malignancies, with TAE, TACE, and TARE showing promising results in palliative management and tumor control. Across studies, these therapies exhibited varying degrees of success in improving progression-free survival and overall survival, with minimal systemic toxicity. Conclusions: The expanding application of LRTs in extrahepatic malignancies highlights their transformative potential in interventional oncology. By offering targeted, minimally invasive treatment options, these modalities bridge critical gaps in managing tumors refractory to conventional therapies. Future research should focus on standardizing protocols, optimizing patient selection, and exploring combination therapies to maximize their clinical efficacy. Full article

Objective: This study evaluates the accuracy of a Machine Learning model of Random Forest (RF) type, using MRI data and radiomic features to predict lymph node involvement in prostate cancer (PCa). Methods: Ninety-five patients who underwent mp-MRI, prostatectomy, and lymphadenectomy at the Fondazione Policlinico Campus Bio-medico Radiological Department from 2016 to 2022 were analyzed. Radiomic features were extracted from T2-weighted, DWI, and ADC sequences and processed using a Random Forest (RF) model. Clinical data such as PSA levels and Gleason scores were also considered. Results: The RF model demonstrated significant accuracy in predicting lymph node involvement, achieving 84% accuracy for nodules in the peripheral zone (80% for predicting positive lymph node involvement and 85% for negative lymph node involvement) and 87% for those in the transitional zone (86% for predicting positive lymph node involvement and 88% for negative lymph node involvement). In the peripheral zone, key features included ADC shape maximum 2D diameter row and T2 noduloglcm difference variance, while in the transitional zone, DWI glcm difference average and DWI glcm Idm were important. DWI and ADC sequences were particularly crucial for accurate lymph node assessment. First-order features emerged as the most significant in whole-gland analysis, indicating fundamental differences in tumor composition and density critical for identifying malignancies with higher metastatic potential. Conclusions: AI-driven radiomic analysis, especially using DWI- and ADC-derived features, effectively predicts lymph node involvement in PCa patients, in particular in negative linfonode status patients, offering a promising tool for preoperative linfonode sparing patient selection. Further validation with larger cohorts is needed. Some limitations of this study are a relatively small sample size and it being a retrospective study. Full article

Cancer ranks among the top causes of illness and death globally. Nanotechnology holds considerable promise for enhancing the effectiveness of therapeutic and diagnostic approaches in cancer treatment. Our study presents a promising strategy for applying thiocompound nanomedicine in cancer therapy. Our first study aimed to investigate the biological properties of a new compound thiodiosgenin (TDG)—a new derivative of diosgenin—a natural compound with known antioxidant and anticancer properties. Our current second study aimed to compare the therapeutic efficacy of a new diosgenin—functionalized gold nanoparticles—with its precursor on prostate cancer (DU-145) cell lines. Moreover, the safety of the new thio-derivative and new conjugates was tested against the human epithelial line PNT-2. New advanced analytical techniques were developed for the characterization of nanomaterials using methods such as SP-ICP-MS, UV-Vis, TEM, NMR, FT-IR ELS, and TGA. Our synthetic approach was based, on the one hand, on the ligand exchange of citrates to thiodiosgenin (TDG) on gold nanoparticles, and on the other hand, on the attachment of DG through an ester bond to the linker, which was 3-mercaptopropionic acid (MPA) on gold nanoparticles. Initial in vitro studies indicate that TDG shows greater cytotoxic effects on cancer cells but poses risks to normal prostate epithelial cells (PNT-2). It was demonstrated that all the conjugates produced exhibited significant cytotoxic effects against cancer cells while being less harmful to normal prostate epithelial cells (PNT-2) compared to TDG itself. All the obtained conjugates showed antitumor properties; however, for targeted transport, the system referred to as AuNPs-MPAm1-DG is promising, due to the size of the nanoparticles of 53 nm, zeta potential of -30 mV, and loading content of 27.6%. New methods for synthesizing conjugates with diosgenin were developed and optimized for medical applications. Advanced new analytical methodologies were developed to characterize new conjugates, particularly the use of SP-ICP-MS, to solve existing differences in the shape and morphology of the surface of new conjugates. Full article

Oligometastatic prostate cancer (OMPC) represents an intermediate state in the progression from localized disease to widespread metastasis when the radiographically significant sites are limited in number and location. With no clear consensus on a definition, its diagnostic significance and associated optimal therapeutic approach remain controversial, posing a significant challenge for clinicians. The current standard of care for metastatic disease is to start systemic therapy; however, active surveillance and targeted radiotherapy have become attractive options to mitigate the long-term effects of androgen deprivation therapy (ADT). Furthermore, evolving biomarker methodologies may further define optimal treatment selection. In this review, we summarize the current understanding that guides the treatment of OMPC, with a focus on how host response can be an important contributing factor. Evolving scientific understanding and clinical development will continue to shape the landscape of treatment strategies for this distinct disease state. Full article

The gut microbiome is essential for regulating host metabolism, defending against pathogens, and shaping the host’s immune system. Mounting evidence highlights that disruption in gut microbial communities significantly impacts cancer development and treatment. Moreover, tumor-associated microbiota, along with its metabolites and toxins, may contribute to cancer progression by promoting epithelial-to-mesenchymal transition, angiogenesis, and metastatic spread to distant organs. Bones, in particular, are common sites for metastasis due to a rich supply of growth and neovascularization factors and extensive blood flow, especially affecting patients with thyroid, prostate, breast, lung, and kidney cancers, where bone metastases severely reduce the quality of life. While the involvement of the gut microbiome in bone metastasis formation is still being explored, proposed mechanisms suggest that intestinal dysbiosis may alter the bone microenvironment via the gut-immune-bone axis, fostering a premetastatic niche and immunosuppressive milieu suitable for cancer cell colonization. Disruption in the delicate balance of bone modeling and remodeling may further create a favorable environment for metastatic growth. This review focuses on the link between beneficial or dysbiotic microbiome composition and bone homeostasis, as well as the role of the microbiome in bone metastasis development. It also provides an overview of clinical trials evaluating the impact of gut microbial community structure on bone parameters across various conditions or health-related issues. Dietary interventions and microbiota modulation via probiotics, prebiotics, and fecal microbiota transplantation help support bone health and might offer promising strategies for addressing bone-related complications in cancer. Full article

The aim of the study is to formulate an injectable nanocrystalline suspension (NS) of dutasteride (DTS), a hydrophobic 5α-reductase inhibitor used to treat benign prostatic hyperplasia and scalp hair loss, for parenteral long-acting delivery. A DTS-loaded NS (DTS-NS, 40 mg/mL DTS) was prepared using a lab-scale bead-milling technique. The optimized DTS-NS prepared using Tween 80 (0.5% w/v) as a nano-suspending agent, was characterized as follows: rod/rectangular shape; particle size of 324 nm; zeta potential of −11 mV; and decreased drug crystallinity compared with intact drug powder. The DTS-NS exhibited a markedly protracted drug concentration-time profile following intramuscular injection, reaching a maximum concentration after 8.40 days, with an elimination half-life of 9.94 days in rats. Histopathological observations revealed a granulomatous inflammatory response at the injection site 7 days after intramuscular administration, which significantly subsided by day 14 and showed minimal inflammation by day 28. These findings suggest that the nanosuspension system is a promising approach for the sustained release parenteral DTS delivery, with a protracted pharmacokinetic profile and tolerable local inflammation. Full article