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To further investigate the utility of bpMRI and work towards improved prostate cancer screening protocols, we propose a pilot study which utilizes bpMRI in conjunction with PSA in the early detection of clinically significant prostate cancer in a high-risk group. Our study would focus on these high-risk patients between the ages of 40-55 with a normal PSA ranging from ≥1.0 to <2.5 ng/mL. bpMRI would be obtained in this group and if any suspicious lesions are found, the recommendation is to undergo MRI/US fusion biopsy. Patients with negative bpMRI will be followed every year with serum PSA. Patients with a positive bpMRI will have a prostate fusion and systematic biopsy performed. Those with a benign biopsy will be followed every year with serum PSA. Those who have a biopsy positive for cancer will be followed according to the standard of care. Our hypothesis is that bpMRI in conjunction with above average PSA in a high-risk group will increase detection of clinically relevant prostate cancer and provide a useful addition to PSA screening.
In Europe, prostate cancer (PCa) is the second most frequent type of cancer in men and the third most lethal. Current clinical practices, often leading to overdiagnosis and overtreatment of indolent tumors, suffer from lack of precision calling for advanced AI models to go beyond SoA by deciphering non-intuitive, high-level medical image patterns and increase performance in discriminating indolent from aggressive disease, early predicting recurrence and detecting metastases or predicting effectiveness of therapies. To date efforts are fragmented, based on single-institution, size-limited and vendorspecific datasets while available PCa public datasets (e.g. US TCIA) are only few hundred cases making model generalizability impossible. The ProCAncer-I project brings together 20 partners, including PCa centers of reference, world leaders in AI and innovative SMEs, with recognized expertise in their respective domains, with the objective to design, develop and sustain a cloud based, secure European Image Infrastructure with tools and services for data handling. The platform hosts the largest collection of PCa multi-parametric (mp)MRI, anonymized image data worldwide (>17,000 cases), based on data donorship, in line with EU legislation (GDPR). Robust AI models are developed, based on novel ensemble learning methodologies, leading to vendor-specific and -neutral AI models for addressing 8 PCa clinical scenarios. To accelerate clinical translation of PCa AI models, we focus on improving the trust of the solutions with respect to fairness, safety, explainability and reproducibility. Metrics to monitor model performance and a causal explainability functionality are developed to further increase clinical trust and inform on possible failures and errors. A roadmap for AI models certification is defined, interacting with regulatory authorities, thus contributing to a European regulatory roadmap for validating the effectiveness of AI-based models for clinical decision making.
This clinical trial will evaluate the safety of Radium-223 in combination with 177Lu-PSMA-I&T in metastatic castration-resistant prostate cancer: Phase I/II study
Worldwide, prostate cancer is the most commonly diagnosed male cancer and the fourth leading cause of cancer death in men. Risk stratification is according to cancer stage, Gleason score, and PSA level . Definitive treatment of localized disease ( low and favorable intermediate risk) includes watchful waiting , active surveillance , radiation therapy , radical prostatectomy and cryotherapy .Primary treatment of unfavorable intermediate risk , high risk localized disease and locally advanced prostate cancer , includes both radical prostatectomy (RP) and EBRT + long-term androgen deprivation therapy (ADT) .Treatment options of metastatic prostate cancer include pain medications, bisphosphonates, hormonal treatment, chemotherapy, radiotherapy, immunotherapy, focused radiation, and other targeted therapies .
The purpose of this study is to quantify and publish participants' relative preferences for outcomes of chemotherapy and novel oral hormonal agents when added to androgen deprivation therapy (ADT) for participants with locally-advanced and metastatic hormone-sensitive prostate cancer (mHSPC). This study will also quantify the importance of administration factors related to convenience relative to treatment outcomes.
In this study, 288 patients will be randomized 1:1 to either having only the standard of care MRI prior to surgery versus having the standard of care MRI and the PSMA PET scan. PET (and MRI) findings will be validated against whole mount pathology. Pre-surgical imaging findings will also be evaluated in the context of affecting subsequent surgical plans and impacting actual patient outcomes.
Currently, in the clinical landscape of PCa, much of the AI work is limited to single-centre, single AI-architecture analyses and critically, on small data sets. ProCAncer-I will create a vast, diversified and multidisciplinary repository, fed by a large collection of mp-MRI. The participating clinical partners will congregate mp-MRI and clinical data, retrospectively and prospectively, from more than 17.000 PCa patients (11.000 retrospective and 6.000 prospective mp-MRI cases), including baseline examinations and follow up studies to form the ProstateNET dataset, counting more than 1.5 million image representations of the prostate (cancerous, non-cancerous and benign cases). ProCAncer-I aims to address the unmet clinical needs in PCa regarding precision diagnosis and personalised disease management with a disruptive paradigm change in clinical research, exploiting a novel multi centre collaboration, comprising a master-global model, boosted with MRI and AI modelling methodology. ProCAncer-I will deal with both retrospective and prospective data. Retrospective data will be collected and will be used to implement and train AI algorithms by other partners of the Consortium. Similarly, prospective data will be collected for the development of vendor specific models and external validation of AI models.
The aim of this study is to facilitate collection of real-world data to test and train the analytics engine for each prototype algorithm. Preliminary datasets will be generated to enable a dry run of the prototype algorithms to check their predictive functionality as part of simulated 'experimental' scenarios at each LifeChamps partner site. This preparatory work will be critical to the development of the LifeChamps platform, prior to progressing to a larger scale feasibility trial.
This study is to obtain acute dose safety and pharmacokinetics/pharmacodynamics (PK/PD) data in a dose-response trial in prostate cancer patients.
The AFFIRM trial tests the safety and clinical feasibility of MR-guided hypofractionated focal boost radiotherapy for patients with locally advanced prostate cancer. External beam radiotherapy combined with androgen deprivation therapy is considered as the treatment of choice for patients with locally advanced non-metastatic prostate cancer with seminal vesicle invasion.The long-term results of the multicentre phase III study (FLAME trial) showed that addition of an isotoxic focal boost to the intraprostatic lesion improves biochemical disease free survival in intermediate to high-risk patients without impacting toxicity and quality of life. This focal boost strategy is now proven for a conventional fractionation scheme (35 fractions). The current trend in radiotherapy for prostate cancer is (extreme) hypofractionation, reducing the number of fractions. For locally advanced prostate cancer, however, the data on extreme hypofractionation are scarce.