Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients

Objective: Artificial intelligence (AI) offers new opportunities for objective quantitative measurements of imaging biomarkers from positron-emission tomography/computed tomography (PET/CT). Clinical image reporting relies predominantly on observer-dependent visual assessment and easily accessible measures like SUVmax, representing lesion uptake in a relatively small amount of tissue. Our hypothesis is that measurements of total volume and lesion uptake of the entire tumour would better reflect the disease`s activity with prognostic significance, compared with conventional measurements. Methods: An AI-based algorithm was trained to automatically measure the prostate and its tumour content in PET/CT of 145 patients. The algorithm was then tested retrospectively on 285 high-risk patients, who were examined using 18F-choline PET/CT for primary staging between April 2008 and July 2015. Prostate tumour volume, tumour fraction of the prostate gland, lesion uptake of the entire tumour, and SUVmax were obtained automatically. Associations between these measurements, age, PSA, Gleason score and prostate cancer-specific survival were studied, using a Cox proportional-hazards regression model. Results: Twenty-three patients died of prostate cancer during follow-up (median survival 3.8 years). Total tumour volume of the prostate (p = 0.008), tumour fraction of the gland (p = 0.005), total lesion uptake of the prostate (p = 0.02), and age (p = 0.01) were significantly associated with disease-specific survival, whereas SUVmax (p = 0.2), PSA (p = 0.2), and Gleason score (p = 0.8) were not. Conclusion: AI-based assessments of total tumour volume and lesion uptake were significantly associated with disease-specific survival in this patient cohort, whereas SUVmax and Gleason scores were not. The AI-based approach appears well-suited for clinically relevant patient stratification and monitoring of individual therapy

Peri-prostatic fat volume measurement as a predictive tool for castration resistance in advanced prostate cancer

Background: Obesity and aggressive prostate cancer (PC) may be linked, but how local peri-prostatic fat relates to tumour response following androgen deprivation therapy (ADT) is unknown. Objective: To test if peri-prostatic fat volume (PPFV) predicts tumour response to ADT. Design, setting, and participants: We performed a retrospective study on consecutive patients receiving primary ADT. From staging pelvic magnetic resonance imaging scans, the PPFV was quantified with OsirixX 6.5 imaging software. Statistical (univariate and multivariate) analysis were performed using R Version 3.2.1. Results and limitations: Of 224 consecutive patients, 61 with advanced (≥T3 or N1 or M1) disease had (3-mm high resolution axial sections) pelvic magnetic resonance imaging scan before ADT. Median age = 75 yr; median PPFV = 24.8 cm3 (range, 7.4–139.4 cm3). PPFV was significantly higher in patients who developed castration resistant prostate cancer (CRPC; n = 31), with a median of 37.9 cm3 compared with 16.1 cm3 (p < 0.0001, Wilcoxon rank sum test) in patients who showed sustained response to ADT (n = 30). Multivariate analysis using Cox proportional hazards models were performed controlling for known predictors of CRPC. PPFV was shown to be independent of all included factors, and the most significant predictor of time to CRPC. Using our multivariate model consisting of all known factors prior to ADT, PPFV significantly improved the area under the curve of the multivariate models receiver operating characteristic analysis. The main study limitation is a relatively small cohort to account for multiple variables, necessitating a future large-scale prospective analysis of PPFV in advanced PC. Conclusions: PPFV quantification in patients with advanced PC predicts tumour response to ADT

Deep learning-based quantification of PET/CT prostate gland uptake: association with overall survival

Aim: To validate a deep-learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. Material and methods: Training of the DL-algorithm regarding prostate volume was performed on manually segmented CT images in 100 patients. Validation of the DL-algorithm was carried out in 45 patients with biopsy-proven hormone-na\uefve prostate cancer. The automated measurements of prostate volume were compared with manual measurements made independently by two observers. PET/CT measurements of tumour burden based on volume and SUV of abnormal voxels were calculated automatically. Voxels in the co-registered 18F-choline PET images above a standardized uptake value (SUV) of 2\ub765, and corresponding to the prostate as defined by the automated segmentation in the CT images, were defined as abnormal. Validation of abnormal voxels was performed by manual segmentation of radiotracer uptake. Agreement between algorithm and observers regarding prostate volume was analysed by S\uf8rensen-Dice index (SDI). Associations between automatically based PET/CT biomarkers and age, prostate-specific antigen (PSA), Gleason score as well as overall survival were evaluated by a univariate Cox regression model. Results: The SDI between the automated and the manual volume segmentations was 0\ub778 and 0\ub779, respectively. Automated PET/CT measures reflecting total lesion uptake and the relation between volume of abnormal voxels and total prostate volume were significantly associated with overall survival (P\ua0=\ua00\ub702), whereas age, PSA, and Gleason score were not. Conclusion: Automated PET/CT biomarkers showed good agreement to manual measurements and were significantly associated with overall survival

Mechanical suppression of osteolytic bone metastases in advanced breast cancer patients: A randomised controlled study protocol evaluating safety, feasibility and preliminary efficacy of exercise as a targeted medicine

Background: Skeletal metastases present a major challenge for clinicians, representing an advanced and typically incurable stage of cancer. Bone is also the most common location for metastatic breast carcinoma, with skeletal lesions identified in over 80% of patients with advanced breast cancer. Preclinical models have demonstrated the ability of mechanical stimulation to suppress tumour formation and promote skeletal preservation at bone sites with osteolytic lesions, generating modulatory interference of tumour-driven bone remodelling. Preclinical studies have also demonstrated anti-cancer effects through exercise by minimising tumour hypoxia, normalising tumour vasculature and increasing tumoural blood perfusion. This study proposes to explore the promising role of targeted exercise to suppress tumour growth while concomitantly delivering broader health benefits in patients with advanced breast cancer with osteolytic bone metastases. Methods: This single-blinded, two-armed, randomised and controlled pilot study aims to establish the safety, feasibility and efficacy of an individually tailored, modular multi-modal exercise programme incorporating spinal isometric training (targeted muscle contraction) in 40 women with advanced breast cancer and stable osteolytic spinal metastases. Participants will be randomly assigned to exercise or usual medical care. The intervention arm will receive a 3-month clinically supervised exercise programme, which if proven to be safe and efficacious will be offered to the control-arm patients following study completion. Primary endpoints (programme feasibility, safety, tolerance and adherence) and secondary endpoints (tumour morphology, serum tumour biomarkers, bone metabolism, inflammation, anthropometry, body composition, bone pain, physical function and patient-reported outcomes) will be measured at baseline and following the intervention. Discussion: Exercise medicine may positively alter tumour biology through numerous mechanical and nonmechanical mechanisms. This randomised controlled pilot trial will explore the preliminary effects of targeted exercise on tumour morphology and circulating metastatic tumour biomarkers using an osteolytic skeletal metastases model in patients with breast cancer. The study is principally aimed at establishing feasibility and safety. If proven to be safe and feasible, results from this study could have important implications for the delivery of this exercise programme to patients with advanced cancer and sclerotic skeletal metastases or with skeletal lesions present in haematological cancers (such as osteolytic lesions in multiple myeloma), for which future research is recommended. Trial registration: anzctr.org.au, ACTRN-12616001368426. Registered on 4 October 2016

Vinorelbine-based chemotherapy in hormone refractory prostate cancer

Background: No consensus exists regarding further therapy for the management of hormone-refractory prostate cancer. In this phase II study, the combination of Vinorelbine with 5-Fluorouracil and folinic acid (FLN regimen) was evaluated in patients with progressive or resistant disease after hormone therapy. Patients and Methods: Thirty-four patients were treated with Vinorelbine at a dose of 20 mg/m 2 intravenously (i.v.) on days 1 and 3, folinic acid (FA), 100 mg/m 2 i.v. and 5-Fluorouracil (5-FU), 350 mg/m 2 i.v. as a short infusion on days 1 to 3. The therapy was given in an out-patient setting, every 3 weeks. Results: All of the 34 eligible patients were evaluable for toxicity and 30 for activity. A total of 127 cycles was administered (91% at full dose). Among the 15 patients with measurable disease, four had a partial response (26.6%; C.I. 95%, 28.3% to 65.7%) and four achieved stable disease. In 14 patients (47%) a clinical benefit was documented. Six out of 15 patients with bone-only involvement had stable disease (40%). The median duration of stabilization and partial response was 16 weeks (range 4-24 weeks). The most common toxicity was hematological: Grade 4 (NCI-CTC scale) in five patients at re-cycle. Other toxicities were of low incidence and easy to manage. Conclusion: The encouraging results obtained with the FLN regimen in terms of clinical benefit and its predictable and manageable toxicity support the palliative role of this chemotherapeutic strategy in hormone-refractory prostate patients

Developing multiparametric and novel magnetic resonance imaging biomarkers for prostate cancer

Whilst biomarker research is gaining momentum within the cancer sciences, disappointingly few biomarkers are successfully translated into clinical practice, which is partly due to lack of rigorous methodology. In this thesis, I aim to systematically study several quantitative magnetic resonance imaging (MRI) biomarkers (QIBs), at various stages of biomarker development for use as tools in the assessment of local and metastatic prostate cancer according to clinical need. I initially focus on QIBs derived from conventional multiparametric (mp) prostate MRI sequences, namely T2 weighted (T2W), apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE). Firstly, by optimising analytical methods used throughout the thesis, deciding which approach is more reliable between single-slice region-of-interest vs. contouring the whole tumour volume using two different software packages. I then consider whether metric reproducibility can be improved by normalisation to different anatomical structures, and assess whether it is preferable to use statistics derived from imaging histograms rather than the current convention of using mean values. I combine multiple QIBs in a logistic regression model to predict a Gleason 4 component in known prostate cancer, which represents an unmet clinical need, as noninvasive tools to distinguish these more aggressive tumours do not currently exist. I subsequently ‘technically validate’ a novel microstructural diffusion-weighted MRI technique called VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours) to detect aggressive prostate cancer as part of a prospective cohort study. I assess the image quality, contrast-to-noise ratio, repeatability and performance of quantitative parametric VERDICT maps to discriminate between Gleason grades vs. the current best performing, but still imperfect tool of ADC. In the final two results chapters, motivated by the limited diagnostic accuracy of the prostate cancer staging modalities in current clinical use, I investigate the ability of mp whole-body (WB) MRI to stage aggressive cancer outside the prostate in patients with a high risk of metastases at primary diagnosis, and in biochemical failure following prostatectomy

Periprostatic fat measured on computed tomography as a marker for prostate cancer aggressiveness

Contains fulltext : 89797.pdf (publisher's version ) (Closed access)OBJECTIVE: Several reports found that obesity was associated with prostate cancer (PC) aggressiveness among men treated with radical prostatectomy or radiotherapy. Studies concerning this issue have basically relied on body mass index (BMI), as a marker for general obesity. Because visceral fat is the most metabolic active fat, we sought to evaluate if periprostatic fat measured on a computed tomography (CT) is a better marker than BMI to predict PC aggressiveness in a Dutch population who underwent brachytherapy for localized PC. PATIENTS AND METHODS: Of the 902 patients who underwent brachytherapy, 725 CT scans were available. Subcutaneous fat thickness (CFT), periprostatic fat area (cm(2)) and fat-density (%) were determined on the CT scan. Patients were stratified into three groups: 75 percentile of the fat-density. Associations between the three fat-density subgroups and BMI and PC aggressiveness were examined. RESULTS: 237 patients were classified as having normal weight (37.2%), 320 as overweight (50.2%) and 80 as obese (12.6%). There was a strong significant association between BMI and fat-density and CFT. The strongest correlation was seen between BMI and CFT (Pearson r coefficient = 0.71). Logistic regression analysis revealed no statistically significant association between the different fat measurements and the risk of having a high-risk disease. CONCLUSIONS: Periprostatic fat and fat-density as measured with CT were not correlated with PC aggressiveness in patients receiving brachytherapy. However, 31% of the patients with a normal BMI had a fat-density of >75 percentile of the periprostatic fat-density.01 december 201