Data analysis with limited data availability: prostate cancer prediction and characterization as a case study

Research studies conducted on limited datasets (i.e., data from tens to maximum hundreds of observations) may be the only practical option for many research areas, as data collection might be costly, complex, or both. Data analysis on these datasets is challenging as it can lead to inaccurate results. In this thesis, we addressed this challenge in the context of prostate cancer research by empirically assessing the predictive and characterization capabilities of attributes with the following objectives: to evaluate the predictive power of features extracted from prostate magnetic resonance imaging (MRI) using cross-validation techniques, to develop and evaluate a cross-validation method for small sample sizes that allow receiver operating characteristic (ROC) analysis, and to identify and compare relevant predictors among MRI features, clinical variables, gene expressions, and kallikreins for prostate cancer detection and stratification. To achieve these objectives, we used data from approved studies and registered clinical trials at Turku University Hospital, involving a strong collaboration between university departments and hospitals. This collaboration enabled the collection of diverse, high-quality features to enhance prostate cancer diagnosis and prognosis research. The results of this thesis can be summarized as follows. First, when evaluating radiomic features from various MRI modalities, our findings demonstrate the potential that these features have in stratifying prostate tumors into low- and highrisk. Second, in terms of model evaluation using ROC analysis and cross-validation, our research highlights a significant negative bias in the area under the ROC curve when estimated by leave-one-out (LOOCV) and introduces a novel cross-validation method called tournament leave-pair-out (TLPOCV) as a more reliable method for ROC analysis than LOOCV. Finally, our results provide empirical evidence of the predictive potential that quantitative and qualitative features from MRI, clinical variables, gene expressions, and kallikreins—individually and in combination—have in detecting and stratifying prostate cancer. The findings in this research are of interest not only to medical professionals and healthcare providers engaged in prostate cancer research but also to those involved in analyzing and learning from size-constrained datasets while achieving clinically meaningful evaluation outcomes

Quicksort leave-pair-out cross-validation for ROC curve analysis

Receiver Operating Characteristic (ROC) curve analysis and area under the ROC curve (AUC) are commonly used performance measures in diagnostic systems. In this work, we assume a setting, where a classifier is inferred from multivariate data to predict the diagnostic outcome for new cases. Cross-validation is a resampling method for estimating the prediction performance of a classifier on data not used for inferring it. Tournament leave-pair-out (TLPO) cross-validation has been shown to be better than other resampling methods at producing a ranking of data that can be used for estimating the ROC curves and areas under them. However, the time complexity of TLPOCV, O(n(2)), means that it is impractical in many applications. In this article, a method called quicksort leave-pair-out cross-validation (QLPOCV) is presented in order to decrease the time complexity of obtaining a reliable ranking of data to O(n log n). The proposed method is compared with existing ones in an experimental study, demonstrating that in terms of ROC curves and AUC values QLPOCV produces as accurate performance estimation as TLPOCV, outperforming both k-fold and leave-one-out cross-validation

Symptoms and diagnostic delays in bladder cancer with high risk of recurrence : results from a prospective FinnBladder 9 trial

Purpose To investigate the symptoms and delays in the clinical pathway of bladder cancer (BC). Methods This is a substudy of a prospective, randomized, multicenter phase III study (FinnBladder 9, NCT01675219) where the efficacy of photodynamic diagnosis and 6 weekly optimized mitomycin C instillations are studied in pTa bladder cancer with high risk for recurrence. The data of presenting symptoms and critical time points were prospectively collected, and the effect of factors on delays was analyzed. Results At the time of analysis, 245 patients were randomized. Analysis included 131 patients with primary bladder cancer and their complete data. Sixty-nine percent had smoking history and 67% presented with macroscopic hematuria. Median patient delay (from symptoms to health-care contact) was 7 days. The median general practice delay (from health-care contact to urology referral) was 8 days. Median time from urology referral to cystoscopy was 23 days and from cystoscopy to TUR-BT 21 days. Total time used in the clinical pathway (from symptom to TUR-BT) was 78 days. Current and former smokers had non-significantly shorter patient-related and general practice delays compared to never smokers. TUR-BT delay was significantly shorter in patients with malignant cytology (16 days) compared to patients with benign cytology (21 days, p = 0.03). Conclusions Patient-derived delay was short and most of the delay occurred in the referral centers. The majority had macroscopic hematuria as the initial symptom. Surprisingly, current and past smokers were more prone to contact the health-care system compared to never smokers.Peer reviewe

Correlation between 18F-1-amino-3-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) uptake and expression of alanine-serine-cysteine-transporter 2 (ASCT2) and L-type amino acid transporter 1 (LAT1) in primary prostate cancer

Purpose: To evaluate the expression of alanine-serine-cysteine-transporter 2 (ASCT2) and L-type amino acid transporter1 (LAT1) in prostate cancer (PCa) and their impact on uptake of F-18-1-amino-3-fluorocyclobutane-1-carboxylic acid (F-18-fluciclovine) which is approved for the detection of recurrent PCa.Methods: Twenty-five hormone-naive patients with histologically confirmed PCa underwent PET/CT before prostatectomy. Dynamic imaging was performed immediately after injection of 368 +/- 10 MBq of F-18-fluciclovine and the uptake in PCa was expressed as SUVmax at six sequential 4-min time frames and as tracer distribution volume (V-T) using Logan plots over 0-24 min. The expression of ASCT2 and LAT1 was studied with immunohistochemistry (IHC) on a tissue microarray (TMA) containing three cores per carcinoma lesion. The TMA slides were scored independently by two trained readers based on visual intensity of ASCT2/LAT1 expression on a four-tiered scale. The correlations between ASCT2/LAT1 staining intensity, SUVmax/V-T, and Gleason grade group (GGG) were assessed using Spearman's rank correlation coefficient (rho).Results: Forty tumor foci (>0.5 mm in diameter, max. 3 per patient) were available for TMA. In visual scoring, low, moderate, and high staining intensity of ASCT2 was observed in 4 (10%), 24 (60%), and 12 (30%) tumors, respectively. No tumors showed high LAT1 staining intensity while moderate intensity was found in 10 (25%), 25 (63%) showed low, and the remaining 5 (12%) were negative for staining with LAT1. Tumors with GGG >2 showed significantly higher uptake of F-18-fluciclovine and higher LAT1 staining intensity (pConclusions: Our findings suggest that LAT1 is moderately associated with the transport of F-18-fluciclovine in local PCa not exposed to hormonal therapy. Both high and low Gleason grade tumors express ASCT2 while LAT1 expression is less conspicuous and may be absent in some low-grade tumors. Our observations may be of importance when using F-18-fluciclovine imaging in the planning of focal therapies for PCa.</p

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization

Purpose To develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w), diffusion weighted imaging (DWI) acquired using high b values, and T2-mapping (T2). Methods T2w, DWI (12 b values, 0–2000 s/mm2), and T2 data sets of 62 patients with histologically confirmed PCa were acquired at 3T using surface array coils. The DWI data sets were post-processed using monoexponential and kurtosis models, while T2w was standardized to a common scale. Local statistics and 8 different radiomics/texture descriptors were utilized at different configurations to extract a total of 7105 unique per-tumor features. Regularized logistic regression with implicit feature selection and leave pair out cross validation was used to discriminate tumors with 3+3 vs >3+3 GS. Results In total, 100 PCa lesions were analysed, of those 20 and 80 had GS of 3+3 and >3+3, respectively. The best model performance was obtained by selecting the top 1% features of T2w, ADCm and K with ROC AUC of 0.88 (95% CI of 0.82–0.95). Features from T2 mapping provided little added value. The most useful texture features were based on the gray-level co-occurrence matrix, Gabor transform, and Zernike moments. Conclusion Texture feature analysis of DWI, post-processed using monoexponential and kurtosis models, and T2w demonstrated good classification performance for GS of PCa. In multisequence setting, the optimal radiomics based texture extraction methods and parameters differed between different image types. </div

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins : A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer

Background Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group >= 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI). Purpose To develop and validate radiomics and kallikrein models for the detection of csPCa. Study Type Retrospective. Population A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated. Field strength/Sequence A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI. Assessment In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores. Statistical Tests For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant. Results The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488). Data Conclusion The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains. Level of Evidence 1 Technical Efficacy Stage 2Peer reviewe

Individualised non-contrast MRI-based risk estimation and shared decision-making in men with a suspicion of prostate cancer : Protocol for multicentre randomised controlled trial (multi-IMPROD V.2.0)

Introduction European Association of Urology and UK National Institute for Health and Care Excellence guidelines recommend that all men with suspicions of prostate cancer should undergo prebiopsy contrast enhanced, that is, multiparametric prostate MRI. Subsequent prostate biopsies should also be performed if MRI is positive, that is, Prostate Imaging-Reporting and Data System (PI-RADS) scores 3-5. However, several retrospective post hoc analyses have shown that this approach still leads to many unnecessary biopsy procedures. For example, 88%-96% of men with PI-RADS, three findings are still diagnosed with clinically non-significant prostate cancer or no cancer at all. Methods and analysis This is a prospective, randomised, controlled, multicentre trial, being conducted in Finland, to demonstrate non-inferiority in clinically significant cancer detection rates among men undergoing prostate biopsies post-MRI and men undergoing prostate biopsies post-MRI only after a shared decision based on individualised risk estimation. Men without previous diagnosis of prostate cancer and with abnormal digital rectal examination findings and/or prostate-specific antigen between 2.5 ug/L and 20.0 ug/L are included. We aim to recruit 830 men who are randomised at a 1:1 ratio into control (all undergo biopsies after MRI) and intervention arms (the decision to perform biopsies is based on risk estimation and shared decision-making). The primary outcome of the study is the proportion of men with clinically significant prostate cancer (Gleason 4+3 prostate cancer or higher). We will also compare the overall biopsy rate, benign biopsy rate and the detection of non-significant prostate cancer between the two study groups. Ethics and dissemination The study (protocol V.2.0, 4 January 2021) was approved by the Ethics Committee of the Hospital District of Southwest Finland (IORG number: 0001744, IBR number: 00002216; trial number: 99/1801/2019). Participants are required to provide written informed consent. Full reports of this study will be submitted to peer-reviewed journals, mainly urology and radiology. Trial registration number NCT04287088; the study is registered at ClinicalTrials.gov.publishedVersionPeer reviewe

Individualised non-contrast MRI-based risk estimation and shared decision-making in men with a suspicion of prostate cancer: protocol for multicentre randomised controlled trial (multi-IMPROD V.2.0)

Introduction European Association of Urology and UK National Institute for Health and Care Excellence guidelines recommend that all men with suspicions of prostate cancer should undergo prebiopsy contrast enhanced, that is, multiparametric prostate MRI. Subsequent prostate biopsies should also be performed if MRI is positive, that is, Prostate Imaging-Reporting and Data System (PI-RADS) scores 3-5. However, several retrospective post hoc analyses have shown that this approach still leads to many unnecessary biopsy procedures. For example, 88%-96% of men with PI-RADS, three findings are still diagnosed with clinically non-significant prostate cancer or no cancer at all.Methods and analysis This is a prospective, randomised, controlled, multicentre trial, being conducted in Finland, to demonstrate non-inferiority in clinically significant cancer detection rates among men undergoing prostate biopsies post-MRI and men undergoing prostate biopsies post-MRI only after a shared decision based on individualised risk estimation. Men without previous diagnosis of prostate cancer and with abnormal digital rectal examination findings and/or prostate-specific antigen between 2.5 ug/L and 20.0 ug/L are included. We aim to recruit 830 men who are randomised at a 1:1 ratio into control (all undergo biopsies after MRI) and intervention arms (the decision to perform biopsies is based on risk estimation and shared decision-making). The primary outcome of the study is the proportion of men with clinically significant prostate cancer (Gleason 4+3 prostate cancer or higher). We will also compare the overall biopsy rate, benign biopsy rate and the detection of non-significant prostate cancer between the two study groups.Ethics and dissemination The study (protocol V.2.0, 4 January 2021) was approved by the Ethics Committee of the Hospital District of Southwest Finland (IORG number: 0001744, IBR number: 00002216; trial number: 99/1801/2019). Participants are required to provide written informed consent. Full reports of this study will be submitted to peer-reviewed journals, mainly urology and radiology.</p