Sampling the spatial patterns of cancer: Optimized biopsy procedures for estimating prostate cancer volume and Gleason Score

Prostate biopsy is the current gold-standard procedure for prostate cancer diagnosis. Existing prostate biopsy procedures have been mostly focusing on detecting cancer presence. However, they often ignore the potential use of biopsy to estimate cancer volume (CV) and Gleason Score (GS, a cancer grade descriptor), the two surrogate markers for cancer aggressiveness and the two crucial factors for treatment planning. To fill up this vacancy, this paper assumes and demonstrates that, by optimally sampling the spatial patterns of cancer, biopsy procedures can be specifically designed for estimating CV and GS. Our approach combines image analysis and machine learning tools in an atlas-based population study that consists of three steps. First, the spatial distributions of cancer in a patient population are learned, by constructing statistical atlases from histological images of prostate specimens with known cancer ground truths. Then, the optimal biopsy locations are determined in a feature selection formulation, so that biopsy outcomes (either cancer presence or absence) at those locations could be used to differentiate, at the best rate, between the existing specimens having different (high vs. low) CV/GS values. Finally, the optimized biopsy locations are utilized to estimate whether a new-coming prostate cancer patient has high or low CV/GS values, based on a binary classification formulation. The estimation accuracy and the generalization ability are evaluated by the classification rates and the associated receiver-operating-characteristic (ROC) curves in cross validations. The optimized biopsy procedures are also designed to be robust to the almost inevitable needle displacement errors in clinical practice, and are found to be robust to variations in the optimization parameters as well as the training populations

Beyond Diagnosis: Evolving Prostate Biopsy in the Era of Focal Therapy

Despite decades of use as the “gold standard” in the detection of prostate cancer, the optimal biopsy regimen is still not universally agreed upon. While important aspects such as the need for laterally placed biopsies and the importance of apical cancer are known, repeated studies have shown significant patients with cancer on subsequent biopsy when the original biopsy was negative and an ongoing suspicion of cancer remained. Attempts to maximise the effectiveness of repeat biopsies have given rise to the alternate approaches of saturation biopsy and the transperineal approach. Recent interest in focal treatment of prostate cancer has further highlighted the need for accurate detection of prostate cancer, and in response, the introduction of transperineal template-guided biopsy. While the saturation biopsy approach and the transperineal template approach increase the detection rate of cancer in men with a previous negative biopsy and appear to have acceptable morbidity, there is a lack of clinical trials evaluating the different biopsy strategies. This paper reviews the evolution of prostatic biopsy and current controversies

Free Prostate-specific Antigen Forms and Kallikrein-related Peptidase 2: Tools for Prostate Cancer Diagnostics

Prostate-specific antigen (PSA) is a marker that is commonly used in estimating prostate cancer risk. Prostate cancer is usually a slowly progressing disease, which might not cause any symptoms whatsoever. Nevertheless, some cases of cancer are aggressive and need to be treated before they become life-threatening. However, the blood PSA concentration may rise also in benign prostate diseases and using a single total PSA (tPSA) measurement to guide the decision on further examinations leads to many unnecessary biopsies, over-detection, and overtreatment of indolent cancers which would not require treatment. Therefore, there is a need for markers that would better separate cancer from benign disorders, and would also predict cancer aggressiveness. The aim of this study was to evaluate whether intact and nicked forms of free PSA (fPSA-I and fPSA-N) or human kallikrein-related peptidase 2 (hK2) could serve as new tools in estimating prostate cancer risk. First, the immunoassays for fPSA-I and free and total hK2 were optimized so that they would be less prone to assay interference caused by interfering factors present in some blood samples. The optimized assays were shown to work well and were used to study the marker concentrations in the clinical sample panels. The marker levels were measured from preoperative blood samples of prostate cancer patients scheduled for radical prostatectomy. The association of the markers with the cancer stage and grade was studied. It was found that among all tested markers and their combinations especially the ratio of fPSA-N to tPSA and ratio of free PSA (fPSA) to tPSA were associated with both cancer stage and grade. They might be useful in predicting the cancer aggressiveness, but further follow-up studies are necessary to fully evaluate the significance of the markers in this clinical setting. The markers tPSA, fPSA, fPSA-I and hK2 were combined in a statistical model which was previously shown to be able to reduce unnecessary biopsies when applied to large screening cohorts of men with elevated tPSA. The discriminative accuracy of this model was compared to models based on established clinical predictors in reference to biopsy outcome. The kallikrein model and the calculated fPSA-N concentrations (fPSA minus fPSA-I) correlated with the prostate volume and the model, when compared to the clinical models, predicted prostate cancer in biopsy equally well. Hence, the measurement of kallikreins in a blood sample could be used to replace the volume measurement which is time-consuming, needs instrumentation and skilled personnel and is an uncomfortable procedure. Overall, the model could simplify the estimation of prostate cancer risk. Finally, as the fPSA-N seems to be an interesting new marker, a direct immunoassay for measuring fPSA-N concentrations was developed. The analytical performance was acceptable, but the rather complicated assay protocol needs to be improved until it can be used for measuring large sample panels.Siirretty Doriast

Diagnosis of prostate cancer with magnetic resonance imaging in men treated with 5-alpha-reductase inhibitors

Purpose The primary aim of this study was to evaluate if exposure to 5-alpha-reductase inhibitors (5-ARIs) modifies the effect of MRI for the diagnosis of clinically significant Prostate Cancer (csPCa) (ISUP Gleason grade >= 2).Methods This study is a multicenter cohort study including patients undergoing prostate biopsy and MRI at 24 institutions between 2013 and 2022. Multivariable analysis predicting csPCa with an interaction term between 5-ARIs and PIRADS score was performed. Sensitivity, specificity, and negative (NPV) and positive (PPV) predictive values of MRI were compared in treated and untreated patients.Results 705 patients (9%) were treated with 5-ARIs [median age 69 years, Interquartile range (IQR): 65, 73; median PSA 6.3 ng/ml, IQR 4.0, 9.0; median prostate volume 53 ml, IQR 40, 72] and 6913 were 5-ARIs naive (age 66 years, IQR 60, 71; PSA 6.5 ng/ml, IQR 4.8, 9.0; prostate volume 50 ml, IQR 37, 65). MRI showed PIRADS 1-2, 3, 4, and 5 lesions in 141 (20%), 158 (22%), 258 (37%), and 148 (21%) patients treated with 5-ARIs, and 878 (13%), 1764 (25%), 2948 (43%), and 1323 (19%) of untreated patients (p < 0.0001). No difference was found in csPCa detection rates, but diagnosis of high-grade PCa (ISUP GG >= 3) was higher in treated patients (23% vs 19%, p = 0.013). We did not find any evidence of interaction between PIRADS score and 5-ARIs exposure in predicting csPCa. Sensitivity, specificity, PPV, and NPV of PIRADS >= 3 were 94%, 29%, 46%, and 88% in treated patients and 96%, 18%, 43%, and 88% in untreated patients, respectively.Conclusions Exposure to 5-ARIs does not affect the association of PIRADS score with csPCa. Higher rates of high-grade PCa were detected in treated patients, but most were clearly visible on MRI as PIRADS 4 and 5 lesions.Trial registration The present study was registered at ClinicalTrials.gov number: NCT05078359

Image-based registration methods for quantification and compensation of prostate motion during trans-rectal ultrasound (TRUS)-guided biopsy

Prostate biopsy is the clinical standard for cancer diagnosis and is typically performed under two-dimensional (2D) transrectal ultrasound (TRUS) for needle guidance. Unfortunately, most early stage prostate cancers are not visible on ultrasound and the procedure suffers from high false negative rates due to the lack of visible targets. Fusion of pre-biopsy MRI to 3D TRUS for targeted biopsy could improve cancer detection rates and volume of tumor sampled. In MRI-TRUS fusion biopsy systems, patient or prostate motion during the procedure causes misalignments in the MR targets mapped to the live 2D TRUS images, limiting the targeting accuracy of the biopsy system. In order to sample smallest clinically significant tumours of 0.5 cm3with 95% confidence, the root mean square (RMS) error of the biopsy system needs to be The target misalignments due to intermittent prostate motion during the procedure can be compensated by registering the live 2D TRUS images acquired during the biopsy procedure to the pre-acquired baseline 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. We developed an intensity-based 2D-3D rigid registration algorithm and validated it by calculating the target registration error (TRE) using manually identified fiducials within the prostate. We discuss two different approaches that can be used to improve the robustness of this registration to meet the clinical requirements. Firstly, we evaluated the impact of intra-procedural 3D TRUS imaging on motion compensation accuracy since the limited anatomical context available in live 2D TRUS images could limit the robustness of the 2D-3D registration. The results indicated that TRE improved when intra-procedural 3D TRUS images were used in registration, with larger improvements in the base and apex regions as compared with the mid-gland region. Secondly, we developed and evaluated a registration algorithm whose optimization is based on learned prostate motion characteristics. Compared to our initial approach, the updated optimization improved the robustness during 2D-3D registration by reducing the number of registrations with a TRE \u3e 5 mm from 9.2% to 1.2% with an overall RMS TRE of 2.3 mm. The methods developed in this work were intended to improve the needle targeting accuracy of 3D TRUS-guided biopsy systems. The successful integration of the techniques into current 3D TRUS-guided systems could improve the overall cancer detection rate during the biopsy and help to achieve earlier diagnosis and fewer repeat biopsy procedures in prostate cancer diagnosis

Illuminating the pathway:For image-guided prostate cancer care

The aim of this thesis is to improve the diagnostic pathway for prostate cancer (PCa) and to develop a minimal invasive focal ablative treatment for PCa. In Chapter 2 risk stratification for detection of clinically significant PCa (csPCa) with systematic biopsy in biopsy naive patients with prostate imaging-reporting and data system (PI-RADS) classification ≤2 on pre-biopsy prostate MRI is evaluated, predictors for csPCa are integrated into a novel risk calculator and compared to contemporary risk calculators. Furthermore, in Chapter 3 an optimal biopsy strategy is determined for prostate biopsy patients with a unilateral PI-RADS classification ≥3 on pre-biopsy prostate MRI based on detection rates of csPCa and iPCa using different combinations of MRI-targeted biopsy, ipsilateral and/or contralateral systematic biopsy. Additionally, in Chapter 4 safety and feasibility of needle-based confocal laser endomicroscopy (CLE) for real-time PCa detection is investigated in prostate biopsy patients. In Chapter 5 safety and feasibility and short-term quality of life outcomes of transperineal focal laser ablation (TPLA) for treatment of PCa under local anesthesia in a daycare setting is evaluated. Moreover, in Chapter 6 three-dimensional ablative effects of TPLA for treatment of PCa are visualized on prostate MRI and contrast-enhanced ultrasound (CEUS) and correlated with whole-mount prostate histology after RARP. Finally, in Chapter 7 safety, feasibility and medium-term oncological and functional outcomes of salvage RARP are studied for recurrent localized PCa following initial focal ablative therapy using irreversible electroporation (IRE)

Clinical Detection of Diagnostic Biomarker Panels Using Microfluidic Electrochemical Immunoarrays

Cancer is a worldwide infliction. Cancer does not discriminate. Cancer does not care if you are young or old, rich or poor, disabled or in the prime of your life. It can be caused by genetics, environmental factors and/or lifestyle. The challenge, how do we diagnose and treat such a dynamic disease? Cancer detection is expensive, invasive, inaccurate and lacks sensitivity. New methods that rely on measurements of analytes in solution for detection and quantification are promising alternatives. Panels of protein biomarkers may aid in personalized diagnosis as protein levels in patients are often upregulated or down regulated in relation to a specified disease. For the medical field this provides opportunities to bring cancer detection to clinical practice as it will enable physicians’ access to blood, saliva, or urine bioassays for screening, as well as monitoring progression and response to therapy. The objectives of this thesis are to utilize new technology in microfluidic fabrication, 3D printing and nanomaterial synthesis for ELISA alternatives. The sensors are developed to be sensitive, rapid, inexpensive and multiplexed for point of care diagnostics. These technically facile immunoassays in human patient serum comprise a multivariable approach for statistically improving the probability of diagnosing and differentiating forms of cancer

Impact of Extracellular Vesicle Isolation Methods on Downstream miRNA Analysis in Semen: A Comparative Study

Seminal plasma (SP) contains a unique concentration of miRNA, mostly contained in small extracellular vesicles (sEVs) such as exosomes, some of which could be clinically useful for diagnosis and/or prognosis of urogenital diseases such as prostate cancer (PCa). We optimized several exosome-EV isolation technologies for their use in semen, evaluating EV purifying effectiveness and impact on the downstream analysis of miRNAs against results from the standard ultracentrifugation (UC) method to implement the use of SP sEV_miRNAs as noninvasive biomarkers for PCa. Our results evidenced that commercial kits designed to isolate exosomes/EVs from blood or urine are mostly applicable to SP, but showed quantitative and qualitative variability between them. ExoGAG 3500× g and the miRCURY Cell/Urine/CSF 1500× g methods resulted as equivalent alternative procedures to UC for isolating exosomes/sEVs from semen for nanoparticle characteristics and quality of RNA contained in vesicles. Additionally, the expression profile of the altered semen sEV-miRNAs in PCa varies depending on the EV isolation method applied. This is possibly due to different extraction techniques yielding different proportions of sEV subtypes. This is evidence that the exosome-EV isolation method has a significant impact on the analysis of the miRNAs contained within, with important consequences for their use as clinical biomarkers. Therefore, miRNA analysis results for EVs cannot be directly extrapolated between different EV isolation methods until clear markers for delineation between microvesicles and exosomes are established. However, EV extraction methodology affects combined models (semen exosome miRNA signatures plus blood Prostate specific antigen (PSA) concentration for PCa diagnosis) less; specifically our previously described (miR-142-3p + miR-142-5p + miR-223-3p + PSA) model functions as molecular marker from EVs from any of the three isolation methods, potentially improving the efficiency of PSA PCa diagnosis

Impact of extracellular vesicle isolation methods on downstream mirna analysis in semen: A comparative study

Seminal plasma (SP) contains a unique concentration of miRNA, mostly contained in small extracellular vesicles (sEVs) such as exosomes, some of which could be clinically useful for diagnosis and/or prognosis of urogenital diseases such as prostate cancer (PCa). We optimized several exosome-EV isolation technologies for their use in semen, evaluating EV purifying effectiveness and impact on the downstream analysis of miRNAs against results from the standard ultracentrifugation (UC) method to implement the use of SP sEV_miRNAs as noninvasive biomarkers for PCa. Our results evidenced that commercial kits designed to isolate exosomes/EVs from blood or urine are mostly applicable to SP, but showed quantitative and qualitative variability between them. ExoGAG 3500x g and the miRCURY Cell/Urine/CSF 1500x g methods resulted as equivalent alternative procedures to UC for isolating exosomes/sEVs from semen for nanoparticle characteristics and quality of RNA contained in vesicles. Additionally, the expression profile of the altered semen sEV-miRNAs in PCa varies depending on the EV isolation method applied. This is possibly due to different extraction techniques yielding different proportions of sEV subtypes. This is evidence that the exosome-EV isolation method has a significant impact on the analysis of the miRNAs contained within, with important consequences for their use as clinical biomarkers. Therefore, miRNA analysis results for EVs cannot be directly extrapolated between different EV isolation methods until clear markers for delineation between microvesicles and exosomes are established. However, EV extraction methodology affects combined models (semen exosome miRNA signatures plus blood Prostate specific antigen (PSA) concentration for PCa diagnosis) less; specifically our previously described (miR-142-3p + miR-142-5p + miR-223-3p + PSA) model functions as molecular marker from EVs from any of the three isolation methods, potentially improving the efficiency of PSA PCa diagnosis