Gas gangrene with Clostridium septicum in a neutropenic patient.

Gas gangrene is a rare presentation of a necrotizing fasciitis, caused by Clostridium perfringens, C. septicum and other clostridial species. With its rapid progression it is a potentially life-threatening infection, that poses as a challenge in the clinical management requiring an interdisciplinary approach.Here we present a 62-year-old woman, who developed neutropenic fever while undergoing chemotherapy for triple negative breast cancer. She presented with a high fever, reporting little pain in her left thigh accompanied by redness and induration locally. Subsequently the patient developed pain and redness of the back of the left hand. The initial findings suggested cellulitis and immediate empiric treatment with intravenous meropenem was started. Despite the antibiotic treatment the patient rapidly developed septic shock along with progression of the local infection. Emergency surgical debridement revealed extensive necrosis of the soft tissues including extensive myonecrosis of the thigh. On the left hand an extensive debridement was performed, the left lower limb could not be preserved and exarticulation of the left hip was required. Microbiologically C. septicum was isolated in different samples, confirming gas gangrene. As there was no local entry portal on the skin, hematogenous seeding from intestinal translocation in this neutropenic patient was suspected. The empiric antibiotic treatment was tailored to intravenous penicillin and complemented with clindamycin for toxin inhibition. Following radical debridement and antibiotic treatment, the patient could be stabilized. After repetitive debridement wound closure was achieved and the patient was discharged for rehabilitation. Antibiotic treatment was continued for four weeks.This rare case of gas gangrene in a neutropenic patient shows the complexity in the diagnostic and therapeutic management of necrotizing soft tissue infections in immunocompromised patients. It particularly highlights the importance of an interdisciplinary management with fast recognition of the disease and rapid, if needed radical, surgical debridement as well as tailored antibiotic treatment for a successful outcome.

Evaluation of Machine Learning Classification Models for False-Positive Reduction in Prostate Cancer Detection Using MRI Data.

In this work, several machine learning (ML) algorithms, both classical ML and modern deep learning, were investigated for their ability to improve the performance of a pipeline for the segmentation and classification of prostate lesions using MRI data. The algorithms were used to perform a binary classification of benign and malignant tissue visible in MRI sequences. The model choices include support vector machines (SVMs), random decision forests (RDFs), and multi-layer perceptrons (MLPs), along with radiomic features that are reduced by applying PCA or mRMR feature selection. Modern CNN-based architectures, such as ConvNeXt, ConvNet, and ResNet, were also evaluated in various setups, including transfer learning. To optimize the performance, different approaches were compared and applied to whole images, as well as gland, peripheral zone (PZ), and lesion segmentations. The contribution of this study is an investigation of several ML approaches regarding their performance in prostate cancer (PCa) diagnosis algorithms. This work delivers insights into the applicability of different approaches for this context based on an exhaustive examination. The outcome is a recommendation or preference for which machine learning model or family of models is best suited to optimize an existing pipeline when the model is applied as an upstream filter.

Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms "in the Wild".

The biopsy Gleason score is an important prognostic marker for prostate cancer patients. It is, however, subject to substantial variability among pathologists. Artificial intelligence (AI)-based algorithms employing deep learning have shown their ability to match pathologists' performance in assigning Gleason scores, with the potential to enhance pathologists' grading accuracy. The performance of Gleason AI algorithms in research is mostly reported on common benchmark data sets or within public challenges. In contrast, many commercial algorithms are evaluated in clinical studies, for which data are not publicly released. As commercial AI vendors typically do not publish performance on public benchmarks, comparison between research and commercial AI is difficult. The aims of this study are to evaluate and compare the performance of top-ranked public and commercial algorithms using real-world data. We curated a diverse data set of whole-slide prostate biopsy images through crowdsourcing containing images with a range of Gleason scores and from diverse sources. Predictions were obtained from 5 top-ranked public algorithms from the Prostate cANcer graDe Assessment (PANDA) challenge and 2 commercial Gleason grading algorithms. Additionally, 10 pathologists (A.C., C.R., J.v.I., K.R.M.L., P.R., P.G.S., R.G., S.F.K.J., T.v.d.K., X.F.) evaluated the data set in a reader study. Overall, the pairwise quadratic weighted kappa among pathologists ranged from 0.777 to 0.916. Both public and commercial algorithms showed high agreement with pathologists, with quadratic kappa ranging from 0.617 to 0.900. Commercial algorithms performed on par or outperformed top public algorithms.

Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology.

Integration of digital pathology (DP) into clinical diagnostic workflows is increasingly receiving attention as new hardware and software become available. To facilitate the adoption of DP, the Swiss Digital Pathology Consortium (SDiPath) organized a Delphi process to produce a series of recommendations for DP integration within Swiss clinical environments. This process saw the creation of 4 working groups, focusing on the various components of a DP system (1) scanners, quality assurance and validation of scans, (2) integration of Whole Slide Image (WSI)-scanners and DP systems into the Pathology Laboratory Information System, (3) digital workflow-compliance with general quality guidelines, and (4) image analysis (IA)/artificial intelligence (AI), with topic experts for each recruited for discussion and statement generation. The work product of the Delphi process is 83 consensus statements presented here, forming the basis for "SDiPath Recommendations for Digital Pathology". They represent an up-to-date resource for national and international hospitals, researchers, device manufacturers, algorithm developers, and all supporting fields, with the intent of providing expectations and best practices to help ensure safe and efficient DP usage.

National digital pathology projects in Switzerland: A 2023 update.

The Swiss Digital Pathology Consortium (SDiPath) was founded in 2018 as a working group of the Swiss Society for Pathology with the aim of networking, training, and promoting digital pathology (DP) at a national level. Since then, two national surveys have been carried out on the level of knowledge, dissemination, use, and needs in DP, which have resulted in clear fields of action. In addition to organizing symposia and workshops, national guidelines were drawn up and an initiative for a national DP platform actively codesigned. With the growing use of digital image processing and artificial intelligence tools, continuous monitoring, evaluation, and exchange of experiences will be pursued, along with best practices.

Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view.

Digital pathology (DP) is increasingly entering routine clinical pathology diagnostics. As digitization of the routine caseload advances, implementation of digital image analysis algorithms and artificial intelligence tools becomes not only attainable, but also desirable in daily sign out. The Swiss Digital Pathology Consortium (SDiPath) has initiated a Delphi process to generate best-practice recommendations for various phases of the process of digitization in pathology for the local Swiss environment, encompassing the following four topics: i) scanners, quality assurance, and validation of scans; ii) integration of scanners and systems into the pathology laboratory information system; iii) the digital workflow; and iv) digital image analysis (DIA)/artificial intelligence (AI). The current article focuses on the DIA-/AI-related recommendations generated and agreed upon by the working group and further verified by the Delphi process among the members of SDiPath. Importantly, they include the view and the currently perceived needs of practicing pathologists from multiple academic and cantonal hospitals as well as private practices.

Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study.

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

Topographic distribution of inflammation factors in a healing aneurysm.

BACKGROUND: Healing of intracranial aneurysms following endovascular treatment relies on the organization of early thrombus into mature scar tissue and neointima formation. Activation and deactivation of the inflammation cascade plays an important role in this process. In addition to timely evolution, its topographic distribution is hypothesized to be crucial for successful aneurysm healing. METHODS: Decellularized saccular sidewall aneurysms were created in Lewis rats and coiled. At follow-up (after 3 days (n = 16); 7 days (n = 19); 21 days (n = 8)), aneurysms were harvested and assessed for healing status. In situ hybridization was performed for soluble inflammatory markers (IL6, MMP2, MMP9, TNF-α, FGF23, VEGF), and immunohistochemical analysis to visualize inflammatory cells (CD45, CD3, CD20, CD31, CD163, HLA-DR). These markers were specifically documented for five regions of interest: aneurysm neck, dome, neointima, thrombus, and adjacent vessel wall. RESULTS: Coiled aneurysms showed enhanced patterns of thrombus organization and neointima formation, whereas those without treatment demonstrated heterogeneous patterns of thrombosis, thrombus recanalization, and aneurysm growth (p = 0.02). In coiled aneurysms, inflammation markers tended to accumulate inside the thrombus and in the neointima (p < 0.001). Endothelial cells accumulated directly in the neointima (p < 0.0001), and their presence was associated with complete aneurysm healing. CONCLUSION: The presence of proinflammatory cells plays a crucial role in aneurysm remodeling after coiling. Whereas thrombus organization is hallmarked by a pronounced intra-thrombotic inflammatory reaction, neointima maturation is characterized by direct invasion of endothelial cells. Knowledge concerning topographic distribution of regenerative inflammatory processes may pave the way for future treatment modalities which enhance aneurysm healing after endovascular therapy.

Unusual Masquerading Infraorbital Mass-A Case Report of Human Ocular Dirofilariosis Found in A Ukrainian Patient in Switzerland.

A 78-year-old Ukrainian woman who had immigrated to Switzerland presented with a rapid growing subcutaneous infraorbital mass. Surgical excision of the mass revealed a well-circumscribed, encapsulated tumor, adherent to the skin. The excision showed a soft tissue inflammation with parts of Dirofilaria spp. The number of cases of human dirofilariosis reported in the last 50 years has gradually increased. Dirofilaria repens is now endemic in many countries and is currently considered to be one of the fast spreading zoonoses in Central, Eastern and Northern Europe. The first empirical evidence of Swiss spreading of D. repens infections was in a dog from southern Switzerland in 1998. Ours is the first case of human orbital dirofilariosis found in a Ukranian patient reported in Switzerland. Our purpose is to inform the ophthalmologist to consider orbital dirofilariosis in the differential diagnosis of inflammatory masses of the orbit and to warn about the spread of this infection in Switzerland.

DNA Methylation Landscapes of Prostate Cancer Brain Metastasis Are Shaped by Early Driver Genetic Alterations.

Metastases from primary prostate cancers to rare locations, such as the brain, are becoming more common due to longer life expectancy resulting from improved treatments. Epigenetic dysregulation is a feature of primary prostate cancer, and distinct DNA methylation profiles have been shown to be associated with the mutually exclusive SPOP-mutant or TMPRSS2-ERG fusion genetic backgrounds. Using a cohort of prostate cancer brain metastases (PCBM) from 42 patients, with matched primary tumors for 17 patients, we carried out a DNA methylation analysis to examine the epigenetic distinction between primary prostate cancer and PCBM, the association between epigenetic alterations and mutational background, and particular epigenetic alterations that may be associated with PCBM. Multiregion sampling of PCBM revealed epigenetic stability within metastases. Aberrant methylation in PCBM was associated with mutational background and PRC2 complex activity, an effect that is particularly pronounced in SPOP-mutant PCBM. While PCBM displayed a CpG island hypermethylator phenotype, hypomethylation at the promoters of genes involved in neuroactive ligand-receptor interaction and cell adhesion molecules such as GABRB3, CLDN8, and CLDN4 was also observed, suggesting that cells from primary tumors may require specific reprogramming to form brain metastasis. This study revealed the DNA methylation landscapes of PCBM and the potential mechanisms and effects of PCBM-associated aberrant DNA methylation. SIGNIFICANCE: DNA methylation analysis reveals the molecular characteristics of PCBM and may serve as a starting point for efforts to identify and target susceptibilities of these rare metastases.

Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.

Although deep learning (DL) has demonstrated impressive diagnostic performance for a variety of computational pathology tasks, this performance often markedly deteriorates on whole slide images (WSI) generated at external test sites. This phenomenon is due in part to domain shift, wherein differences in test-site pre-analytical variables (e.g., slide scanner, staining procedure) result in WSI with notably different visual presentations compared to training data. To ameliorate pre-analytic variances, approaches such as CycleGAN can be used to calibrate visual properties of images between sites, with the intent of improving DL classifier generalizability. In this work, we present a new approach termed Multi-Site Cross-Organ Calibration based Deep Learning (MuSClD) that employs WSIs of an off-target organ for calibration created at the same site as the on-target organ, based off the assumption that cross-organ slides are subjected to a common set of pre-analytical sources of variance. We demonstrate that by using an off-target organ from the test site to calibrate training data, the domain shift between training and testing data can be mitigated. Importantly, this strategy uniquely guards against potential data leakage introduced during calibration, wherein information only available in the testing data is imparted on the training data. We evaluate MuSClD in the context of the automated diagnosis of non-melanoma skin cancer (NMSC). Specifically, we evaluated MuSClD for identifying and distinguishing (a) basal cell carcinoma (BCC), (b) in-situ squamous cell carcinomas (SCC-In Situ), and (c) invasive squamous cell carcinomas (SCC-Invasive), using an Australian (training, n = 85) and a Swiss (held-out testing, n = 352) cohort. Our experiments reveal that MuSCID reduces the Wasserstein distances between sites in terms of color, contrast, and brightness metrics, without imparting noticeable artifacts to training data. The NMSC-subtyping performance is statistically improved as a result of MuSCID in terms of one-vs. rest AUC: BCC (0.92 vs 0.87, p = 0.01), SCC-In Situ (0.87 vs 0.73, p = 0.15) and SCC-Invasive (0.92 vs 0.82, p = 1e-5). Compared to baseline NMSC-subtyping with no calibration, the internal validation results of MuSClD (BCC (0.98), SCC-In Situ (0.92), and SCC-Invasive (0.97)) suggest that while domain shift indeed degrades classification performance, our on-target calibration using off-target tissue can safely compensate for pre-analytical variabilities, while improving the robustness of the model.

Towards a national strategy for digital pathology in Switzerland.

Precision medicine is entering a new era of digital diagnostics; the availability of integrated digital pathology (DP) and structured clinical datasets has the potential to become a key catalyst for biomedical research, education and business development. In Europe, national programs for sharing of this data will be crucial for the development, testing, and validation of machine learning-enabled tools supporting clinical decision-making. Here, the Swiss Digital Pathology Consortium (SDiPath) discusses the creation of a Swiss Digital Pathology Infrastructure (SDPI), which aims to develop a unified national DP network bringing together the Swiss Personalized Health Network (SPHN) with Swiss university hospitals and subsequent inclusion of cantonal and private institutions. This effort builds on existing developments for the national implementation of structured pathology reporting. Opening this national infrastructure and data to international researchers in a sequential rollout phase can enable the large-scale integration of health data and pooling of resources for research purposes and clinical trials. Therefore, the concept of a SDPI directly synergizes with the priorities of the European Commission communication on the digital transformation of healthcare on an international level, and with the aims of the Swiss State Secretariat for Economic Affairs (SECO) for advancing research and innovation in the digitalization domain. SDPI directly addresses the needs of existing national and international research programs in neoplastic and non-neoplastic diseases by providing unprecedented access to well-curated clinicopathological datasets for the development and implementation of novel integrative methods for analysis of clinical outcomes and treatment response. In conclusion, a SDPI would facilitate and strengthen inter-institutional collaboration in technology, clinical development, business and research at a national and international scale, promoting improved patient care via precision medicine.

Alterations in homologous recombination repair genes in prostate cancer brain metastases.

Improved survival rates for prostate cancer through more effective therapies have also led to an increase in the diagnosis of metastases to infrequent locations such as the brain. Here we investigate the repertoire of somatic genetic alterations present in brain metastases from 51 patients with prostate cancer brain metastases (PCBM). We highlight the clonal evolution occurring in PCBM and demonstrate an increased mutational burden, concomitant with an enrichment of the homologous recombination deficiency mutational signature in PCBM compared to non-brain metastases. Focusing on known pathogenic alterations within homologous recombination repair genes, we find 10 patients (19.6%) fulfilling the inclusion criteria used in the PROfound clinical trial, which assessed the efficacy of PARP inhibitors (PARPi) in homologous recombination deficient prostate cancer. Eight (15.7%) patients show biallelic loss of one of the 15 genes included in the trial, while 5 patients (9.8%) harbor pathogenic alterations in BRCA1/2 specifically. Uncovering these molecular features of PCBM may have therapeutic implications, suggesting the need of clinical trial enrollment of PCBM patients when evaluating potential benefit from PARPi.

Update on the current opinion, status and future development of digital pathology in Switzerland in light of COVID-19.

AIMS: The transition from analogue to digital pathology (DP) in Switzerland has coincided with the COVID-19 crisis. The Swiss Digital Pathology Consortium conducted a national survey to assess the experience of pathologists in dealing with the challenges of the pandemic and how this has influenced the outlook and adoption of DP. METHODS: A survey containing 20 questions relating to DP, personal experiences and challenges during the pandemic was addressed to Swiss pathologists at different experience stages in private practice, community and university hospitals. RESULTS: All 74 respondents were pathologists, with 81.1% reporting more than 5 years of diagnostic service experience. 32.5% reported having read 100 digital slides or more in a diagnostic context. 39.2% reported using whole slide imaging systems at their primary workplace. Key DP use cases before the COVID-19 lockdown were tumour boards (39.2%), education (60.8%) and research (44.6%), with DP used for primary diagnosis in 13.5%. During the COVID-19 crisis, the use of DP for primary diagnostics more than doubled (30% vs 13.5%), with internal consults as important drivers (22.5% vs 16.5%), while research use (25% vs 44.6%) and external consults (17.5% vs 41.9%) strongly decreased. Key challenges identified included a lack of established standard operating procedures and availability of specialised hardware and software. CONCLUSIONS: This survey indicates that the crisis acted as a catalyst in promoting DP adoption in centres where basic workflows were already established while posing major technical and organisational challenges in institutions that were at an early stage of DP implementation.

Effects of lenalidomide on the bone marrow microenvironment in acute myeloid leukemia: Translational analysis of the HOVON103 AML/SAKK30/10 Swiss trial cohort.

This translational study aimed at gaining insight into the effects of lenalidomide in acute myeloid leukemia (AML). Forty-one AML patients aged 66 or older of the Swiss cohort of the HOVON-103 AML/SAKK30/10 study were included. After randomization, they received standard induction chemotherapy with or without lenalidomide. Bone marrow biopsies at diagnosis and before the 2nd induction cycle were obtained to assess the therapeutic impact on leukemic blasts and microenvironment. Increased bone marrow angiogenesis, as assessed by microvessel density (MVD), was found at AML diagnosis and differed significantly between the WHO categories. Morphological analysis revealed a higher initial MVD in AML with myelodysplasia-related changes (AML-MRC) and a more substantial decrease of microvascularization after lenalidomide exposure. A slight increase of T-bet-positive TH1-equivalents was identifiable under lenalidomide. In the subgroup of patients with AML-MRC, the progression-free survival differed between the two treatment regimens, showing a potential but not significant benefit of lenalidomide. We found no correlation between the cereblon genotype (the target of lenalidomide) and treatment response or prognosis. In conclusion, addition of lenalidomide may be beneficial to elderly patients suffering from AML-MRC, where it leads to a reduction of microvascularization and, probably, to an intensified specific T cell-driven anti-leukemic response.

Midthoracic Pain, Sentinel Arterial Haemorrhage and Exsanguination after a Symptom-Free Interval (Chiari's Triad) is Diagnostic of Arterio-Oesophageal Fistula: A Life-Threatening Cause of Gastrointestinal Bleeding.

INTRODUCTION: Arterio-oesophageal fistulae are a very uncommon cause of severe gastrointestinal bleeding, and mostly result from an aberrant right subclavian artery and mediastinal surgery or prolonged endotracheal/nasogastric intubation. MATERIAL AND METHODS: We present the case of a patient with an oesophageal adenocarcinoma and haematemesis due to a subclavian arterio-oesophageal fistula after mediastinal radiotherapy. CONCLUSION: We discuss the rare, life-threatening condition of acute erosion of the left subclavian artery caused by an oesophageal tumour and presenting with Chiari's triad. LEARNING POINTS: Subclavian arterio-oesophageal fistula is an uncommon, life-threatening cause of gastrointestinal bleeding.Knowledge of Chiari's triad enables early recognition of potentially fatal gastro-intestinal bleeding.A high level of suspicion is essential for prompt diagnosis and referral for surgical treatment especially in patients with malignancies of the upper gastrointestinal tract.

Prognostic implications of the microenvironment for follicular lymphoma under immunomodulation therapy.

Follicular lymphoma (FL) constitutes a significant proportion of lymphomas and shows frequent relapses. Beyond conventional chemotherapy, new therapeutic approaches have emerged, focussing on the interplay between lymphoma cells and the microenvironment. Here we report the immunophenotypic investigation of the microenvironment of a clinically well-characterized prospective cohort (study SAKK35/10, NCT01307605) of 154 treatment-naïve FL patients in need of therapy, who have been treated with rituximab only or a combination of rituximab and the immunomodulatory drug lenalidomide/Revlimid® A high ratio of CD4- to CD8-positive T cells (P = 0·009) and increased amounts of PD1+ tumour-infiltrating T cells (P = 0·007) were associated with inferior progression-free survival in the whole cohort. Interestingly, the prognostic impact of PD1+ T cells and the CD4/CD8 ratio lost its significance in the subgroup treated with R2 . In the latter group, high amounts of GATA3+ T helper (Th2) equivalents were associated with better progression-free survival (P < 0·001). We identified tumour microenvironmental features that allow prognostic stratification with respect to immuno- and combined immuno- and immunomodulatory therapy. Our analysis indicates that lenalidomide may compensate the adverse prognostic implication of higher amounts of CD4+ and, particularly, PD1+ T cells and that it has favourable effects mainly in cases with higher amounts of Th2 equivalents. [Correction added on 11 February 2020, after online publication: The NCT-trial number was previously incorrect and has been updated in this version].

Current opinion, status and future development of digital pathology in Switzerland.

AIMS: The transition from analogue to digital pathology (DP) is underway in Switzerland. To assess relevant experiences of pathologists with DP and gauge their outlook towards a digital future, a national survey was conducted by the Swiss Digital Pathology Consortium. Similar surveys were conducted in other countries, enabling a meta-analysis of DP experiences. METHODS: Pathologists and residents were asked to complete a survey containing 12 questions. Results were compared with similar studies conducted in the United Kingdom, Sweden, Canada, and India. RESULTS: The estimated response rate among practicing pathologists and trainees nationwide was 39.5%. Of these, 89% have experience with digital slides, mainly for education (61%) and primary diagnostics (20%). Further, 32% have worked with an image analysis programme and 26% use computer-based algorithms weekly. Interestingly, 66% would feel comfortable making a primary diagnosis digitally, while 10% would not. Most respondents believe more standards and regulations are necessary for the clinical employment of DP. Noted advantages include ease of access to slides and the resulting connectivity benefits, namely collaboration with experts across disciplines, off-site work, training purposes, and computational image analysis. Perceived disadvantages include implementation costs and issues associated with IT infrastructure and file formats. CONCLUSION: The survey results suggest that experiences and perspectives of Swiss pathologists concerning DP is comparable to that of the other reporting countries undergoing transitions to digital workflows. Although more standards and regulations are needed to ensure the safe usage of these technologies, pathologists in Switzerland appear welcoming of this new digital era.

Influence of regular aspirin intake on PSA values, prostate cancer incidence and overall survival in a prospective screening trial (ERSPC Aarau).

OBJECTIVES: To analyze the influence of aspirin (ASA) intake on PSA values and prostate cancer (PCa) development in a prospective screening study cohort. METHODS: 4314 men from the Swiss section of the European Randomized Study of Screening for Prostate Cancer (ERSPC) were included. A transrectal prostate biopsy was performed in men with a PSA level ≥ 3 ng/ml. Mortality data were obtained through registry linkages. PCa incidence and grade, total PSA, free-to-total PSA and overall survival were compared between ASA users and non-users. RESULTS: Median follow-up time was 9.6 years. In 789 men (18.3%) using aspirin [ASA +], the overall PCa incidence was significantly lower (6.8% vs. 9.6%, p = 0.015), but the multivariate Cox regression analysis showed no significant decrease in risk of PCa diagnosis (HR 0.84, p = 0.297). Total PSA values were significantly lower in ASA users for both baseline (1.6 vs. 1.8 ng/ml, p = 0.007) and follow-up visits (1.75 vs. 2.1 ng/ml, p < 0.001). Multivariate Cox regression analysis predicted significantly higher overall mortality risk among ASA users (HR 1.46, p = 0.009). CONCLUSIONS: In our study population, PCa incidence was significantly reduced among patients on aspirin. While we did not observe a statistically significant PCa risk reduction during the follow-up period, we found lower PSA values among ASA users compared to non-users, with a more distinct difference after 4 years of ASA intake, suggesting a cumulative effect and a potential protective association between regular ASA intake and PCa development. As for clinical practice, lowering PSA cutoff values by 0.4 ng/ml could be considered in long-term ASA users to avoid a potential bias towards delayed PCa detection.

Diagnostic Accuracy of a MR Protocol Acquired with and without Endorectal Coil for Detection of Prostate Cancer: A Multicenter Study.

INTRODUCTION: The purpose of this study was to compare diagnostic accuracy of a prostate multiparametric magnetic resonance imaging (mpMRI) protocol for detection of prostate cancer between images acquired with and without en-dorectal coil (ERC). MATERIALS: This study was approved by the regional ethics committee. Between 2014 and 2015, 33 patients (median age 51.3 years; range 42.1-77.3 years) who underwent prostate-MRI at 3T scanners at 2 different institutions, acquired with (mpMRIERC) and without (mpMRIPPA) ERC and who received radical prostatectomy, were included in this retrospective study. Two expert readers (R1, R2) attributed a PI-RADS version 2 score for the most suspect (i. e. index) lesion for mpMRIPPA and mpMRIERC. Sensitivity and positive predictive value for detection of index lesions were assessed using 2 × 2 contingency tables. Differences between groups were tested using the McNemar test. Whole-mount histopathology served as reference standard. RESULTS: On a quadrant-basis cumulative sensitivity ranged between 0.61-0.67 and 0.76-0.88 for mpMRIPPA and mpMRIERC protocols, respectively (p > 0.05). Cumulative positive predictive value ranged between 0.80-0.81 and 0.89-0.91 for mpMRIPPA and mpMRIERC protocols, respectively. The differences were not statistically significant for R1 (p = 0.267) or R2 (p = 0.508). CONCLUSION: Our results suggest that there may be no significant differences for detection of prostate cancer between images acquired with and without an ERC.