Artificial intelligence for streamlining prostate cancer diagnostics

With around 1.2 million cases per year, prostate cancer is the second most common cancer among men. It is usually a slow growing disease that affects older men. It is also a cancer that is heterogenous, often multifocal, and rarely show symptoms as long as it is localized. All these things make the disease difficult to detect, diagnose and study. The objective of this thesis is to develop and improve technologies for prostate cancer diagnostics and to acquire knowledge related to these technologies that directly translate to clinical utility. In Study I, we extended analysis of the multivariable diagnostic prediction model S3M by exploring the relative contribution from the individual predictors and evaluating the model in reflex setting where the test is only given to men positive on a PSA test. We also updated the list of included predictors and refitted the model to more data. In Study II, we digitized a substantial part of the biopsy cores collected from the men in study I. These images were used to develop and validate an AI for prostate cancer diagnostics by detecting, grading, and measuring the extent of cancer in the biopsies. The AI achieved nearly perfect detection of cancer and expert pathologist level grading of the biopsies. It also well predicted the total tumor burden of the patient. In Study III, we focused our attention on perineural invasion, a common finding in prostate biopsies. This study has added to the evidence that there is substantial and independent prognostic information in this finding and argued that it should be included as a compulsory part in pathology reporting guidelines for prostate biopsies. In Study IV, we developed an AI for detection and localization of perineural invasion in biopsies. The AI achieved high discriminative ability on an independent test set. We are currently collecting external data to validate these results in another environment and to compare the results of the AI against expert pathologists. In conclusion, the technologies developed in this thesis has shown promise in streamlining the clinical workload around prostate cancer detection and diagnostics. The thesis has also contributed to pieces of information related to these technologies

Plant species from mesotrophic wetlands cause relatively high methane emissions from peat soil

Plants can influence methane emissions from wetland ecosystems by altering its production, consumption and transport in the soil. The aim of this study was to investigate how eight vascular plant species from mesotrophic to eutrophic wetlands vary in their influence on CH4 emissions from peat cores, under low and high N supply. Additionally, we measured the production of low-molecular-weight organic acids (LOA) by the same species (also at low and high N supply), because LOA form a substrate for methanogenesis. There were considerable differences among species in their effects upon rates of CH4 emission. Six of the species (Eriophorum latifolium Hoppe, Potentilla palustris (L.) Scop., Anthoxanthum odoratum (L.) s. str., Carex rostrata Stokes, Carex elata All., Carex acutiformis Ehrh.) increased CH4 emissions up to five times compared to control peat cores without plants, whereas two species (Phalaris arundinacea L., Phragmites australis (Cav.) Trin. ex Steud.) had no effect. There was a weak negative correlation between plant biomass and CH4 emission. N addition had no significant general effect upon CH4 emission. LOA production varied considerably among species, and tended to be highest for species from mesotrophic habitats. LOA production was stimulated by N addition. We conclude that some species from mesotrophic wetlands tend to cause higher CH4 emissions than species from eutrophic wetlands. This pattern, which contradicts what is often mentioned in literature, may be explained by the higher LOA production rates of species adapted to less productive habitat

Plasma atropine concentrations associated with decreased intestinal motility in horses

IntroductionAtropine is an essential part of the treatment protocol for equine uveitis. Topical atropine administration has been associated with decreased intestinal motility and abdominal pain in horses. Experimental studies have indicated that frequent dosing is associated with a higher risk than dosing every 6 h. Unfortunately, no quantitative pharmacodynamic data for inhibition of the equine gut are published. Materials and methodsEight standardbred horses were assigned to receive either atropine or saline (control) to be infused over 30 min in a two-treatment cross-over design. Atropine concentrations in plasma were measured using ultra-high-performance liquid chromatography-tandem mass spectrometry. Intestinal motility was measured using borborygmi frequency and electrointestinography (EIG). Experimental data were analyzed using a non-linear mixed effects model. The model was then used to simulate different dosing regimens. ResultsAtropine significantly decreased borborygmi response and EIG response. Six horses developed clinical signs of abdominal pain. The pharmacokinetic typical values were 0.31, 1.38, 0.69, and 1.95 L/kg center dot h for the volumes of the central, the highly perfused, the scarcely perfused compartments, and the total body clearance, respectively. The pharmacodynamic typical values were 0.31 mu g/L and 0.6 and 207 nV(2)7 cpm for the plasma concentration at 50% of the maximum response and the maximum response and the baseline of cecal EIG response, respectively. Six different dosing regimens of topical atropine sulfate to the eye (0.4 and 1 mg every hour, every 3 h, and every 6 h) were simulated. ConclusionThe IV PK/PD data coupled with simulations predict that administration of 1 mg of topical atropine sulfate administered to the eye every hour or every 3 h will lead to atropine accumulation in plasma and decreased intestinal myoelectric activity. Administration every 6 h predicted a safe dosing regimen in full-sized horses. Clinical studies would be valuable to confirm the conclusions. For smaller equids and horses put at risk for colic due to othercauses, droplet bottles that deliver 40 mu l of 1% atropine sulfate per drop or less may be used to lower the risk further

Detection of perineural invasion in prostate needle biopsies with deep neural networks

The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97–0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohen’s kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.publishedVersionPeer reviewe

Detection of perineural invasion in prostate needle biopsies with deep neural networks

The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97-0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohen's kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.</p

Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies

Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67-0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization

Operative versus non-operative treatment for 2-part proximal humerus fracture: A multicenter randomized controlled trial

Background Although increasingly used, the benefit of surgical treatment of displaced 2-part proximal humerus fractures has not been proven. This trial evaluates the clinical effectiveness of surgery with locking plate compared with non-operative treatment for these fractures. Methods and findings The NITEP group conducted a superiority, assessor-blinded, multicenter randomized trial in 6 hospitals in Finland, Estonia, Sweden, and Denmark. Eighty-eight patients aged 60 years or older with displaced (more than 1 cm or 45 degrees) 2-part surgical or anatomical neck proximal humerus fracture were randomly assigned in a 1:1 ratio to undergo either operative treatment with a locking plate or non-operative treatment. The mean age of patients was 72 years in the non-operative group and 73 years in the operative group, with a female sex distribution of 95% and 87%, respectively. Patients were recruited between February 2011 and April 2016. The primary outcome measure was Disabilities of Arm, Shoulder, and Hand (DASH) score at 2-year follow-up. Secondary outcomes included Constant–Murley score, the visual analogue scale for pain, the quality of life questionnaire 15D, EuroQol Group’s 5- dimension self-reported questionnaire EQ-5D, the Oxford Shoulder Score, and complications. The mean DASH score (0 best, 100 worst) at 2 years was 18.5 points for the operative treatment group and 17.4 points for the non-operative group (mean difference 1.1 [95% CI −7.8 to 9.4], p = 0.81). At 2 years, there were no statistically or clinically significant between-group differences in any of the outcome measures. All 3 complications resulting in secondary surgery occurred in the operative group. The lack of blinding in patient-reported outcome assessment is a limitation of the study. Our assessor physiotherapists were, however, blinded. Conclusions This trial found no significant difference in clinical outcomes at 2 years between surgery and non-operative treatment in patients 60 years of age or older with displaced 2-part fractures of the proximal humerus. These results suggest that the current practice of performing surgery on the majority of displaced proximal 2-part fractures of the humerus in older adults may not be beneficial. Trial registration ClinicalTrials.gov NCT01246167.Peer reviewe

N-1-methylnicotinamide is a signalling molecule produced in skeletal muscle coordinating energy metabolism

Obesity is a major health problem, and although caloric restriction and exercise are successful strategies to lose adipose tissue in obese individuals, a simultaneous decrease in skeletal muscle mass, negatively effects metabolism and muscle function. To deeper understand molecular events occurring in muscle during weight-loss, we measured the expressional change in human skeletal muscle following a combination of severe caloric restriction and exercise over 4 days in 15 Swedish men. Key metabolic genes were regulated after the intervention, indicating a shift from carbohydrate to fat metabolism. Nicotinamide N-methyltransferase (NNMT) was the most consistently upregulated gene following the energy-deficit exercise. Circulating levels of N-1-methylnicotinamide (MNA), the product of NNMT activity, were doubled after the intervention. The fasting-fed state was an important determinant of plasma MNA levels, peaking at similar to 18 h of fasting and being lowest similar to 3 h after a meal. In culture, MNA was secreted by isolated human myotubes and stimulated lipolysis directly, with no effect on glucagon or insulin secretion. We propose that MNA is a novel myokine that enhances the utilization of energy stores in response to low muscle energy availability. Future research should focus on applying MNA as a biomarker to identify individuals with metabolic disturbances at an early stage.Peer reviewe