Targeting prostate cancer with Clostridium perfringens enterotoxin functionalized nanoparticles co-encapsulating imaging cargo enhances magnetic resonance imaging specificity.

Magnetic resonance is a key imaging tool for the detection of prostate cancer; however, better tools focusing on cancer specificity are required to distinguish benign from cancerous regions. We found higher expression of claudin-3 (CLDN-3) and -4 (CLDN-4) in higher grade than lower-grade human prostate cancer biopsies (n = 174), leading to the design of functionalized nanoparticles (NPs) with a non-toxic truncated version of the natural ligand Clostridium perfringens enterotoxin (C-CPE) that has a strong binding affinity to Cldn-3 and Cldn-4 receptors. We developed a first-of-its-type, C-CPE-NP-based MRI detection tool in a prostate tumor-bearing mouse model. NPs with an average diameter of 152.9 ±â€¯15.7 nm (RS1) had a 2-fold enhancement of tumor specificity compared to larger (421.2 ±â€¯33.8 nm) NPs (RS4). There was a 1.8-fold (P < 0.01) and 1.6-fold (P < 0.01) upregulation of the tumor-to-liver signal intensities of C-RS1 and C-RS4 (functionalized NPs) compared to controls, respectively. Also, tumor specificity was 3.1-fold higher (P < 0.001) when comparing C-RS1 to C-RS4. This detection tool improved tumor localization of contrast-enhanced MRI, supporting potential clinical applicability.

Development and Validation of ARC, a Model for Anticipating Acute Respiratory Failure in Coronavirus Disease 2019 Patients.

OBJECTIVES: To evaluate factors predictive of clinical progression among coronavirus disease 2019 patients following admission, and whether continuous, automated assessments of patient status may contribute to optimal monitoring and management. DESIGN: Retrospective cohort for algorithm training, testing, and validation. SETTING: Eight hospitals across two geographically distinct regions. PATIENTS: Two-thousand fifteen hospitalized coronavirus disease 2019-positive patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Anticipating Respiratory failure in Coronavirus disease (ARC), a clinically interpretable, continuously monitoring prognostic model of acute respiratory failure in hospitalized coronavirus disease 2019 patients, was developed and validated. An analysis of the most important clinical predictors aligns with key risk factors identified by other investigators but contributes new insights regarding the time at which key factors first begin to exhibit aberrency and distinguishes features predictive of acute respiratory failure in coronavirus disease 2019 versus pneumonia caused by other types of infection. Departing from prior work, ARC was designed to update continuously over time as new observations (vitals and laboratory test results) are recorded in the electronic health record. Validation against data from two geographically distinct health systems showed that the proposed model achieved 75% specificity and 77% sensitivity and predicted acute respiratory failure at a median time of 32 hours prior to onset. Over 80% of true-positive alerts occurred in non-ICU settings. CONCLUSIONS: Patients admitted to non-ICU environments with coronavirus disease 2019 are at ongoing risk of clinical progression to severe disease, yet it is challenging to anticipate which patients will develop acute respiratory failure. A continuously monitoring prognostic model has potential to facilitate anticipatory rather than reactive approaches to escalation of care (e.g., earlier initiation of treatments for severe disease or structured monitoring and therapeutic interventions for high-risk patients).

Distinguishing Benign Renal Tumors with an Oncocytic Gene Expression (ONEX) Classifier.

Renal oncocytoma (RO) accounts for 5% of renal cancers and generally behaves as a benign tumor with favorable long-term prognosis. It is difficult to confidently distinguish between benign RO and other renal malignancies, particularly chromophobe renal cell carcinoma (chRCC). Therefore, RO is often managed aggressively with surgery. We sought to identify molecular biomarkers to distinguish RO from chRCC and other malignant renal cancer mimics. In a 44-patient discovery cohort, we identified a significant differential abundance of nine genes in RO relative to chRCC. These genes were used to train a classifier to distinguish RO from chRCC in an independent 57-patient cohort. The trained classifier was then validated in five independent cohorts comprising 89 total patients. This nine-gene classifier trained on the basis of differential gene expression showed 93% sensitivity and 98% specificity for distinguishing RO from chRCC across the pooled validation cohorts, with a c-statistic of 0.978. This tool may be a useful adjunct to other diagnostic modalities to decrease the diagnostic and management uncertainty associated with small renal masses and to enable clinicians to recommend more confidently less aggressive management for some tumors. PATIENT SUMMARY: Renal oncocytoma is generally a benign form of kidney cancer that does not necessarily require surgical removal. However, it is difficult to distinguish renal oncocytoma from other more aggressive forms of kidney cancer, so it is treated most commonly with surgery. We built a classification tool based on the RNA levels of nine genes that may help avoid these surgeries by reliably distinguishing renal oncocytoma from other forms of kidney cancer.

Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence.

Increasingly, interventions aimed at improving care are likely to use such technologies as machine learning and artificial intelligence. However, health care has been relatively late to adopt them. This article provides clinical examples in which machine learning and artificial intelligence are already in use in health care and appear to deliver benefit. Three key bottlenecks toward increasing the pace of diffusion and adoption are methodological issues in evaluation of artificial intelligence-based interventions, reporting standards to enable assessment of model performance, and issues that need to be addressed for an institution to adopt these interventions. Methodological best practices will include external validation, ideally at a different site; use of proactive learning algorithms to correct for site-specific biases and increase robustness as algorithms are deployed across multiple sites; addressing subgroup performance; and communicating to providers the uncertainty of predictions. Regarding reporting, especially important issues are the extent to which implementing standardized approaches for introducing clinical decision support has been followed, describing the data sources, reporting on data assumptions, and addressing biases. Although most health care organizations in the United States have adopted electronic health records, they may be ill prepared to adopt machine learning and artificial intelligence. Several steps can enable this: preparing data, developing tools to get suggestions to clinicians in useful ways, and getting clinicians engaged in the process. Open challenges and the role of regulation in this area are briefly discussed. Although these techniques have enormous potential to improve care and personalize recommendations for individuals, the hype regarding them is tremendous. Organizations will need to approach this domain carefully with knowledgeable partners to obtain the hoped-for benefits and avoid failures.

A Review of Challenges and Opportunities in Machine Learning for Health.

Modern electronic health records (EHRs) provide data to answer clinically meaningful questions. The growing data in EHRs makes healthcare ripe for the use of machine learning. However, learning in a clinical setting presents unique challenges that complicate the use of common machine learning methodologies. For example, diseases in EHRs are poorly labeled, conditions can encompass multiple underlying endotypes, and healthy individuals are underrepresented. This article serves as a primer to illuminate these challenges and highlights opportunities for members of the machine learning community to contribute to healthcare.

A non-enzymatic method for dissection of mouse bladder urothelial tissue.

Urothelial cells contribute to bladder functions, including urine storage, urine emptying, and innate immune response. Functional studies of urothelial cells usually use either freshly isolated cells or cultured cells. Most methods of isolating urothelial cells require enzymes; however, these techniques remove proteins that connect the cells and disrupt the orientation of the cells within the multilayered urothelium. In addition, PCR or immunoblot results obtained from homogenates of bladder mucosa or whole bladder do not represent pure urothelial cells. We describe a dissection process that does not require enzymes and is able to obtain pure urothelial tissues from mice and humans. This method can isolate single urothelial cells for electrophysiology in situ and can also isolate pure urothelial tissue for PCR, microarray, and immunoblot procedures. The time required to obtain urothelial tissue from one mouse bladder is 15-20 min. This method is simple and time efficient as compared with alternative methods and therefore facilitates our understanding of urothelial biology.

The Yale Center for Biomedical Innovation and Technology (CBIT): One Model to Accelerate Impact From Academic Health Care Innovation.

The process of translating academic biomedical advances into clinical care improvements is difficult, risky, expensive, and poorly understood. Notably, many clinicians who identify health care problems do not have the time or expertise to solve the problems, and many academic researchers are unaware of important gaps in clinical care to which their expertise may apply.Recognizing an opportunity to connect people who can identify health care problems with those who can solve them, the Yale Center for Biomedical Innovation and Technology (CBIT) was established in 2014 to educate and enhance the impact of health care innovators. The authors review other health care innovation centers and describe best practices borrowed by Yale CBIT, which tailored its activities and approach to its unique ecosystem.In four years, Yale CBIT has affected over 3,000 people and established a health care innovation cycle as an efficient strategy to guide translational research. Yale CBIT has created or supported graduate and undergraduate courses, clinical immersion programs for industry partners, and large health care hackathon events. Over 200 projects have been submitted to CBIT for mentorship, and some of those projects have been commercialized and raised millions of dollars of follow-on funding.The authors present Yale CBIT as one model of accelerating the impact of academic medicine on clinical practice and outcomes. The project advising strategy is intended to be a template to maximize the efficiency of biomedical innovation and ultimately improve the outcomes and experiences of future patients.

Factors associated with physicians' prescriptions for rheumatoid arthritis drugs not filled by patients.

BACKGROUND: This study estimated the extent and predictors of primary nonadherence (i.e., prescriptions made by physicians but not initiated by patients) to methotrexate and to biologics or tofacitinib in rheumatoid arthritis (RA) patients who were newly prescribed these medications. METHODS: Using administrative claims linked with electronic health records (EHRs) from multiple healthcare provider organizations in the USA, RA patients who received a new prescription for methotrexate or biologics/tofacitinib were identified from EHRs. Claims data were used to ascertain filling or administration status. A logistic regression model for predicting primary nonadherence was developed and tested in training and test samples. Predictors were selected based on clinical judgment and LASSO logistic regression. RESULTS: A total of 36.8% of patients newly prescribed methotrexate failed to initiate methotrexate within 2 months; 40.6% of patients newly prescribed biologics/tofacitinib failed to initiate within 3 months. Factors associated with methotrexate primary nonadherence included age, race, region, body mass index, count of active drug ingredients, and certain previously diagnosed and treated conditions at baseline. Factors associated with biologics/tofacitinib primary nonadherence included age, insurance, and certain previously treated conditions at baseline. The area under the receiver operating characteristic curve of the logistic regression model estimated in the training sample and applied to the independent test sample was 0.86 and 0.78 for predicting primary nonadherence to methotrexate and to biologics/tofacitinib, respectively. CONCLUSIONS: This study confirmed that failure to initiate new prescriptions for methotrexate and biologics/tofacitinib was common in RA patients. It is feasible to predict patients at high risk of primary nonadherence to methotrexate and to biologics/tofacitinib and to target such patients for early interventions to promote adherence.

Prostate zonal anatomy correlates with the detection of prostate cancer on multiparametric magnetic resonance imaging/ultrasound fusion-targeted biopsy in patients with a solitary PI-RADS v2-scored lesion.

PURPOSE: To evaluate the positive predictive value (PPV) of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) assessment method in patients with a single suspicious finding on prostate multiparametric magnetic resonance imaging (mpMRI). PATIENTS AND METHODS: A total of 176 patients underwent MRI/ultrasound fusion-targeted prostate biopsy after the detection of a single suspicious finding on mpMRI. The PPV for cancer detection was determined based on PI-RADS v2 assessment score and location. RESULTS: Fusion biopsy detected prostate cancer in 60.2% of patients. Of these patients, 69.8% had Gleason score (GS) ≥7 prostate cancer. Targeted biopsy detected 90.5% of all GS≥7 prostate cancer. The PPV for GS≥7 detection of PI-RADS v2 category 5 (P5) and category 4 (P4) lesions was 70.2% and 37.7%, respectively. This increased to 88% and 38.5% for P5 and P4 lesions in the peripheral zone (PZ), respectively. Targeted biopsy did not miss GS≥7 disease compared with systematic biopsy in P5 lesions in the PZ and transition zone. CONCLUSION: The PPV of PI-RADS v2 for prostate cancer in patients with a single lesion on mpMRI is dependent on PI-RADS assessment category and location. The highest PPV was for a P5 lesion in the PZ.

Negative Multiparametric Magnetic Resonance Imaging of the Prostate Predicts Absence of Clinically Significant Prostate Cancer on 12-Core Template Prostate Biopsy.

OBJECTIVE: To determine the negative predictive value of multiparametric magnetic resonance imaging (mpMRI), we evaluated the frequency of prostate cancer detection by 12-core template mapping biopsy in men whose mpMRI showed no suspicious regions. METHODS: Six hundred seventy patients underwent mpMRI followed by transrectal ultrasound (TRUS)-guided systematic prostate biopsy from December 2012 to June 2016. Of this cohort, 100 patients had a negative mpMRI. mpMRI imaging sequences included T2-weighted and diffusion-weighted imaging, and dynamic contrast enhancement sequences. RESULTS: The mean age, prostate-specific antigen, and prostate volume of the 100 men included were 64.3 years, 7.2 ng/mL, and 71 mL, respectively. Overall cancer detection was 27% (27 of 100). Prostate cancer was detected in 26.3% (10 of 38) of patients who were biopsy-naïve, 12.1% (4 of 33) of patients who had a prior negative biopsy, and in 44.8% (13 of 29) of patients previously on active surveillance; Gleason grade ≥7 was detected in 3% of patients overall (3 of 100). The negative predictive value of a negative mpMRI was 73% for all prostate cancer and 97% for Gleason ≥7 prostate cancer. CONCLUSION: There is an approximately 3% chance of detecting clinically significant prostate cancer with systematic TRUS-guided biopsy in patients with no suspicious findings on mpMRI. This information should help guide recommendations to patients about undergoing systematic TRUS-guided biopsy when mpMRI is negative.

Prevalence of incidental findings on abdominal computed tomography angiograms on prospective renal donors.

OBJECTIVE: To evaluate the prevalence of incidental findings on preoperative abdominal computed tomography angiography-computed tomography urography in asymptomatic prospective renal donors. METHODS: A Health Insurance Portability and Accountability Act (HIPAA)-compliant, Institutional Review Board (IRB)-approved retrospective study of 1,597 subjects undergoing renal transplant evaluation from June 1, 2006, to March 31, 2011, was performed. Candidates underwent multiphasic multidetector computed tomography angiography-computed tomography urography for presurgical evaluation of renal vascular and parenchymal anatomy. All scans were reviewed by one of three fellowship-trained abdominal radiologists. The diagnoses were made on the basis of computed tomography characteristics of each lesion, and pathology confirmation was available for seven patients. We calculated the prevalence of each incidental finding, performed Fisher exact test or chi-square test for categorical variables between the cohort that did and did not undergo donor nephrectomy, and performed simple linear logistic regression analysis of incidental findings which predicted renal donation. RESULTS: Of the 1,597 potential donors, 58.4% were female, and the mean age was 42.6 years (range, 18-74). One thousand one hundred ninety-five (74.9%) had a total of 2,105 incidental findings. Based on American College of Radiology Incidental Findings Committee White Paper on Managing Incidental Findings on Abdominal Computed Tomography, 17.3% had incidentalomas and 1.1% required follow-up. Majority of the incidental findings (16 of 17) were in patients who did not undergo renal donation. The prevalence of pathologically proven malignancy was 0.1% (3 of 1,597). CONCLUSION: Preoperative computed tomography angiography-computed tomography urography not only identifies vascular anatomy but may also help detect clinically significant unanticipated findings in an otherwise healthy population.

A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases.

Making accurate prognoses in chronic, complex diseases is challenging due to the wide variation in expression across individuals. In many such diseases, the notion of subtypes-subpopulations that share similar symptoms and patterns of progression-have been proposed. We develop a probabilistic model that exploits the concept of subtypes to individualize prognoses of disease trajectories. These subtypes are learned automatically from data. On a new individual, our model incorporates static and time-varying markers to dynamically update predictions of subtype membership and provide individualized predictions of disease trajectory. We use our model to tackle the problem of predicting lung function trajectories in scleroderma, an autoimmune disease, and demonstrate improved predictive performance over existing approaches.

Evolution of laparoscopic donor nephrectomy technique and outcomes: a single-center experience with more than 1300 cases.

OBJECTIVE: To describe and illustrate the evolution of surgical technique, emphasizing technical modifications of laparoscopic donor nephrectomy (LDN) and the impact on complication outcome. METHODS: This is a retrospective observational study of prospectively collected data on all consecutive purely LDN surgeries performed at a tertiary academic medical center (n = 1325), performed between March 2000 and October 2013. RESULTS: Over time, LDN was performed on older patients, changing from a mean of 35.7 years in 2000 to 41.2 years in 2013 (P <.001). Additionally, mean blood loss decreased from 75 mL in 2000 to 21.6 mL in 2013 (P <.001). However, body mass index, operative time, and length of stay remained similar. Overall, there were 105 (7.9%) complications: Clavien grade 1 (n = 81, 6.1%) and grade 2 or higher (n = 23, 1.8%). Procedure duration, blood loss, surgeon, year of procedure, laterality, body mass index, age, and gender did not significantly predict complications. There was no significant difference for Clavien complication rates between the early learning period (first 150 cases) and the rest of the series. CONCLUSION: With continual refinement with LDN techniques based on intraoperative observations and technological advances, complication rates remain consistently low, despite increasing donor age.

Association of type of renal surgery and access to robotic technology for kidney cancer: results from a population-based cohort.

OBJECTIVE: To evaluate the relationship between partial nephrectomy (PN) and hospital availability of robot-assisted surgery from a population-based cohort in the USA. METHODS: After merging the Nationwide Inpatient Sample (NIS) and the American Hospital Association survey from 2006 to 2008, we identified 21 179 patients who underwent either PN or radical nephrectomy (RN) for renal cell carcinoma (RCC). The primary outcome assessed was the type of nephrectomy performed. Multivariable logistic regression identified the patient and hospital characteristics associated with receipt of PN. RESULTS: We identified 4832 (22.8%) and 16 347 (77.2%) patients who were treated for RCC with PN and RN, respectively. On multivariable analysis, patients were more likely to receive PN at academic centres (odds ratio [OR] 2.77; P < 0.001), urban centres (OR 3.66; P < 0.001) and American College of Surgeons (ACOS)-designated cancer centres (OR: 1.10; P < 0.05) compared with non-academic, rural and non-ACOS-designated cancer centre hospitals, respectively. Robot-assisted surgery availability at a hospital was also associated with a higher adjusted odds of PN compared with centres without that availability (OR 1.28; P < 0.001). CONCLUSIONS: Although academic and urban locations are established factors that affect the receipt of PN for RCC, the availability of robot-assisted surgery at a hospital was also independently associated with higher use of PN. Our results are informative in identifying other key hospital characteristics which may facilitate greater adoption of PN.

Determinants of laparoscopic donor nephrectomy outcomes.

BACKGROUND: Pure laparoscopic donor nephrectomy (LDN) is a unique intervention because it carries known risks and complications, yet carries no direct benefit to the donor. Therefore, it is critical to continually examine and improve quality of care. OBJECTIVE: To identify factors affecting LDN outcomes and complications. DESIGN, SETTING, AND PARTICIPANTS: A retrospective analysis of prospectively collected data for 1204 consecutive LDNs performed from March 2000 through August 2012. INTERVENTION: LDN performed at an academic training center. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Using multivariable regression, we assessed the effect of age, sex, body mass index (BMI), laterality, and vascular variation on operative time, estimated blood loss (EBL), complications, and length of stay. RESULTS AND LIMITATIONS: The following variables were associated with longer operative time (data given as parameter estimate plus or minus the standard error): female sex (9.09 ± 2.43; p<0.001), higher BMI (1.03 ± 0.32; p=0.001), two (7.87 ± 2.70; p=0.004) and three or more (22.45 ± 7.13; p=0.002) versus one renal artery, and early renal arterial branching (5.67 ± 2.82; p=0.045), while early renal arterial branching (7.81 ± 3.85; p=0.043) was associated with higher EBL. Overall, 8.2% of LDNs experienced complications, and by modified Clavien classification, 74 (5.9%) were grade 1, 13 (1.1%) were grade 2a, 10 (0.8%) were grade 2b, and 2 (0.2%) were grade 2c. There were no grade 3 or 4 complications. Three or more renal arteries (odds ratio [OR]: 2.74; 95% CI, 1.05-7.16; p=0.04) and late renal vein confluence (OR: 2.42; 95% CI, 1.50-3.91; p=0.0003) were associated with more complications. Finally, we did not find an association of the independent variables with length of stay. A limitation is that warm ischemia time was not assessed. CONCLUSIONS: In our series, renal vascular variation prolonged operative time and was associated with more complications. While complicated donor anatomy is not a contraindication of LDN, surgical decision-making should take into consideration these results.

Implantable electrolyte conductance-based pressure sensing catheter, II. Device construction and testing.

Direct measurements of arterial blood pressure most commonly use bulky external instrumentation containing a pressure transducer connected to an ex vivo fluid-filled arterial line, which is subject to several sensing artifacts. In situ blood pressure sensors, typically solid state piezoresistive, capacitive, and interferometric sensors, are unaffected by these artifacts, but can be expensive to produce and miniaturize. We have developed an alternative approach to blood pressure measurement based on deformation of an elastic tube filled with electrolyte solution. Simple measurement of the electrical conductance of this solution as the tube dimensions change allows determination of the external pressure. The sensor is made from inexpensive materials and its miniaturization is straightforward. In vitro static testing of initial sensor prototypes mounted on a catheter tip showed a linear response with applied pressure and a resolution of 1 mmHg. In vivo sensing followed catheterization of the sensor into the femoral artery of a porcine model through a 7F catheter port. The sensor performed comparably to a commercial pressure transducer also connected to the catheter port. Due to its scalability and cost, this sensor has the potential for use in a range of pressure sensing applications, such as measurement of intracranial, spinal, or interstitial pressures.

Implantable electrolyte conductance-based pressure sensing catheter, I. Modeling.

Direct measurements of arterial blood pressure most commonly use bulky external instrumentation containing a pressure transducer connected to an ex vivo fluid-filled arterial line, which is subject to several sensing artifacts. In situ blood pressure sensors, typically solid state piezoresistive, capacitive, and interferometric sensors, are unaffected by these artifacts, but can be expensive to produce and miniaturize. We have developed an alternative approach to blood pressure measurement based on deformation of an elastic tube filled with electrolyte solution. We have constructed an analytical model describing the deformation of a fluid-filled tube part of which is exposed to external pressure, with the remaining part unexposed. The model predicts pressure-induced change in dimension of the internal electrolyte-filled volume and a resultant change in its electrical resistance, which can be measured to determine the pressure and is the basis for the sensor operation. We have applied the model to find the pressure sensitivity of fractional change in resistance as a function of device material and dimensional parameters. Construction and testing of a device is described in the following paper.

Diffusion tensor magnetic resonance tractography of the prostate: feasibility for mapping periprostatic fibers.

OBJECTIVE: To evaluate the feasibility of diffusion tensor imaging (DTI) tractography of the prostate for mapping of periprostatic neurovascular anatomy. METHODS: Eight men with prostate cancer scheduled to undergo nerve-sparing robot-assisted radical prostatectomy (RARP) underwent endorectal multiparametric magnetic resonance imaging (MRI) of the prostate with DTI. Tract mapping was accomplished by positioning spherical regions of interest contiguously along the prostatic capsule at the prostatic apex, midgland, and base. RESULTS: DTI tractography of the prostate effectively visualized periprostatic fiber tract anatomy. There was no significant correlation between total tract number and prostate size, however (Spearman's coefficient = 0.33, P = .42). Variation in tract distribution existed. The total fiber mass was highest in the lower prostate hemisphere at the base of the prostate (mean = 36.9 vs 21.1, P = .0004) and in the upper hemisphere at the apex (mean = 41.6 vs 57.9, P = .006). CONCLUSION: DTI tractography successfully visualized fiber tracts around the prostate. Gold standard anatomic correlation is needed.

A transurethral catheter-based ultrasound system for multi-modal fusion.

Current methods of prostate cancer diagnosis and therapy rely on accurate imaging of the prostate using real-time ultrasound. Transurethral ultrasound (TUUS) may improve upon the current gold standard through improved 3D visualization and co-registration (fusion) with CT and MRI. A prototype transurethral ultrasound (TUUS) catheter-based transducer array and system was developed, featuring 32 elements with a diameter of 18F (6mm). A robust, multi-channel ultrasound transceiver was also developed to enable TUUS imaging using pulse-echo and frequency-based signal processing methods. The feasibility of a TUUS imaging system suitable for multi-modal image fusion and novel ultrasound signaling techniques was demonstrated.