Applying deep learning to segmentation of murine lung tumors in pre-clinical micro-computed tomography.

Lung cancer remains a leading cause of cancer-related death, but scientists have made great strides in developing new treatments recently, partly owing to the use of genetically engineered mouse models (GEMMs). GEMM tumors represent a translational model that recapitulates human disease better than implanted models because tumors develop spontaneously in the lungs. However, detection of these tumors relies on in vivo imaging tools, specifically micro-Computed Tomography (micro-CT or µCT), and image analysis can be laborious with high inter-user variability. Here we present a deep learning model trained to perform fully automated segmentation of lung tumors without the interference of other soft tissues. Trained and tested on 100 3D µCT images (18,662 slices) that were manually segmented, the model demonstrated a high correlation to manual segmentations on the testing data (r2=0.99, DSC=0.78) and on an independent dataset (n = 12 3D scans or 2328 2D slices, r2=0.97, DSC=0.73). In a comparison against manual segmentation performed by multiple analysts, the model (r2=0.98, DSC=0.78) performed within inter-reader variability (r2=0.79, DSC=0.69) and close to intra-reader variability (r2=0.99, DSC=0.82), all while completing 5+ hours of manual segmentations in 1 minute. Finally, when applied to a real-world longitudinal study (n = 55 mice), the model successfully detected tumor progression over time and the differences in tumor burden between groups induced with different virus titers, aligning well with more traditional analysis methods. In conclusion, we have developed a deep learning model which can perform fast, accurate, and fully automated segmentation of µCT scans of murine lung tumors.

Volumetric imaging of optically cleared and fluorescently labeled animal tissue (VIOLA) for quantifying the 3D biodistribution of nanoparticles at cellular resolution in tumor tissue.

Nanoparticle (NP) technology holds significant promise to mediate targeted drug delivery to specific organs in the body. Understanding the 3D biodistribution of NPs in heterogeneous environments such as the tumor tissue can provide crucial information on efficacy, safety and potential clinical outcomes. Here we present a novel end-to-end workflow, VIOLA, which makes use of tissue clearing methodology in conjunction with high resolution imaging and advanced 3D image processing to quantify the spatiotemporal 3D biodistribution of fluorescently labeled ACCURIN® NPs. Specifically, we investigate the spatiotemporal biodistribution of NPs in three different murine tumor models (CT26, EMT6, and KPC-GEM) of increasing complexity and translational relevance. We have developed new endpoints to characterize NP biodistribution at multiple length scales. Our observations reveal that the macroscale NP biodistribution is spatially heterogeneous and exhibits a gradient with relatively high accumulation at the tumor periphery that progressively decreases towards the tumor core in all the tumor models. Microscale analysis revealed that NP extravasation from blood vessels increases in a time dependent manner and plateaus at 72 h post injection. Volumetric analysis and pharmacokinetic modeling of NP biodistribution in the vicinity of the blood vessels revealed that the local NP density exhibits a distance dependent spatiotemporal biodistribution which provide insights into the dynamics of NP extravasation in the tumor tissue. Our data represents a comprehensive analysis of NP biodistribution at multiple length scales in different tumor models providing unique insights into their spatiotemporal dynamics. Specifically, our results show that NPs exhibit a dynamic equilibrium with macroscale heterogeneity combined with microscale homogeneity.

Mouse lung automated segmentation tool for quantifying lung tumors after micro-computed tomography.

Unlike the majority of cancers, survival for lung cancer has not shown much improvement since the early 1970s and survival rates remain low. Genetically engineered mice tumor models are of high translational relevance as we can generate tissue specific mutations which are observed in lung cancer patients. Since these tumors cannot be detected and quantified by traditional methods, we use micro-computed tomography imaging for longitudinal evaluation and to measure response to therapy. Conventionally, we analyze microCT images of lung cancer via a manual segmentation. Manual segmentation is time-consuming and sensitive to intra- and inter-analyst variation. To overcome the limitations of manual segmentation, we set out to develop a fully-automated alternative, the Mouse Lung Automated Segmentation Tool (MLAST). MLAST locates the thoracic region of interest, thresholds and categorizes the lung field into three tissue categories: soft tissue, intermediate, and lung. An increase in the tumor burden was measured by a decrease in lung volume with a simultaneous increase in soft and intermediate tissue quantities. MLAST segmentation was validated against three methods: manual scoring, manual segmentation, and histology. MLAST was applied in an efficacy trial using a Kras/Lkb1 non-small cell lung cancer model and demonstrated adequate precision and sensitivity in quantifying tumor growth inhibition after drug treatment. Implementation of MLAST has considerably accelerated the microCT data analysis, allowing for larger study sizes and mid-study readouts. This study illustrates how automated image analysis tools for large datasets can be used in preclinical imaging to deliver high throughput and quantitative results.

Characteristics, Comorbidities, and Outcomes in a Multicenter Registry of Patients With Human Immunodeficiency Virus and Coronavirus Disease 2019.

BACKGROUND: People living with human immunodeficiency virus (HIV) may have numerous risk factors for acquiring coronavirus disease 2019 (COVID-19) and developing severe outcomes, but current data are conflicting. METHODS: Health-care providers enrolled consecutively, by nonrandom sampling, people living with HIV (PWH) with lab-confirmed COVID-19, diagnosed at their facilities between 1 April and 1 July 2020. Deidentified data were entered into an electronic Research Electronic Data Capture (REDCap) system. The primary endpoint was a severe outcome, defined as a composite endpoint of intensive care unit (ICU) admission, mechanical ventilation, or death. The secondary outcome was the need for hospitalization. RESULTS: There were 286 patients included; the mean age was 51.4 years (standard deviation, 14.4), 25.9% were female, and 75.4% were African American or Hispanic. Most patients (94.3%) were on antiretroviral therapy, 88.7% had HIV virologic suppression, and 80.8% had comorbidities. Within 30 days of testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 164 (57.3%) patients were hospitalized, and 47 (16.5%) required ICU admission. Mortality rates were 9.4% (27/286) overall, 16.5% (27/164) among those hospitalized, and 51.5% (24/47) among those admitted to an ICU. The primary composite endpoint occurred in 17.5% (50/286) of all patients and 30.5% (50/164) of hospitalized patients. Older age, chronic lung disease, and hypertension were associated with severe outcomes. A lower CD4 count (<200 cells/mm3) was associated with the primary and secondary endpoints. There were no associations between the ART regimen or lack of viral suppression and the predefined outcomes. CONCLUSIONS: Severe clinical outcomes occurred commonly in PWH with COVID-19. The risks for poor outcomes were higher in those with comorbidities and lower CD4 cell counts, despite HIV viral suppression. CLINICAL TRIALS REGISTRATION: NCT04333953.

Glioma-Induced Alterations in Neuronal Activity and Neurovascular Coupling during Disease Progression.

Diffusely infiltrating gliomas are known to cause alterations in cortical function, vascular disruption, and seizures. These neurological complications present major clinical challenges, yet their underlying mechanisms and causal relationships to disease progression are poorly characterized. Here, we follow glioma progression in awake Thy1-GCaMP6f mice using in vivo wide-field optical mapping to monitor alterations in both neuronal activity and functional hemodynamics. The bilateral synchrony of spontaneous neuronal activity gradually decreases in glioma-infiltrated cortical regions, while neurovascular coupling becomes progressively disrupted compared to uninvolved cortex. Over time, mice develop diverse patterns of high amplitude discharges and eventually generalized seizures that appear to originate at the tumors' infiltrative margins. Interictal and seizure events exhibit positive neurovascular coupling in uninfiltrated cortex; however, glioma-infiltrated regions exhibit disrupted hemodynamic responses driving seizure-evoked hypoxia. These results reveal a landscape of complex physiological interactions occurring during glioma progression and present new opportunities for exploring novel biomarkers and therapeutic targets.

High Cost and Low Yield: The Diagnostic Evaluation of Rumination Syndrome in Pediatrics.

OBJECTIVE: To document the use of diagnostic testing in adolescents who ultimately were diagnosed with rumination syndrome, a functional gastrointestinal disorder. We examined the diagnostic yield of each test as well as the associated costs, and we determined if any demographic or illness-related variables impacted the magnitude of the work-up. STUDY DESIGN: A retrospective chart review was conducted for 68 patients with rumination syndrome admitted to our inpatient treatment program. The cost and findings of patients' diagnostic investigations were gathered, as well as demographic and illness-related variables to determine factors that may be related to evaluation size. RESULTS: The most commonly used tests in the evaluation of rumination syndrome included esophagogastroduodenoscopy, gastric emptying, antroduodenal manometry, upper gastrointestinal series, and abdominal ultrasound scan. Each patient underwent an average of 8.8 tests, with the average cost for each patient's diagnostic work-up being US $19 795. Few tests were found to be beneficial in the diagnosis of rumination syndrome, and few demographic or illness variables were found to be related to the overall extent of the investigation. CONCLUSIONS: Extensive testing for rumination syndrome in adolescents is common in clinical practice, and comes at a high financial cost with low yield, likely delaying diagnosis and treatment. Symptom-based criteria should be used to make the diagnosis of rumination syndrome.

Rapid-Growing Mycobacteria Infections in Medical Tourists: Our Experience and Literature Review.

BACKGROUND: "Medical tourism" has gained popularity over the past few decades. This is particularly common with patients seeking elective cosmetic surgery in the developing world. However, the risk of severe and unusual infectious complications appears to be higher than for patients undergoing similar procedures in the United States. OBJECTIVES: The authors describe their experience with atypical mycobacterial infections in cosmetic surgical patients returning to the United States postoperatively. METHODS: A review of patient medical records presenting with infectious complications after cosmetic surgery between January 2010 and July 2015 was performed. Patients presenting with mycobacterial infections following cosmetic surgery were reviewed in detail. An extensive literature review was performed for rapid-growing mycobacteria (RGM) related to cosmetic procedures. RESULTS: Between January 2010 and July 2015, three patients presented to our institution with culture-proven Mycobacterium abscessus at the sites of recent cosmetic surgery. All had surgery performed in the developing world. The mean age of these patients was 36 years (range, 29-44 years). There was a delay of up to 16 weeks between the initial presentation and correct diagnosis. All patients were treated with surgical drainage and combination antibiotics with complete resolution. CONCLUSIONS: We present series of patients with mycobacterial infections after cosmetic surgery in the developing world. This may be related to the endemic nature of these bacteria and/or inadequate sterilization or sterile technique. Due to low domestic incidence of these infections, diagnosis may be difficult and/or delayed. Consulting physicians should have a low threshold to consider atypical etiologies in such scenarios. LEVEL OF EVIDENCE: 5 Therapeutic.

RNA interference: historical overview and significance.

In the early 1990s, attempts to manipulate gene expression by researchers working in three different fields resulted in unanticipated gene silencing. Rather than ignoring such results, these researchers went on to document and further investigate the nature of such silencing, which was named "co-suppression" in plants, "quelling" in fungi, and "RNA interference" (RNAi) in nematodes. By the late 1990s, it was discovered that silencing could be initiated in this diverse set of organisms by exposing cells to double-stranded RNA (dsRNA), which directed the destruction of mRNAs containing similar sequences. Soon afterward, such dsRNA-mediated silencing was employed as a reverse genetic technique to analyze the functions of specific genes in a broad variety of organisms. Biochemical and genetic studies designed to uncover the components of the RNA silencing machinery identified a common core of proteins that serve to amplify the interfering RNA signal and direct endonucleolytic cleavage of target RNAs. A subset of silencing events may also direct DNA methylation of targeted genes. RNA silencing is thought to have evolved as a defense mechanism to suppress viral replication and transposon mobilization. However, additional functions involving the RNAi machinery have been uncovered, including posttranscriptional regulation of endogenous genes, and maintenance of structure and function of heterochromatin. Whereas many researchers have focused on understanding the natural biological functions of RNA silencing, others are testing its utility in antiviral and cancer therapies and in other biotechnological and biomedical applications.

Queensland public sector nurse executives: professional development needs.

In a time of health care reform and rapid change, nurse executives need effective leadership skills to be able to respond to a challenging environment, provide quality cost-effective care and promote the professional development of nursing. This research aimed to provide an understanding of nursing executives' roles and professional development needs and obtain concise information for the development of strategies and professional development programs to enhance the effectiveness of the present and future roles of nursing executives. A descriptive cross-sectional postal survey was sent to all public sector Level 4 and 5 nursing executives in Queensland (n = 281), with a response rate of 52.3% (n = 147). Financial management, human resource management and information technologies were identified as the areas where professional development was most needed. Structured educational activities such as short courses or seminars covering information technology, financial and budget management and general business management were identified as the type of activities best suited to nurse executives' needs. The most frequently reported barriers to professional development were difficulties obtaining relief staff, inadequate time, financial cost and inadequate district manager and regional support to enable access to professional development programs.