Contour subregion error detection methodology using deep learning auto-segmentation.

BACKGROUND: Inaccurate manual organ delineation is one of the high-risk failure modes in radiation treatment. Numerous automated contour quality assurance (QA) systems have been developed to assess contour acceptability; however, manual inspection of flagged cases is a time-consuming and challenging process, and can lead to users overlooking the exact error location. PURPOSE: Our aim is to develop and validate a contour QA system that can effectively detect and visualize subregional contour errors, both qualitatively and quantitatively. METHODS/MATERIALS: A novel contour subregion error detection (CSED) system was developed using subregional surface distance discrepancies between manual and deep learning auto-segmentation (DLAS) contours. A validation study was conducted using a head and neck public dataset containing 339 cases and evaluated according to knowledge-based pass criteria derived from a clinical training dataset of 60 cases. A blind qualitative evaluation was conducted, comparing the results from the CSED system with manual labels. Subsequently, the CSED-flagged cases were re-examined by a radiation oncologist. RESULTS: The CSED system could visualize the diverse types of subregional contour errors qualitatively and quantitatively. In the validation dataset, the CSED system resulted in true positive rates (TPR) of 0.814, 0.800, and 0.771; false positive rates (FPR) of 0.310, 0.267, and 0.298; and accuracies of 0.735, 0.759, and 0.730, for brainstem and left and right parotid contours, respectively. The CSED-assisted manual review caught 13 brainstem, 19 left parotid, and 21 right parotid contour errors missed by conventional human review. The TPR/FPR/accuracy of the CSED-assisted manual review improved to 0.836/0.253/0.784, 0.831/0.171/0.830, and 0.808/0.193/0.807 for each structure, respectively. Further, the time savings achieved through CSED-assisted review improved by 75%, with the time for review taking 24.81 ± 12.84, 26.75 ± 10.41, and 28.71 ± 13.72 s for each structure, respectively. CONCLUSIONS: The CSED system enables qualitative and quantitative detection, localization, and visualization of manual segmentation subregional errors utilizing DLAS contours as references. The use of this system has been shown to help reduce the risk of high-risk failure modes resulting from inaccurate organ segmentation.

Contouring quality assurance methodology based on multiple geometric features against deep learning auto-segmentation.

BACKGROUND: Contouring error is one of the top failure modes in radiation treatment. Multiple efforts have been made to develop tools to automatically detect segmentation errors. Deep learning-based auto-segmentation (DLAS) has been used as a baseline for flagging manual segmentation errors, but those efforts are limited to using only one or two contour comparison metrics. PURPOSE: The purpose of this research is to develop an improved contouring quality assurance system to identify and flag manual contouring errors. METHODS AND MATERIALS: DLAS contours were used as a reference to compare with manually segmented contours. A total of 27 geometric agreement metrics were determined from the comparisons between the two segmentation approaches. Feature selection was performed to optimize the training of a machine learning classification model to identify potential contouring errors. A public dataset with 339 cases was used to train and test the classifier. Four independent classifiers were trained using five-fold cross validation, and the predictions from each classifier were ensembled using soft voting. The trained model was validated on a held-out testing dataset. An additional independent clinical dataset with 60 cases was used to test the generalizability of the model. Model predictions were reviewed by an expert to confirm or reject the findings. RESULTS: The proposed machine learning multiple features (ML-MF) approach outperformed traditional nonmachine-learning-based approaches that are based on only one or two geometric agreement metrics. The machine learning model achieved recall (precision) values of 0.842 (0.899), 0.762 (0.762), 0.727 (0.842), and 0.773 (0.773) for Brainstem, Parotid_L, Parotid_R, and mandible contours, respectively compared to 0.526 (0.909), 0.619 (0.765), 0.682 (0.882), 0.773 (0.568) for an approach based solely on Dice similarity coefficient values. In the external validation dataset, 66.7, 93.3, 94.1, and 58.8% of flagged cases were confirmed to have contouring errors by an expert for Brainstem, Parotid_L, Parotid_R, and mandible contours, respectively. CONCLUSIONS: The proposed ML-MF approach, which includes multiple geometric agreement metrics to flag manual contouring errors, demonstrated superior performance in comparison to traditional methods. This method is easy to implement in clinical practice and can help to reduce the significant time and labor costs associated with manual segmentation and review.

Development of a virtual source model for Monte Carlo-based independent dose calculation for varian linac.

Monte Carlo (MC) independent dose calculations are often based on phase-space files (PSF), as they can accurately represent particle characteristics. PSF generally are large and create a bottleneck in computation time. In addition, the number of independent particles is limited by the PSF, preventing further reduction of statistical uncertainty. The purpose of this study is to develop and validate a virtual source model (VSM) to address these limitations. Particles from existing PSF for the Varian TrueBeam medical linear accelerator 6X, 6XFFF, 10X, and 10XFFF beam configurations were tallied, analyzed, and used to generate a dual-source photon VSM that includes electron contamination. The particle density distribution, kinetic energy spectrum, particle direction, and the correlations between characteristics were computed. The VSM models for each beam configuration were validated with water phantom measurements as well as clinical test cases against the original PSF. The new VSM requires 67 MB of disk space for each beam configuration, compared to 50 GB for the PSF from which they are based and effectively remove the bottleneck set by the PSF. At 3% MC uncertainty, the VSM approach reduces the calculation time by a factor of 14 on our server. MC doses obtained using the VSM approach were compared against PSF-generated doses in clinical test cases and measurements in a water phantom using a gamma index analysis. For all tests, the VSMs were in excellent agreement with PSF doses and measurements (>90% passing voxels between doses and measurements). Results of this study indicate the successful derivation and implementation of a VSM model for Varian Linac that significantly saves computation time without sacrificing accuracy for independent dose calculation.

Investigation of absolute dose calibration accuracy for TomoTherapy using real water.

A systematic bias in TomoTherapy output calibration was reported by the Imaging and Radiation Oncology Core Houston (IROC-H) after analyzing intensity-modulated radiation therapy (IMRT) credentialing results from hundreds of TomoTherapy units. Multiple theories were developed to explain this observation. One theory was that the use of a solid water "cheese" phantom instead of real water in the calibration measurement was the culprit. A phantom filled with distilled water was built to investigate whether our TomoTherapy was miscalibrated due to the use of a solid water phantom. A miscalibration of -1.47% was detected on our TomoTherapy unit. It is found that despite following the vendor's updated recommendation on computed tomography (CT) number to density calibration, the cheese phantom was still mapped to a density of 1.028 g/cm3 , rather than the 1.01 g/cm3 value reported in literature. When the density of the cheese phantom was modified to 1.01 g/cm3 in the treatment planning system, the measurement also indicated that our TomoTherapy machine was miscalibrated by -1.52%, agreeing with the real water phantom findings. Our single-institution finding showed that the cheese phantom density assignment can introduce greater than 1% errors in the TomoTherapy absolute dose calibration. It is recommended that the absolute dose calibration for TomoTherapy be performed either in real water or in the cheese phantom with the density in TPS overridden as 1.01 g/cm3 .

Congenitally Malformed Hearts: Aspects of Teaching and Research Involving Medical Students.

To appreciate congenital heart disease fully, a detailed understanding of the anatomical presentation, as well as the physiology, is required. This is often introduced at an advanced stage of training. Professor Anderson has been influential in the Clinical Anatomy Intercalated BSc programme at the University of Birmingham, in particular in his teaching on Sequential Segmental Analysis. This article describes the experiences of the latest cohort of students on this programme, who undertook varying research projects using the Birmingham Cardiac Archive, with the guidance of Professor Anderson. The projects outlined include various aspects of isomerism, encompassing both the cardiac and abdominal manifestations, as well as details of congenitally corrected transposition of the great arteries and prenatally diagnosed right aortic arch and double arch. These studies all aimed to increase the knowledge base of their respective cardiac malformations and provide a basis for further research.

Immunohistochemical profile of the anti-apoptosis, apoptosis and proliferation markers Bcl-2, caspase-3, p53, and Ki-67 in botryoid odontogenic cysts compared to lateral periodontal cysts and gingival cysts of the adult.

We investigated the differences in growth and rates of recurrence of the botryoid odontogenic cyst (BOC) and the less aggressive lateral periodontal cyst (LPC) and gingival cyst of the adult (GCA). We compared the immunohistochemical expression of selected biomarkers of apoptosis and proliferation and of regulators of their activity. Sections from archival paraffin blocks of 15 BOCs, six GCAs, six LPCs, and three odontogenic keratocysts (OKCs) were processed for immunohistochemical localization of Bcl-2, caspase-3, p53 and Ki-67. Labeled and unlabeled epithelial cells were counted and differences in the mean labeling index (LI) were evaluated statistically. The only significant differences in LI were for the anti-apoptotic marker, Bcl-2; the hierarchy was BOC > OKC > LPC > GCA. In two BOCs, 97% of the cells, and in all OKCs, all of the basal cells were labeled with Bcl-2. Otherwise, cells labeled with Bcl-2, p53 and caspase-3 were scattered among the basal and intermediate epithelial cell layers. Ki-67 labeled almost exclusively basal cells in the BOCs, LPCs and GCAs, and both basal and intermediate layer cells in the OKCs. Our findings suggest that while there was no significant difference in replicative potential of the GCAs, LPCs and BOCs, factors that influence apoptosis may be partially responsible for the more aggressive behavior of BOCs and OKCs.

Genome-wide DNA methylation profiling in human breast tissue by Illumina TruSeq methyl capture EPIC sequencing and infinium methylationEPIC beadchip microarray.

A newly-developed platform, the Illumina TruSeq Methyl Capture EPIC library prep (TruSeq EPIC), builds on the content of the Infinium MethylationEPIC Beadchip Microarray (EPIC-array) and leverages the power of next-generation sequencing for targeted bisulphite sequencing. We empirically examined the performance of TruSeq EPIC and EPIC-array in assessing genome-wide DNA methylation in breast tissue samples. TruSeq EPIC provided data with a much higher density in the regions when compared to EPIC-array (~2.74 million CpGs with at least 10X coverage vs ~752 K CpGs, respectively). Approximately 398 K CpGs were common and measured across the two platforms in every sample. Overall, there was high concordance in methylation levels between the two platforms (Pearson correlation r = 0.98, P < 0.0001). However, we observed that TruSeq EPIC measurements provided a wider dynamic range and likely a higher quantitative sensitivity for CpGs that were either hypo- or hyper-methylated (ß close to 0 or 1, respectively). In addition, when comparing different breast tissue types TruSeq EPIC identified more differentially methylated CpGs than EPIC-array, not only out of additional sites interrogated by TruSeq EPIC alone, but also out of common sites interrogated by both platforms. Our results suggest that both platforms show high reproducibility and reliability in genome-wide DNA methylation profiling, while TruSeq EPIC had a significant improvement over EPIC-array regarding genomic resolution and coverage. The wider dynamic range and likely higher precision of the estimates by the TruSeq EPIC may lead to the identification of novel differentially methylated markers that are associated with disease risk.

Estimating breast tissue-specific DNA methylation age using next-generation sequencing data.

BACKGROUND: DNA methylation (DNAm) age has been widely accepted as an epigenetic biomarker for biological aging. Emerging evidence suggests that DNAm age can be tissue-specific and female breast tissue ages faster than other parts of the body. The Horvath clock, which estimates DNAm age across multiple tissues, has been shown to be poorly calibrated in breast issue. We aim to develop a model to estimate breast tissue-specific DNAm age. METHODS: Genome-wide DNA methylation sequencing data were generated for 459 normal, 107 tumor, and 45 paired adjacent-normal breast tissue samples. We determined a novel set of 286 breast tissue-specific clock CpGs using penalized linear regression and developed a model to estimate breast tissue-specific DNAm age. The model was applied to estimate breast tissue-specific DNAm age in different breast tissue types and in tumors with distinct clinical characteristics to investigate cancer-related aging effects. RESULTS: Our estimated breast tissue-specific DNAm age was highly correlated with chronological age (r = 0.88; p = 2.9 × 10-31) in normal breast tissue. Breast tumor tissue samples exhibited a positive epigenetic age acceleration, where DNAm age was on average 7 years older than respective chronological age (p = 1.8 × 10-8). In age-matched analyses, tumor breast tissue appeared 12 and 13 years older in DNAm age than adjacent-normal and normal breast tissue (p = 4.0 × 10-6 and 1.0 × 10-6, respectively). Both HER2+ and hormone-receptor positive subtypes demonstrated significant acceleration in DNAm ages (p = 0.04 and 3.8 × 10-6, respectively), while no apparent DNAm age acceleration was observed for triple-negative breast tumors. We observed a non-linear pattern of epigenetic age acceleration with breast tumor grade. In addition, early-staged tumors showed a positive epigenetic age acceleration (p = 0.003) while late-staged tumors exhibited a non-significant negative epigenetic age acceleration (p = 0.10). CONCLUSIONS: The intended applications for this model are wide-spread and have been shown to provide biologically meaningful results for cancer-related aging effects in breast tumor tissue. Future studies are warranted to explore whether breast tissue-specific epigenetic age acceleration is predictive of breast cancer development, treatment response, and survival as well as the clinical utility of whether this model can be extended to blood samples.

Practical Guides for X-Ray Photoelectron Spectroscopy (XPS): First Steps in planning, conducting and reporting XPS measurements.

Over the past three decades, the widespread utility and applicability of X-ray photoelectron spectroscopy (XPS) in research and applications has made it the most popular and widely used method of surface analysis. Associated with this increased use has been an increase in the number of new or inexperienced users which has led to erroneous uses and misapplications of the method. This article is the first in a series of guides assembled by a committee of experienced XPS practitioners that are intended to assist inexperienced users by providing information about good practices in the use of XPS. This first guide outlines steps appropriate for determining whether XPS is capable of obtaining the desired information, identifies issues relevant to planning, conducting and reporting an XPS measurement, and identifies sources of practical information for conducting XPS measurements. Many of the topics and questions addressed in this article also apply to other surface-analysis techniques.

Building of EMR Tools to Support Quality and Research in a Memory Disorders Clinic.

The electronic medical record (EMR) presents an opportunity to standardize patient data collection based on quality guidelines and conduct practice-based research. We describe the development of a customized EMR "toolkit" that standardizes patient data collection with hundreds of discrete fields that supports Best Practices for treating patients with memory disorders. The toolkit also supports practice-based research. We describe the design and successful implementation of a customized EMR toolkit to support Best Practices in the care of patients with memory disorders. We discuss applications, including quality improvement projects and current research initiatives, using the toolkit. This toolkit is being shared with other departments of Neurology as part of the Neurology Practice-Based Research Network. Data collection is ongoing, including longitudinal follow-up. This toolkit will generate data that will allow for descriptive and hypothesis driven research as well-quality improvement among patients seen in a memory clinic.

Design and implementation of pragmatic clinical trials using the electronic medical record and an adaptive design.

OBJECTIVES: To demonstrate the feasibility of pragmatic clinical trials comparing the effectiveness of treatments using the electronic medical record (EMR) and an adaptive assignment design. METHODS: We have designed and are implementing pragmatic trials at the point-of-care using custom-designed structured clinical documentation support and clinical decision support tools within our physician's typical EMR workflow. We are applying a subgroup based adaptive design (SUBA) that enriches treatment assignments based on baseline characteristics and prior outcomes. SUBA uses information from a randomization phase (phase 1, equal randomization, 120 patients), to adaptively assign treatments to the remaining participants (at least 300 additional patients total) based on a Bayesian hierarchical model. Enrollment in phase 1 is underway in our neurology clinical practices for 2 separate trials using this method, for migraine and mild cognitive impairment (MCI). RESULTS: We are successfully collecting structured data, in the context of the providers' clinical workflow, necessary to conduct our trials. We are currently enrolling patients in 2 point-of-care trials of non-inferior treatments. As of March 1, 2018, we have enrolled 36% of eligible patients into our migraine study and 63% of eligible patients into our MCI study. Enrollment is ongoing and validation of outcomes has begun. DISCUSSION: This proof of concept article demonstrates the feasibility of conducting pragmatic trials using the EMR and an adaptive design. CONCLUSION: The demonstration of successful pragmatic clinical trials based on a customized EMR and adaptive design is an important next step in achieving personalized medicine and provides a framework for future studies of comparative effectiveness.

Cholesteatoma Pearls: Practical Points and Update.

The European Academy of Otology and Neurotology in collaboration with the Japanese Otological Society (EAONO/JOS) recently produced a joint consensus document outlining the definitions, classification and staging of middle ear cholesteatoma. The goals were to provide terminologies in the description of cholesteatoma, classify cholesteatoma into distinct categories to facilitate the comparison of surgical outcomes and to provide a staging system that reflects the severity, difficulty of complete removal and restoration of normal function. Cholesteatoma is considered a benign, expanding and destructive epithelial lesion of the temporal bone that is the result of a multifactorial process. If undetected and left treated, cholesteatoma may lead to significant complications including hearing loss, temporal bone destruction and cranial invasion. Recent advances in imaging modalities have allowed for high sensitivity and specificity in identifying the presence of cholesteatoma. Despite these advances, deficiencies exist around the world with access to health care facilities meaning cholesteatoma remains a serious and challenging entity to manage whether found within the pediatric or adult population. Proper diagnosis and management of each form of cholesteatoma is achieved by a thorough understanding of the etiology, classification, clinical presentation and histology, thereby facilitating prevention, early detection and appropriate treatment.

In Situ Electrochemical-AFM and Cluster-Ion-Profiled XPS Characterization of an Insulating Polymeric Membrane as a Substrate for Immobilizing Biomolecules.

The electrochemical oxidation of ortho-aminophenol (oAP) by cyclic voltammetry (CV), on platinum substrates in neutral solution, produces a polymeric film (PoAP) that grows to a limiting thickness of about 10 nm. The insulating film has potential use as a bioimmobilizing substrate, with its specificity depending on the orientation of its molecular chains. Prior investigations suggest that the film consists of alternating quinoneimine and oAP units, progressively filling all the platinum sites during the electrosynthesis. This work concerns the evaluation of the growth orientation of PoAP chains, which until now was deduced only from indirect evidence. Atomic force microscopy (AFM) has been used in situ with an electrochemical cell so that PoAP deposition on a specific area can be observed, thus avoiding any surface reorganization during ex situ transport. In parallel with microscopy, XPS experiments have been performed using cluster ion beams to profile this film, which is exceptionally thin, without damage while retaining molecular information.

A risk-based approach for identifying constituents of concern in oil sands process-affected water from the Athabasca Oil Sands region.

Mining leases in the Athabasca Oil Sands (AOS) region produce large volumes of oil sands process-affected water (OSPW) containing constituents that limit beneficial uses and discharge into receiving systems. The aim of this research is to identify constituents of concern (COCs) in OSPW sourced from an active settling basin with the goal of providing a sound rational for developing mitigation strategies for using constructed treatment wetlands for COCs contained in OSPW. COCs were identified through several lines of evidence: 1) chemical and physical characterization of OSPW and comparisons with numeric water quality guidelines and toxicity endpoints, 2) measuring toxicity of OSPW using a taxonomic range of sentinel organisms (i.e. fish, aquatic invertebrates, and a macrophyte), 3) conducting process-based manipulations (PBMs) of OSPW to alter toxicity and inform treatment processes, and 4) discerning potential treatment pathways to mitigate ecological risks of OSPW based on identification of COCs, toxicological analyses, and PBM results. COCs identified in OSPW included organics (naphthenic acids [NAs], oil and grease [O/G]), metals/metalloids, and suspended solids. In terms of species sensitivities to undiluted OSPW, fish ≥ aquatic invertebrates > macrophytes. Bench-scale manipulations of the organic fractions of OSPW via PBMs (i.e. H2O2+UV254 and granular activated charcoal treatments) eliminated toxicity to Ceriodaphnia dubia (7-8 d), in terms of mortality and reproduction. Results from this study provide critical information to inform mitigation strategies using passive or semi-passive treatment processes (e.g., constructed treatment wetlands) to mitigate ecological risks of OSPW to aquatic organisms.

Effects of environmental conditions on aerobic degradation of a commercial naphthenic acid.

Naphthenic acids (NAs) are problematic constituents in energy-derived waters, and aerobic degradation may provide a strategy for mitigating risks to aquatic organisms. The overall objective of this study was to determine the influence of concentrations of N (as ammonia) and P (as phosphate), and DO, as well as pH and temperatures on degradation of a commercial NA in bench-scale reactors. Commercial NAs provided replicable compounds necessary to compare influences of environmental conditions on degradation. NAs were quantified using high performance liquid chromatography. Microbial diversity and relative abundance were measured in treatments as explanatory parameters for potential effects of environmental conditions on microbial populations to support analytically measured NA degradation. Environmental conditions that positively influenced degradation rates of Fluka NAs included nutrients (C:N 10:1-500:1, C:P 100:1-5000:1), DO (4.76-8.43 mg L(-1)), pH (6-8), and temperature (5-25 °C). Approximately 50% removal of 61 ± 8 mg L(-1) was achieved in less than 2 d after NA introduction, achieving the method detection limit (5 mg L(-1)) by day 6 of the experiment in treatments with a C:N:P ratio of 100:10:1, DO > 8 mg L(-1), pH ∼8-9, and temperatures >23 °C. Microbial diversity was lowest in lower temperature treatments (6-16 °C), which may have resulted in observed slower NA degradation. Based on results from this study, when macro- and micronutrients were available, DO, pH, and temperature (within environmentally relevant ranges) influenced rates of aerobic degradation of Fluka NAs. This study could serve as a model for systematically evaluating environmental factors that influence NA degradation in field scenarios.

Malignant Vagal Paraganglioma.

Paragangliomas are rare, typically benign neuroendocrine tumors that represent a small portion of head and neck tumors. A small percentage of these are known to have malignant potential. They arise from the carotid body, jugular bulb or vagus nerves. There is limited literature discussing the management of malignant vagal paragangliomas. We present a case of a 25 year old female with a left malignant vagal paraganglioma. The following case presentation will describe the presentation, classic radiologic findings, and management of a malignant vagal paraganglioma along with a review of the literature.

Effects of simulated oilfield produced water on early seedling growth after treatment in a pilot-scale constructed wetland system.

Seed germination and early seedling growth bioassays were used to evaluate phytotoxicity of simulated oilfield produced water (OPW) before and after treatment in a subsurface-flow, pilot-scale constructed wetland treatment system (CWTS). Responses to untreated and treated OPW were compared among seven plant species, including three monocotyledons: corn (Zea mays), millet (Panicum miliaceum), and sorghum (Sorghum bicolor); and four dicotyledons: lettuce (Lactuca sativa), okra (Abelmoschus esculents), watermelon (Citrullus lanatus), and soybean (Glycine max). Phytotoxicity was greater in untreated OPW than in treated OPW. Exposures to untreated and treated OPW enhanced growth in some plant species (sorghum, millet, okra, and corn) relative to a negative control and reduced growth in other plant species (lettuce, soybean, and watermelon). Early seedling growth parameters indicated that dicotyledons were more sensitive to test waters compared to monocotyledons, suggesting that morphological differences between plant species affected phytotoxicity. Results indicated the following sensitivity scale for plant species: lettuce>soybean>watermelon>corn>okra≈millet>sorghum. Phytotoxicity of the treated OPW to lettuce and soybean, although concentrations of COCs were less than irrigation guideline concentrations, suggests that chemical characterization and comparison to guideline concentrations alone may not be sufficient to evaluate water for use in growing crops.