Investigation of the clinical inter-observer bias in prostate fiducial marker image registration between CT and MR images

Background and purpose Inter-modality image registration between computed tomography (CT) and magnetic resonance (MR) images is associated with systematic uncertainties and the magnitude of these uncertainties is not well documented. The purpose of this study was to investigate the potential uncertainty of gold fiducial marker (GFM) registration for localized prostate cancer and to estimate the inter-observer bias in a clinical setting. Methods Four experienced observers registered CT and MR images for 42 prostate cancer patients. Manual GFM identification was followed by a landmark-based registration. The absolute difference between observers in GFM identification and the displacement of the clinical target volume (CTV) was investigated. The CTV center of mass (CoM) vector displacements, DICE-index and Hausdorff distances for the observer registrations were compared against a clinical baseline registration. The time allocated for the manual registrations was compared. Results Absolute difference in GFM identification between observers ranged from 0.0 to 3.0 mm. The maximum CTV CoM displacement from the clinical baseline was 3.1 mm. Displacements larger than or equal to 1 mm, 2 mm and 3 mm were 46%, 18% and 4%, respectively. No statistically significant difference was detected between observers in terms of CTV displacement. Median DICE-index and Hausdorff distance for the CTV, with their respective ranges were 0.94 [0.70–1.00] and 2.5 mm [0.7–8.7]. Conclusions Registration of CT and MR images using GFMs for localized prostate cancer patients was subject to inter-observer bias on an individual patient level. A CTV displacement as large as 3 mm occurred for individual patients. These results show that GFM registration in a clinical setting is associated with uncertainties, which motivates the removal of inter-modality registrations in the radiotherapy workflow and a transition to an MRI-only workflow for localized prostate cancer.

Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics

The methods of geometric morphometrics are commonly used to quantify morphology in a broad range of biological sciences. The application of these methods to large datasets is constrained by manual landmark placement limiting the number of landmarks and introducing observer bias. To move the field forward, we need to automate morphological phenotyping in ways that capture comprehensive representations of morphological variation with minimal observer bias. Here, we present Morphological Variation Quantifier (morphVQ), a shape analysis pipeline for quantifying, analyzing, and exploring shape variation in the functional domain. morphVQ uses descriptor learning to estimate the functional correspondence between whole triangular meshes in lieu of landmark configurations. With functional maps between pairs of specimens in a dataset we can analyze and explore shape variation. morphVQ uses Consistent ZoomOut refinement to improve these functional maps and produce a new representation of shape variation, area-based and conformal (angular) latent shape space differences (LSSDs). We compare this new representation of shape variation to shape variables obtained via manual digitization and auto3DGM, an existing approach to automated morphological phenotyping. We find that LSSDs compare favorably to modern 3DGM and auto3DGM while being more computationally efficient. By characterizing whole surfaces, our method incorporates more morphological detail in shape analysis. We can classify known biological groupings, such as Genus affiliation with comparable accuracy. The shape spaces produced by our method are similar to those produced by modern 3DGM and to auto3DGM, and distinctiveness functions derived from LSSDs show us how shape variation differs between groups. morphVQ can capture shape in an automated fashion while avoiding the limitations of manually digitized landmarks, and thus represents a novel and computationally efficient addition to the geometric morphometrics toolkit.

Initial Cluster of Novel Coronavirus (2019-nCoV) Infections in Wuhan, China Is Consistent with Substantial Human-to-Human Transmission

Reanalysis of the epidemic curve from the initial cluster of cases with novel coronavirus (2019-nCoV) in December 2019 indicates substantial human-to-human transmission. It is possible that the common exposure history at a seafood market in Wuhan originated from the human-to-human transmission events within the market, and the early, strong emphasis that market exposure indicated animal-to-human transmission was potentially the result of observer bias. To support the hypothesis of zoonotic origin of 2019-nCoV stemming from the Huanan seafood market, the index case should have had exposure history related to the market and the virus should have been identified from animals sold at the market. As these requirements remain unmet, zoonotic spillover at the market must not be overemphasized.

Perception of Entrepreneurial Ecosystem: Testing the Actor–Observer Bias

Entrepreneurial ecosystem is the interacting socio-economic environment that facilitates entrepreneurs to start and develop their enterprises. A vibrant and supportive entrepreneurial ecosystem is necessary for the start-up and growth of an enterprise. The entrepreneurial action would largely depend on the perception of entrepreneurs about the ecosystem. In this context, a study was designed to understand the perceptions of actors (entrepreneurs) and observers (non-entrepreneurs) on various components of the entrepreneurial ecosystem. Data for this study were collected from 296 entrepreneurs and 315 non-entrepreneurs from India, who responded to a 77-item questionnaire by giving their ratings of various aspects of the ecosystem on a 5-point scale. Findings of the study showed that perceptions of the entrepreneurial ecosystem were significantly different for most of the subgroups. Most notable among these differences was those between entrepreneurs and non-entrepreneurs, where the mean scores on all dimensions were found to be significantly higher for non-entrepreneurs than for entrepreneurs except for entrepreneurial capability which was found to be higher for entrepreneurs. Hence, the hypothesis of actor–observer bias in the perceptions of entrepreneurs and non-entrepreneurs is supported.

Volunteer Observer Bias and Sharp-Tailed Grouse Lek Counts in the Upper Midwest

For most species of prairie grouse Tympanuchus spp. standardized monitoring protocols do not exist across adjoining jurisdictions. For instance, researchers monitor relatively small and disjunct populations of prairie sharp-tailed grouse Tympanuchus phasisanellus campestris in Michigan, Wisconsin, and Minnesota using different lek count protocols. Some of these state-led monitoring efforts include the widespread use of volunteers who conduct lek counts without training. To facilitate discussions regarding standardizing sharp-tailed grouse lek count protocols in the Upper Midwest and elsewhere, we quantified the magnitude of differences in data arising from lek counts conducted by paired observers and examined factors potentially associated with observer bias (e.g., training type, use of optical equipment, experience). During 2010–2015, 44 unique pairs of formally trained volunteers in the Upper Peninsula of Michigan performed 93 counts at one lek while controlling for weather, distance to the lek, and the timing of observations. All counts consisted of six 1 min observations over 1 h. At three leks in northeastern Minnesota during 2015, nine pairs (consisting of an individual new to lek counts and a more experienced biologist) performed 21 lek counts using the same protocols, but without formal training for novice observers. Across all years and all sites, our results consistently indicated more agreement in data for dancing birds than nondancing birds. Overall, the mean ± SE difference between paired observers for total birds (dancing and nondancing combined) was 1.05 ± 0.09 in Michigan and 0.37 ± 0.08 in Minnesota. Generalized linear models indicated that the use of optical equipment and training type for dancing birds and training type for nondancing birds were significant factors that improved data agreement in Michigan. In Minnesota, models indicated that experience level (number of surveys performed) of the technician or volunteer did not affect count differences for dancing birds or nondancing birds. We contend that using behavior as a proxy for sex can bias lek count data for sharp-tailed grouse. We suggest lek count protocols in the Upper Midwest be simplified and standardized. Specifically, we suggest that observers report the total number of observed birds (regardless of behavior) and that protocols establish a set duration of observation. We also suggest that the use of optical equipment be required and that training be mandatory.