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Taillandier A, Avry F, Miquelestorena-Standley E, Samimi M, de la Fouchardière A, Macagno N, Kervarrec T. Impact of the adjunction of a short video to an original article for the recognition of newly described tumor entities in pathology: An interventional prospective study. J Cutan Pathol 2024. [PMID: 39014546 DOI: 10.1111/cup.14685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 06/24/2024] [Accepted: 07/01/2024] [Indexed: 07/18/2024]
Abstract
CONTEXT Merkel cell carcinoma diagnosis is often based on microscopic examination by pathologists. While histopathologic diagnosis primarily hinges on conscious and analytical cognition, the pathologist's decision-making process is also influenced by a rapid "gist" or "gestalt" approach. In this study, using cases of Merkel cell carcinoma as a model, we aim to assess how pathologists' viewing short videos containing conceptual clues and visual aids, in conjunction with reading an original article as a reference, may enhance their diagnostic performance. METHOD Sixteen pathologists were included in the present work. After participants had read the original article, their ability to distinguish Merkel cell polyomavirus (MCPyV)+ and MCPyV- Merkel cell carcinoma cases was evaluated on a first preliminary series of 20 cases. Following this test, the participants watched the video and then evaluated a second "experimental" series of 20 independent cases. RESULTS After reading the original article, for each case, a median number of 12 participants (75%, Q1-Q3: 10-13) classified the specimen in the correct category (92 incorrect answers in the whole series). An important interobserver variability was observed in this setting (Kappa coefficient = 0.465). By contrast, following the video, all cases were correctly classified by most of the participants, with only 12 incorrect answers on the whole series and excellent interobserver reproducibility (Kappa coefficient = 0.846). CONCLUSION Our study demonstrated that providing a short video together with an original article may enhance pathologists' performance in diagnosing Merkel cell carcinoma.
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Affiliation(s)
- Antoine Taillandier
- Department of Pathology, Université de Tours, Centre Hospitalier Universitaire de Tours, Chambray-les-tours, France
| | - François Avry
- Pharmacie à usage Intérieur, Université de Tours, Centre Hospitalier Universitaire de Tours, Chambray-les-tours, France
| | - Elodie Miquelestorena-Standley
- Department of Pathology, Université de Tours, Centre Hospitalier Universitaire de Tours, Chambray-les-tours, France
- «Transplantation, Immunologie, Inflammation», EA4145, Université de Tours, Tours, France
| | - Mahtab Samimi
- "Biologie des infections à polyomavirus" team, UMR INRA ISP 1282, Université de Tours, Tours, France
- Department of Dermatology, Université de Tours, Centre Hospitalier Universitaire de Tours, Chambray-les-tours, France
| | | | - Nicolas Macagno
- Department of Pathology, AP-HM, Timone University Hospital, Marseille, France
- Aix-Marseille University, INSERM U1251, MMG, Marseille, France
| | - Thibault Kervarrec
- Department of Pathology, Université de Tours, Centre Hospitalier Universitaire de Tours, Chambray-les-tours, France
- "Biologie des infections à polyomavirus" team, UMR INRA ISP 1282, Université de Tours, Tours, France
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Parthasarathy MK, Zuley ML, Bandos AI, Abbey CK, Webster MA. Visual adaptation to medical images: a comparison of digital mammography and tomosynthesis. J Med Imaging (Bellingham) 2023; 10:S11909. [PMID: 37114188 PMCID: PMC10128168 DOI: 10.1117/1.jmi.10.s1.s11909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 03/31/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Purpose Radiologists and other image readers spend prolonged periods inspecting medical images. The visual system can rapidly adapt or adjust sensitivity to the images that an observer is currently viewing, and previous studies have demonstrated that this can lead to pronounced changes in the perception of mammogram images. We compared these adaptation effects for images from different imaging modalities to explore both general and modality-specific consequences of adaptation in medical image perception. Approach We measured perceptual changes induced by adaptation to images acquired by digital mammography (DM) or digital breast tomosynthesis (DBT), which have both similar and distinct textural properties. Participants (nonradiologists) adapted to images from the same patient acquired from each modality or for different patients with American College of Radiology-Breast Imaging Reporting and Data System (BI-RADS) classification of dense or fatty tissue. The participants then judged the appearance of composite images formed by blending the two adapting images (i.e., DM versus DBT or dense versus fatty in each modality). Results Adaptation to either modality produced similar significant shifts in the perception of dense and fatty textures, reducing the salience of the adapted component in the test images. In side-by-side judgments, a modality-specific adaptation effect was not observed. However, when the images were directly fixated during adaptation and testing, so that the textural differences between the modalities were more visible, significantly different changes in the sensitivity to the noise in the images were observed. Conclusions These results confirm that observers can readily adapt to the visual properties or spatial textures of medical images in ways that can bias their perception of the images, and that adaptation can also be selective for the distinctive visual features of images acquired by different modalities.
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Affiliation(s)
| | - Margarita L. Zuley
- University of Pittsburgh, Department of Radiology, Pittsburgh, Pennsylvania, United States
| | - Andriy I. Bandos
- University of Pittsburgh, School of Public health, Pittsburgh, Pennsylvania, United States
| | - Craig K. Abbey
- University of California, Santa Barbara, Department of Psychological and Brain Sciences, Santa Barbara, California, United States
| | - Michael A. Webster
- University of Nevada, Reno, Department of Psychology, Reno, Nevada, United States
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Canas-Bajo T, Whitney D. Relative tuning of holistic face processing towards the fovea. Vision Res 2022; 197:108049. [PMID: 35461170 PMCID: PMC10101769 DOI: 10.1016/j.visres.2022.108049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 03/12/2022] [Accepted: 03/29/2022] [Indexed: 10/18/2022]
Abstract
Humans quickly detect and gaze at faces in the world, which reflects their importance in cognition and may lead to tuning of face recognition toward the central visual field. Although sometimes reported, foveal selectivity in face processing is debated: brain imaging studies have found evidence for a central field bias specific to faces, but behavioral studies have found little foveal selectivity in face recognition. These conflicting results are difficult to reconcile, but they could arise from stimulus-specific differences. Recent studies, for example, suggest that individual faces vary in the degree to which they require holistic processing. Holistic processing is the perception of faces as a whole rather than as a set of separate features. We hypothesized that the dissociation between behavioral and neuroimaging studies arises because of this stimulus-specific dependence on holistic processing. Specifically, the central bias found in neuroimaging studies may be specific to holistic processing. Here, we tested whether the eccentricity-dependence of face perception is determined by the degree to which faces require holistic processing. We first measured the holistic-ness of individual Mooney faces (two-tone shadow images readily perceived as faces). In a group of independent observers, we then used a gender discrimination task to measured recognition of these Mooney faces as a function of their eccentricity. Face gender was recognized across the visual field, even at substantial eccentricities, replicating prior work. Importantly, however, holistic face gender recognition was relatively tuned-slightly, but reliably stronger in the central visual field. Our results may reconcile the debate on the eccentricity-dependance of face perception and reveal a spatial inhomogeneity specifically in the holistic representations of faces.
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Affiliation(s)
- Teresa Canas-Bajo
- Vision Science Graduate Group, University of California, Berkeley, Berkeley, CA, USA.
| | - David Whitney
- Vision Science Graduate Group, University of California, Berkeley, Berkeley, CA, USA; Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
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Ren Z, Yu SX, Whitney D. Controllable Medical Image Generation via GAN. JOURNAL OF PERCEPTUAL IMAGING 2022; 5:0005021-50215. [PMID: 37621378 PMCID: PMC10448967 DOI: 10.2352/j.percept.imaging.2022.5.000502] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
Medical image data is critically important for a range of disciplines, including medical image perception research, clinician training programs, and computer vision algorithms, among many other applications. Authentic medical image data, unfortunately, is relatively scarce for many of these uses. Because of this, researchers often collect their own data in nearby hospitals, which limits the generalizabilty of the data and findings. Moreover, even when larger datasets become available, they are of limited use because of the necessary data processing procedures such as de-identification, labeling, and categorizing, which requires significant time and effort. Thus, in some applications, including behavioral experiments on medical image perception, researchers have used naive artificial medical images (e.g., shapes or textures that are not realistic). These artificial medical images are easy to generate and manipulate, but the lack of authenticity inevitably raises questions about the applicability of the research to clinical practice. Recently, with the great progress in Generative Adversarial Networks (GAN), authentic images can be generated with high quality. In this paper, we propose to use GAN to generate authentic medical images for medical imaging studies. We also adopt a controllable method to manipulate the generated image attributes such that these images can satisfy any arbitrary experimenter goals, tasks, or stimulus settings. We have tested the proposed method on various medical image modalities, including mammogram, MRI, CT, and skin cancer images. The generated authentic medical images verify the success of the proposed method. The model and generated images could be employed in any medical image perception research.
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Affiliation(s)
- Zhihang Ren
- Vision Science Graduate Group, University of California, Berkeley, CA 94720, United States of America
- International Computer Science Institute, Berkeley, CA 94720, United States of America
| | - Stella X Yu
- Vision Science Graduate Group, University of California, Berkeley, CA 94720, United States of America
- International Computer Science Institute, Berkeley, CA 94720, United States of America
| | - David Whitney
- Vision Science Graduate Group, University of California, Berkeley, CA 94720, United States of America
- International Computer Science Institute, Berkeley, CA 94720, United States of America
- Department of Psychology, University of California, Berkeley CA 94720, United States of America
- Helen Wills Neuroscience Institute, University of California, Berkeley CA 94720, United States of America
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