Using Virtual Telepathology Technology to Train Pathology Residents

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Using Virtual Telepathology to Train Pathology Residents

Elizabeth A. Krupinski, PhD Allison Tillack, MS Lynne Richter, MT Jeffrey Henderson, MD Achyut Bhattacharyya, MD Katherine Scott, MD Anna Graham, MD Michael Descour, PhD John Davis, MD Ronald S. Weinstein, MD



Arizona Telemedicine Program University of Arizona



Rationale

• Little research in pathology on the nature & development of expertise • Much known in radiology from eyeposition studies with significant differences between novices & experts • Differences similar in pathology? • Can we utilize differences to develop training programs to foster expertise?



Virtual Slides

• Dmetrix virtual slide processor •Three 80-element 10 x 8 lenslet arrays stacked vertically with 80 each side • Each has 250 micron FOV • Scans @ 3 mm/sec yields 3000 images/sec/array • 58 sec for 2.25 cm2 section • 40X objective detail •1 image = 200 MB – 1 GB storage space



Eye-Position Study

• • • • 20 virtual slides (breast biopsy) IBM 9-MegaPixel color display Initial resolution only 9 observers

– 3 pathologists – 3 pathology residents – 3 medical students



• ASL 4000SU Eye Tracker • Pick 3 areas most want to zoom on



Marked Zoom Areas



Marked Zoom Areas



Eye-Tracking



Eye-Tracking Data



Cluster



Saccade



Fixation (size = dwell)



Med Student Resident Pathologist



Viewing Time

Mean Total View Time (sec)

14 12 10 8 6 4 2 0 Path Res Med



F = 29.880, p < 0.0001 All differ significantly



Number Fixations

50 45 40 35 30 25 20 15 10 5 0 Path Res Med



F = 47.891, p < 0.0001 All differ significantly



Mean Number Fixations



# Saccades

50



Average Saccades Generated per Image



40 30 20 10 0 Path Res Experience Level Med



Benign



Malignant



F = 36.063, p < 0.0001 All differ significantly



Saccade Length

0.6



Saccade Length (sec)



0.5 0.4 0.3 0.2 0.1 0 Path Res Med



F = 54.761, p < 0.0001 All differ significantly



Saccade Distance

Saccade Length Deg Visual Angle



6 5 4 3 2 1 0 Path Res Med



F = 11.975, p < 0.0001 All differ significantly



Discussion

• Trained pathologists are more efficient at extracting information from virtual slides than less experienced residents or med students • Field of attention expands with expertise taking in more relevant information in the global percept or gist followed by directed focal search



Discussion

• Possibly use expert scan paths as examples for learners to accelerate the adoption of better search strategies • Possibly utilize expert scans to automatically change magnifications & field selections • Possibly use in self-assessment or proficiency testing scenarios



THANK YOU!




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