Recurrence quantification analysis of radiologists' scanpaths when interpreting mammograms. Issue 7 (16th May 2018)

• Record Type: Journal Article
• Authors: Gandomkar, Ziba; Tay, Kevin; Brennan, Patrick C.; Mello‐Thoms, Claudia
• Is Part Of: Medical physics. Volume 45:Issue 7(2018)
• Page Start: 3052
• Page End: 3062
• Publication Date: 2018-05-16
• Subjects: breast cancer -- eye movements -- mammogram -- recurrence quantification analysis -- scanpaths; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.12935
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: The purpose of this study was to Propose a classifier based on recurrence quantification analysis (RQA) metrics for distinguishing experts' scanpaths from those of less‐experienced readers and to explore the association of spatiotemporal dynamics of the mammographic scanpaths with the characteristics of cases and radiologists using RQA metrics. Materials and methods: Eye movements were recorded from eight radiologists (two cohorts: four experienced and four less‐experienced) while reading 120 mammograms (59 cancer, 61 normal). Ten RQA measures were extracted for each recorded scanpath. The measures described the temporal distribution of recurrent fixations as well as laminar and deterministic eye movements. Recurrent fixations are fixations that are located close to a previously fixated point in a scanpath. Deterministic eye movements represent looking back and forth between two locations, while laminar eye movements indicate detailed scanning of an area with consecutive fixations. The RQA metrics along with six conventional eye‐tracking parameters were used to construct a classifier for distinguishing experts' scanpaths from those of less‐experienced readers. Leave‐one‐out cross validation was used for evaluating the classifier. For each reader cohort, the ANOVA analysis was done to study the relationship of RQA measures with breast density, case pathology, readers' expertise, and readers' decisions on the case. The proportions of laminar and deterministic movements involved fixations in the location of lesions were also compared for two reader cohorts using two proportion z‐tests. Results: All RQA measures differed significantly between scanpaths of experienced readers and those of less‐experienced readers. The classifier achieved an area under the receiver operating characteristic curve of 0.89 (0.87–0.91) for detecting experts' scanpaths. Proportionately more refixations and laminar and deterministic sequences were in the location of the lesion for the experienced cohort compared to the less‐experienced cohort (all P ‐values < 0.001). Eight and four RQA measures differed between normal and cancer cases for the experienced and less experienced readers, respectively. None of metrics differed between fatty and dense breasts for the less experienced readers, while two measures resulted into a significant difference for the experienced readers. For experts, six measures differed significantly between true negatives and false positives and nine were significantly different between true positives and false negatives. For the less‐experienced cohort, the corresponding figures were seven and one measures, respectively. Conclusion: The RQA measures can quantify the differences among experienced and less experienced radiologists. They also capture differences among experts' scanpaths related to case pathology and radiologists' decisions on the case.