Evidence map›Paper›PMID 42427845›Full record

ArticleResearch square2026

Microsaccade Dynamics Enhance Nodule Detection and Discriminate Reader Expertise Levels During Chest Radiography.

Robert G Alexander, Stephen Waite, Shawn Lyo, Ashwin Venkatakrishnan, Arcadij Grigorian, Riley Morrone, Samuel Sabzanov, Shamsul Alam, Ellis Gayles, Stephen L Macknik and 1 more

Abstract readPreprint
In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Robert G AlexanderDepartment of Psychology & Counseling, New York Institute of Technology, USA.
Stephen WaiteDepartment of Radiology, SUNY Downstate Health Sciences University, USA.
Shawn LyoDepartment of Radiology, SUNY Downstate Health Sciences University, USA.
Ashwin VenkatakrishnanDepartment of Ophthalmology, SUNY Downstate Health Sciences University, USA.
Arcadij GrigorianDepartment of Radiology, SUNY Downstate Health Sciences University, USA.
Riley MorroneDepartment of Ophthalmology, SUNY Downstate Health Sciences University, USA.
Samuel SabzanovDepartment of Radiology, SUNY Downstate Health Sciences University, USA.
Shamsul AlamDepartment of Radiology, SUNY Downstate Health Sciences University, USA.
Ellis GaylesExpertize, Inc., USA.
Stephen L MacknikDepartment of Ophthalmology, SUNY Downstate Health Sciences University, USA.
Susana Martinez-CondeDepartment of Ophthalmology, SUNY Downstate Health Sciences University, USA.ORCID 0000-0003-4600-9767

Funding

Novel Perceptual and Oculomotor Heuristics for Enhancing Radiologic PerformanceR01CA258021 · NCI · SUNY DOWNSTATE MEDICAL CENTER · PI MACKNIK, STEPHEN LOUIS, MARTINEZ-CONDE, SUSANA · 2021 to 2025
$2.9M
Visual cortical mechanisms for the perception of self-generated vs. external motionR01EY031971 · NEI · SUNY DOWNSTATE MEDICAL CENTER · PI Stephen Louis Macknik, Susana Martinez-Conde · 2020 to 2026
$2.2M
The Effects of Cue Precision on Medical Imaging InterpretationR16GM159810 · NIGMS · NEW YORK INST OF TECHNOLOGY · PI Robert G Alexander · 2025 to 2026
$284k
NCI NIH HHS R01 CA258021NEI NIH HHS R01 EY031971NIGMS NIH HHS R16 GM159810
6 · The paper itself

Abstract

Background: Perceptual misses are a major source of diagnostic error in radiology, yet no physiological biomarker currently exists for expertise in chest radiograph interpretation. Purpose: To determine whether microsaccade dynamics enhance pulmonary nodule detection and discriminate reader expertise levels during chest radiography. Materials and Methods: In this experimental eye-tracking study, 26 adults (nine naive observers, 11 radiology residents, and six attending radiologists) searched for nodules in 148 chest radiographs from the Japanese Society of Radiological Technology database. Eye movements were recorded during image interpretation. Readers were analyzed by both training level and performance-based accuracy groups. Microsaccade dynamics were compared inside versus outside the nodule region and on correct versus incorrect trials. Receiver operating characteristic analyses were used to test whether oculomotor variables discriminated lower- from higher-accuracy readers. Results: On correct trials, across expertise levels, readers generated more microsaccades per fixation when viewing nodules than when viewing other image regions. This relationship was absent on incorrect trials, linking microsaccade production to successful abnormality detection. The effect remained after matching fixation durations inside and outside the target region, indicating that it was not explained solely by longer fixation times. Higher-accuracy readers also showed a greater prevalence of fixations containing microsaccades within the target region on correct trials. Receiver operating characteristic analyses identified a microsaccade-based oculomotor signature that differentiated lower- from higher-accuracy readers, including microsaccade rate within the target region on correct trials. Conclusion: Microsaccade dynamics enhance pulmonary nodule detection during chest radiography and provide, to our knowledge, the first microsaccade-based, largely non-volitional physiological biomarker of expertise in chest radiograph interpretation.

Indexed as

cancerdecision-making errorsfixational eye movementslung nodule detectionmedical image perceptionmicrosaccadesperceptual errorperceptual expertise in radiologyrecognition errorssaccadesvisual search

Identifiers

PMID42427845
PMCPMC13345524

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.