Temporal subtraction of computed tomography images improves detectability of bone metastases by radiology residents
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Temporal subtraction of CT (TS) images improves detection of newly developed bone metastases (BM). We sought to determine whether TS improves detection of BM by radiology residents as well.
We performed an observer study using a previously reported dataset, consisting of 60 oncology patients, each with previous and current CT images. TS images were calculated using in-house software. Four residents independently interpreted twice the 60 sets of CT images, without and with TS. They identified BM by marking suspicious lesions likely to be BM. Lesion-based sensitivity and number of false positives per patient were calculated. Figure-of-merit (FOM) was calculated. Detectability of BM, with and without TS, was compared between radiology residents and board-certified radiologists, as published previously.
FOM of residents significantly improved by implementing TS (p value < 0.0001). Lesion-based sensitivity, false positives per patients, and FOM were 40.8%, 0.121, and 0.657, respectively, without TS, and 58.1%, 0.0958, and 0.796, respectively, with TS. These findings were comparable with the previously published values for board-certified radiologists without TS (58.0%, 0.19, and 0.758, respectively).
The detectability of BM by residents improved markedly by implementing TS and reached that of board-certified radiologists without TS.
• Detectability of bone metastases on CT by residents improved significantly when using temporal subtraction of CT (TS).
• Detections by residents with TS and board-certified radiologists without TS were comparable.
• TS is useful for residents as it is for board-certified radiologists.
KeywordsTomography X-Ray computed Bone neoplasms Internship and residency
Abbreviations and acronyms
Newly developed bone metastases
Temporal subtraction of CT
The authors state that this work has not received any funding.
Compliance with ethical standards
The scientific guarantor of this publication is K. Togashi.
Conflict of interest
The authors of this manuscript declare relationships with the following companies: Canon Inc. K. Togashi has received research grants from Canon Inc.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was waived by the Institutional Review Board.
Institutional Review Board approval was obtained.
Study subjects or cohorts overlap
For 60 subjects in our study, there is overlap between our study and the previous study (ref. ). The purpose of our study (detectability of residents) is totally different from that of the previous study (detectability of board-certified radiologists).
• diagnostic or prognostic study
• performed at one institution
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