Evidence map›Paper›PMID 40485126›Full record

ArticleJournal of thoracic imaging2025

Computer-aided Nodule Detection in the Lung Apices in Head and Neck Computed Tomography Angiography: An Unexpected Opportunity.

Tamar Perel Kass, Jeffrey Chankowsky, Jacob Sosna, Benjamin Hyatt Taragin, Alla Khashper

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Article in Journal of thoracic imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Tamar Perel KassDepartment of Radiology, Shamir Medical Center, Beer Yakov.
Jeffrey ChankowskyDepartment of Radiology, Hadassah Medical Center, The Hebrew University of Jerusalem, Jerusalem, Israel.
Jacob SosnaDepartment of Radiology, Hadassah Medical Center, The Hebrew University of Jerusalem, Jerusalem, Israel.
Benjamin Hyatt TaraginDepartment of Radiology, Assuta Medical Center, Ashdod.
Alla KhashperDepartment of Radiology, Shamir Medical Center, Beer Yakov.ORCID 0000-0002-0737-1643

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeComputed tomography angiography (CTA) of the head and neck includes the pulmonary apices, a common location for pulmonary nodules. Computer-aided detection (CAD) is an adjunctive tool for the detection of lung nodules and is widely used in standard chest CT scans. We evaluated whether the available software can be applied to CTA head and neck examinations, which include the lung apices, resulting in improved accuracy for lung nodule detection. MATERIALS AND

methodsIn this retrospective single-center study, 191 previously reported head and neck CTA scans were re-evaluated for apical pulmonary nodules by 2 radiologists. Subsequently, CAD software ( Syngo .via, Siemens Healthiness AG) was applied to the lung apices and the results were compared between CAD and research radiologists (first reading) or clinical radiologist (null reading). In addition, the CAD performance in limited lung fields was compared with the accepted CAD assessment applied to whole lungs.

resultsOf the 191 patients, 110 (57.6%) were men, with a mean age of 68 years. In the 24 CT scans, the research radiologists detected 40 nodules. In the 180 scans evaluated by CAD, the software detected 39 nodules in 22 examinations, with a sensitivity of 60.8% and a PPV of 63.6%. In the remaining 158 examinations in which CAD did not detect nodules, the radiologists concurred in 149 scans, with a specificity of 94.9%, NPV of 94.3%, and accuracy of 90.6%.

conclusionThe study results indicate that CAD is an unexpected quick supportive tool for nodule detection, particularly for excluding clinically significant nodules in lung apices on CTA head and neck, showing similar results for partial and full lung fields.

Indexed as

Computed Tomography AngiographyDiagnosis, Computer-AssistedHead and Neck NeoplasmsLung NeoplasmsMultiple Pulmonary NodulesRadiographic Image Interpretation, Computer-AssistedSolitary Pulmonary NoduleAdultAgedAged, 80 and overFemaleHeadHumansLungMaleMiddle Agedcomputed tomography angiography head and neckcomputer-aided detectionlung apiceslung nodulespartial lung scan

Identifiers

PMID40485126
PMCPMC12369503

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