Tamar Perel Kass, Jeffrey Chankowsky, Jacob Sosna, Benjamin Hyatt Taragin, Alla Khashper
{"title":"头颈部计算机断层血管造影中肺尖的计算机辅助结节检测:一个意外的机会。","authors":"Tamar Perel Kass, Jeffrey Chankowsky, Jacob Sosna, Benjamin Hyatt Taragin, Alla Khashper","doi":"10.1097/RTI.0000000000000836","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Computed 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.</p><p><strong>Materials and methods: </strong>In 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.</p><p><strong>Results: </strong>Of 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%.</p><p><strong>Conclusion: </strong>The 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.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computer-aided Nodule Detection in the Lung Apices in Head and Neck Computed Tomography Angiography: An Unexpected Opportunity.\",\"authors\":\"Tamar Perel Kass, Jeffrey Chankowsky, Jacob Sosna, Benjamin Hyatt Taragin, Alla Khashper\",\"doi\":\"10.1097/RTI.0000000000000836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Computed 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.</p><p><strong>Materials and methods: </strong>In 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.</p><p><strong>Results: </strong>Of 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%.</p><p><strong>Conclusion: </strong>The 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.</p>\",\"PeriodicalId\":49974,\"journal\":{\"name\":\"Journal of Thoracic Imaging\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Thoracic Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/RTI.0000000000000836\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thoracic Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/RTI.0000000000000836","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Computer-aided Nodule Detection in the Lung Apices in Head and Neck Computed Tomography Angiography: An Unexpected Opportunity.
Purpose: Computed 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 methods: In 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.
Results: Of 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%.
Conclusion: The 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.
期刊介绍:
Journal of Thoracic Imaging (JTI) provides authoritative information on all aspects of the use of imaging techniques in the diagnosis of cardiac and pulmonary diseases. Original articles and analytical reviews published in this timely journal provide the very latest thinking of leading experts concerning the use of chest radiography, computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and all other promising imaging techniques in cardiopulmonary radiology.
Official Journal of the Society of Thoracic Radiology:
Japanese Society of Thoracic Radiology
Korean Society of Thoracic Radiology
European Society of Thoracic Imaging.