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Sogukpinar O, Akturk UA, Akbay MO, Tatlidil E, Ernam D. Diagnostic value of transthoracic needle biopsy in lung tumors. REVISTA DA ASSOCIACAO MEDICA BRASILEIRA (1992) 2024; 70:e20231082. [PMID: 38656001 DOI: 10.1590/1806-9282.20231082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 11/07/2023] [Indexed: 04/26/2024]
Abstract
OBJECTIVE Thoracic ultrasonography is widely used in imaging peripheral lesions and invasive interventional procedures. The aim of this study was to assess the diagnostic value of thoracic ultrasonography-guided transthoracic needle aspiration biopsy and the factors affecting the diagnosis of peripheral tumoral lung lesions. METHODS The lesion size, biopsy needle type, number of blocks, complications, and pathology results were compared in 83 patients between January 2015 and July 2018. The cases with pathological non-diagnosis and definite pathological diagnosis were determined. For the assessment of the factors affecting diagnosis, the size of the lesions and the biopsy needle type were evaluated. Biopsy preparations containing non-diagnostic atypical cells were referred to a cytopathologist. The effect of the cytopathological examination on the diagnosis was also evaluated. RESULTS Pathological diagnosis was made in 66.3% of the cases; cell type could not be determined in 22.9% of the cases, and they were referred to a cytopathologist. After the cytopathologist's examination, the diagnosis rate increased to 80.7%. Diagnosis rates were higher when using tru-cut than Chiba and higher in cases with tumor size >2 cm than smaller. CONCLUSION Thoracic ultrasonography-guided transthoracic needle aspiration biopsy is a preferred approach to the diagnosis of peripheral tumoral lung lesions, given its high diagnostic rate, in addition to being cheap, highly suitable for bedside use, and safe, and the lack of radiation exposure.
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Affiliation(s)
- Ozlem Sogukpinar
- University of Health Sciences, Sureyyapasa Chest Diseases and Thoracic Surgery Training and Research Hospital, Department of Chest Diseases - İstanbul, Turkey
| | - Ulku Aka Akturk
- University of Health Sciences, Sureyyapasa Chest Diseases and Thoracic Surgery Training and Research Hospital, Department of Chest Diseases - İstanbul, Turkey
| | - Makbule Ozlem Akbay
- University of Health Sciences, Sureyyapasa Chest Diseases and Thoracic Surgery Training and Research Hospital, Department of Chest Diseases - İstanbul, Turkey
| | - Erdal Tatlidil
- Denizli State Hospital, Department of Chest Diseases - Denizli, Turkey
| | - Dilek Ernam
- University of Health Sciences, Sureyyapasa Chest Diseases and Thoracic Surgery Training and Research Hospital, Department of Chest Diseases - İstanbul, Turkey
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Ferrando Blanco D, Persiva Morenza Ó, Cabanzo Campos LB, Sánchez Martínez AL, Varona Porres D, Del Carpio Bellido Vargas LA, Andreu Soriano J. Utility of artificial intelligence for detection of pneumothorax on chest radiopgraphs done after transthoracic percutaneous transthoracic biopsy guided by computed tomography. RADIOLOGIA 2024; 66 Suppl 1:S40-S46. [PMID: 38642960 DOI: 10.1016/j.rxeng.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/27/2023] [Indexed: 04/22/2024]
Abstract
OBJETIVE To assess the ability of an artificial intelligence software to detect pneumothorax in chest radiographs done after percutaneous transthoracic biopsy. MATERIAL AND METHODS We included retrospectively in our study adult patients who underwent CT-guided percutaneous transthoracic biopsies from lung, pleural or mediastinal lesions from June 2019 to June 2020, and who had a follow-up chest radiograph after the procedure. These chest radiographs were read to search the presence of pneumothorax independently by an expert thoracic radiologist and a radiodiagnosis resident, whose unified lecture was defined as the gold standard, and the result of each radiograph after interpretation by the artificial intelligence software was documented for posterior comparison with the gold standard. RESULTS A total of 284 chest radiographs were included in the study and the incidence of pneumothorax was 14.4%. There were no discrepancies between the two readers' interpretation of any of the postbiopsy chest radiographs. The artificial intelligence software was able to detect 41/41 of the present pneumothorax, implying a sensitivity of 100% and a negative predictive value of 100%, with a specificity of 79.4% and a positive predictive value of 45%. The accuracy was 82.4%, indicating that there is a high probability that an individual will be adequately classified by the software. It has also been documented that the presence of Port-a-cath is the cause of 8 of the 50 of false positives by the software. CONCLUSIONS The software has detected 100% of cases of pneumothorax in the postbiopsy chest radiographs. A potential use of this software could be as a prioritisation tool, allowing radiologists not to read immediately (or even not to read) chest radiographs classified as non-pathological by the software, with the confidence that there are no pathological cases.
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Affiliation(s)
- D Ferrando Blanco
- Servicio de Radiología, Hospital Universitari Vall d'Hebrón, Barcelona, Spain.
| | - Ó Persiva Morenza
- Servicio de Radiología, Hospital Universitari Vall d'Hebrón, Barcelona, Spain
| | - L B Cabanzo Campos
- Servicio de Radiología, Hospital Universitari Vall d'Hebrón, Barcelona, Spain
| | | | - D Varona Porres
- Servicio de Radiología, Hospital Universitari Vall d'Hebrón, Barcelona, Spain
| | | | - J Andreu Soriano
- Servicio de Radiología, Hospital Universitari Vall d'Hebrón, Barcelona, Spain
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Xu D, Xie F, Zhang J, Chen H, Chen Z, Guan Z, Hou G, Ji C, Li H, Li M, Li W, Li X, Li Y, Lian H, Liao J, Liu D, Luo Z, Ouyang H, Shen Y, Shi Y, Tang C, Wan N, Wang T, Wang H, Wang H, Wang J, Wu X, Xia Y, Xiao K, Xu W, Xu F, Yang H, Yang J, Ye T, Ye X, Yu P, Zhang N, Zhang P, Zhang Q, Zhao Q, Zheng X, Zou J, Chen E, Sun J. Chinese expert consensus on cone-beam CT-guided diagnosis, localization and treatment for pulmonary nodules. Thorac Cancer 2024; 15:582-597. [PMID: 38337087 PMCID: PMC10912555 DOI: 10.1111/1759-7714.15222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 01/07/2024] [Indexed: 02/12/2024] Open
Abstract
Cone-beam computed tomography (CBCT) system can provide real-time 3D images and fluoroscopy images of the region of interest during the operation. Some systems can even offer augmented fluoroscopy and puncture guidance. The use of CBCT for interventional pulmonary procedures has grown significantly in recent years, and numerous clinical studies have confirmed the technology's efficacy and safety in the diagnosis, localization, and treatment of pulmonary nodules. In order to optimize and standardize the technical specifications of CBCT and guide its application in clinical practice, the consensus statement has been organized and written in a collaborative effort by the Professional Committee on Interventional Pulmonology of China Association for Promotion of Health Science and Technology.
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Affiliation(s)
- Dongyang Xu
- Department of Respiratory Endoscopy, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Department of Respiratory and Critical Care Medicine, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai Engineering Research Center of Respiratory EndoscopyShanghaiChina
| | - Fangfang Xie
- Department of Respiratory Endoscopy, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Department of Respiratory and Critical Care Medicine, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai Engineering Research Center of Respiratory EndoscopyShanghaiChina
| | - Jisong Zhang
- Department of Pulmonary and Critical Care Medicine, Regional Medical Center for National Institute of Respiratory DiseaseSir Run Run Shaw Hospital of Zhejiang UniversityHangzhouChina
| | - Hong Chen
- Department of Pulmonary and Critical Care MedicineSecond Affiliated Hospital of Harbin Medical UniversityHarbinChina
| | - Zhongbo Chen
- Department of Pulmonary and Critical Care Medicine, The Affiliated Hospital of Medical SchoolNingbo UniversityNingboChina
| | - Zhenbiao Guan
- Department of Respiration, Changhai HospitalNaval Medical UniversityShanghaiChina
| | - Gang Hou
- Department of Pulmonary and Critical Care Medicine, China‐Japan Friendship HospitalBeijingChina
| | - Cheng Ji
- Department of Respiratory and Critical Care MedicineThe First Affiliated Hospital of Soochow UniversitySuzhouChina
| | - Haitao Li
- Department of Respiratory and Critical Care MedicineThe Second Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
| | - Manxiang Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Wei Li
- Department of Respiratory DiseaseThe First Affiliated Hospital of Bengbu Medical CollegeBengbuChina
| | - Xuan Li
- Department of Respiratory Medicine, Shanghai Tenth People's HospitalTongji University School of MedicineShanghaiChina
| | - Yishi Li
- Dept of Respiratory and Critical Care MedicineThe First Affiliated Hospital of Chongqing Medical UniversityChongqingChina
| | - Hairong Lian
- Department of Respiratory MedicineAffiliated Hospital of Jiangnan UniversityWuxiChina
| | - Jiangrong Liao
- Department of Respiratory MedicineGuizhou Aerospace HospitalZunyiChina
| | - Dan Liu
- Department of Respiratory and Critical Care MedicineWest China Hospital of Sichuan UniversityChengduChina
| | - Zhuang Luo
- Department of Respiratory and Critical Care MedicineFirst Affiliated Hospital of Kunming Medical UniversityKunmingChina
| | - Haifeng Ouyang
- Department of Respiratory DiseasesXi'an International Medical CenterXi'anChina
| | - Yongchun Shen
- Department of Respiratory and Critical Care MedicineWest China Hospital of Sichuan UniversityChengduChina
| | - Yiwei Shi
- Department of Respiratory and Critical Care MedicineShanxi Medical University Affiliated First HospitalTaiyuanChina
| | - Chunli Tang
- China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory DiseaseThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Nansheng Wan
- Department of Respiratory and Critical Care MedicineTianjin Medical University General HospitalTianjinChina
| | - Tao Wang
- Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Hong Wang
- Department of Respiratory MedicineLanzhou University Second HospitalLanzhouChina
| | - Huaqi Wang
- Department of Respiratory MedicineThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Juan Wang
- Department of Respiratory and Critical Care Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xuemei Wu
- Department of Respiratory CentreThe Second Affiliated Hospital of Xiamen Medical CollegeXiamenChina
| | - Yang Xia
- Department of Respiratory and Critical Care MedicineSecond Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Kui Xiao
- Department of Respiratory Medicine, The Second Xiangya HospitalCentral South UniversityChangshaChina
| | - Wujian Xu
- Department of Respiratory and Critical Care Medicine, Shanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Fei Xu
- Department of Respiratory and Critical Care MedicineThe First Affiliated Hospital of Nanchang UniversityNanchangChina
| | - Huizhen Yang
- Department of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, People's Hospital of Zhengzhou UniversityZhengzhouChina
| | - Junyong Yang
- Department of Respiratory MedicineXinjiang Chest HospitalWulumuqiChina
| | - Taosheng Ye
- Department of TuberculosisThe Third People's Hospital of ShenzhenShenzhenChina
| | - Xianwei Ye
- Department of Pulmonary and Critical Care MedicineGuizhou Provincial People's HospitalGuiyangChina
| | - Pengfei Yu
- Department of Respiratory and Critical Care Medicine, Yantai Yuhuangding HospitalAffiliated with the Medical College of QingdaoYantaiChina
| | - Nan Zhang
- Department of Respiratory Medicine, Emergency General HospitalBeijingChina
| | - Peng Zhang
- Pulmonary Intervention DepartmentAnhui Chest HospitalHefeiChina
| | - Quncheng Zhang
- Department of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, People's Hospital of Zhengzhou UniversityZhengzhouChina
| | - Qi Zhao
- Department of Respiratory Medicine, Nanjing Drum Tower HospitalNanjing University Medical SchoolNanjingChina
| | - Xiaoxuan Zheng
- Department of Respiratory Endoscopy, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Department of Respiratory and Critical Care Medicine, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai Engineering Research Center of Respiratory EndoscopyShanghaiChina
| | - Jun Zou
- Department of Respiratory and Critical Care Medicine, Sichuan Provincial People's HospitalUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Enguo Chen
- Department of Pulmonary and Critical Care Medicine, Regional Medical Center for National Institute of Respiratory DiseaseSir Run Run Shaw Hospital of Zhejiang UniversityHangzhouChina
| | - Jiayuan Sun
- Department of Respiratory Endoscopy, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Department of Respiratory and Critical Care Medicine, Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai Engineering Research Center of Respiratory EndoscopyShanghaiChina
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Li J, Su L, Liu J, Peng Q, Xu R, Cui W, Deng Y, Xie W, Huang B, Chen J. Optical navigation robot-assisted puncture system for accurate lung nodule biopsy: an animal study. Quant Imaging Med Surg 2023; 13:7789-7801. [PMID: 38106300 PMCID: PMC10722077 DOI: 10.21037/qims-23-576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 09/06/2023] [Indexed: 12/19/2023]
Abstract
Background As lung cancer is one of the most significant factors seriously endangering human health, a robot-assisted puncture system with high accuracy and safety is urgently needed. The purpose of this investigation was to compare the safety and effectiveness of such a robot-assisted system to the conventional computed tomography (CT)-guided manual method for percutaneous lung biopsies (PLBs) in pigs. Methods An optical navigation robot-assisted puncture system was developed and compared to the traditional CT-guided PLB using simulated lesions in experimental animals. A total of 30 pulmonary nodules were successfully created in 5 pigs (Wuzhishan pig, 1 male and 4 females). Of these, 15 were punctured by the optical navigation robot-assisted puncture system (robotic group), and 15 were manually punctured under CT guidance (manual group). The biopsy success rate, operation time, first needle tip-target point deviation, and needle adjustment times were compared between groups. Postoperative CT scans were performed to identify complications. Results The single puncture success rate was higher in the robotic group (13/15; 86.7%) than in the manual group (8/15; 53.3%). The first puncture was closer to the target lesion (1.8±1.7 mm), and the operation time was shorter (7.1±3.7 minutes) in the robotic group than in the manual group (4.4±2.8 mm and 12.9±7.6 minutes, respectively). The angle deviation was smaller in the robotic group (3.26°±2.48°) than in the manual group (7.71°±3.86°). The robotic group displayed significant advantages (P<0.05). The primary complication in both groups was slight bleeding, with an incidence of 26.7% in the robotic group and 40.0% in the manual group. There was 1 case of pneumothorax in the manual group, and there were no deaths due to complications in either group. Conclusions An optical navigation robot-assisted system for PLBs guided by CT images was developed and demonstrated. The experimental results indicate that the proposed system is accurate, efficient, and safe in pigs.
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Affiliation(s)
- Jing Li
- Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
- Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Liyilei Su
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
| | - Jun Liu
- Wuerzburg Dynamics Inc., Shenzhen, China
| | - Qian Peng
- Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Rongde Xu
- Department of Interventional Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Wei Cui
- Department of Interventional Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yi Deng
- Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Weiguo Xie
- Wuerzburg Dynamics Inc., Shenzhen, China
| | - Bingding Huang
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
| | - Jingjing Chen
- Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
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Cheng K, Li L, Du Y, Wang J, Chen Z, Liu J, Zhang X, Dong L, Shen Y, Yang Z. A systematic review of image-guided, surgical robot-assisted percutaneous puncture: Challenges and benefits. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:8375-8399. [PMID: 37161203 DOI: 10.3934/mbe.2023367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Percutaneous puncture is a common medical procedure that involves accessing an internal organ or tissue through the skin. Image guidance and surgical robots have been increasingly used to assist with percutaneous procedures, but the challenges and benefits of these technologies have not been thoroughly explored. The aims of this systematic review are to furnish an overview of the challenges and benefits of image-guided, surgical robot-assisted percutaneous puncture and to provide evidence on this approach. We searched several electronic databases for studies on image-guided, surgical robot-assisted percutaneous punctures published between January 2018 and December 2022. The final analysis refers to 53 studies in total. The results of this review suggest that image guidance and surgical robots can improve the accuracy and precision of percutaneous procedures, decrease radiation exposure to patients and medical personnel and lower the risk of complications. However, there are many challenges related to the use of these technologies, such as the integration of the robot and operating room, immature robotic perception, and deviation of needle insertion. In conclusion, image-guided, surgical robot-assisted percutaneous puncture offers many potential benefits, but further research is needed to fully understand the challenges and optimize the utilization of these technologies in clinical practice.
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Affiliation(s)
- Kai Cheng
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Lixia Li
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Yanmin Du
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Jiangtao Wang
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Zhenghua Chen
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Jian Liu
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Xiangsheng Zhang
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Lin Dong
- Center on Frontiers of Computing Studies, Peking University, Beijing 100089, China
| | - Yuanyuan Shen
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
| | - Zhenlin Yang
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China
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Piacentino F, Fontana F, Zorzetto G, Saccomanno A, Casagrande S, Franzi F, Imperatori A, Lanza C, Carriero S, Coppola A, Ierardi AM, Carrafiello G, Venturini M. Could Maximum SUV be Used as Imaging Guidance in Large Lung Lesions Biopsies? Double Sampling Under PET-CT/XperGuide Fusion Imaging in Inhomogeneous Lung Uptaking Lesions to Show That it can Make a Difference. Technol Cancer Res Treat 2023; 22:15330338221144508. [PMID: 37116886 PMCID: PMC10155026 DOI: 10.1177/15330338221144508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2023] Open
Abstract
Introduction: The purpose of this study is to evaluate the diagnostic value of positron emission computed tomography-cone beam computed tomography (PET/CT-CBCT) fusion guided percutaneous biopsy, targeted to the maximum standardized uptake value (SUVmax) and minimum standardized uptake value (SUVmin) of large lung lesions. Materials and Methods: Inside a larger cohort of PET/CT-CBCT guided percutaneous lung biopsies, 10 patients with large pulmonary lesions (diameter > 30 mm) were selected retrospectively. These patients have been subjected to double biopsy sampling respectively in the SUVmax area and in the SUVmin area of the lesion. Technical success has been calculated. For each sample, the percentage of neoplastic, inflammatory, and fibrotic cells was reported. Furthermore, the possibility of performing immunohistochemical or molecular biology investigations to specifically define the biomolecular tumor profile was analyzed. Results: Nine lesions were found to be malignant, one benign (inflammation). Technical success was 100% (10/10) in the SUVmax samples and 70% (7/10) in the SUVmin samples (P-value: .21). In the first group, higher percentages of neoplastic cells were found at pathologic evaluation, while in the second group areas of inflammation and fibrosis were more represented. The biomolecular profile was obtained in 100% of cases (9/9) of the first group, while in the second group only in 33.3% of cases (2/6), with a statistically significant difference between the 2 groups (P-value: .011). Conclusion: A correlation between the standardized uptake value value and the technical success of the biopsy sample has been identified. PET/CT-CBCT guidance allows to target the biopsy in the areas of the tumor which are richer in neoplastic cells, thus obtaining more useful information for the planning of patient-tailored cancer treatments.
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Affiliation(s)
- Filippo Piacentino
- Department of Diagnostic and Interventional Radiology, Circolo Hospital and Macchi Foundation, Insubria University, Varese, Italy
| | - Federico Fontana
- Department of Diagnostic and Interventional Radiology, Circolo Hospital and Macchi Foundation, Insubria University, Varese, Italy
| | - Giada Zorzetto
- Postgraduate School of Radiodiagnostics, Insubria University, Varese, Italy
| | - Angiola Saccomanno
- Postgraduate School of Radiodiagnostics, Insubria University, Varese, Italy
| | - Sabrina Casagrande
- Nuclear Medicine Unit, Circolo Hospital and Macchi Foundation, Varese, Italy
| | - Francesca Franzi
- Division of Pathological Anatomy, Circolo Hospital and Macchi Foundation, Insubria University, Varese, Italy
| | - Andrea Imperatori
- Division of Thoracic Surgery, Circolo Hospital and Macchi Foundation, Insubria University, Varese, Italy
| | - Carolina Lanza
- Postgraduate School of Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Serena Carriero
- Postgraduate School of Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Andrea Coppola
- Department of Diagnostic and Interventional Radiology, Circolo Hospital and Macchi Foundation, Insubria University, Varese, Italy
| | - Anna Maria Ierardi
- Interventional Radiology Unit, Department of Radiology, Foundation IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Gianpaolo Carrafiello
- Interventional Radiology Unit, Department of Radiology, Foundation IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimo Venturini
- Department of Diagnostic and Interventional Radiology, Circolo Hospital and Macchi Foundation, Insubria University, Varese, Italy
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Lovrenski A, Gardic N, Tegeltija D, Miljkovic D. Diagnostic accuracy and adequacy of peripheral pulmonary nodules samples obtained by transthoracic needle aspiration. Cytopathology 2023; 34:35-42. [PMID: 36062401 DOI: 10.1111/cyt.13176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/26/2022] [Accepted: 08/31/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To examine the adequacy of samples and accuracy of transthoracic needle aspiration (TTNA) in patients with peripheral pulmonary nodule (PPN) diagnosis. METHODS This retrospective study included 248 patients who underwent TTNA of PPN and subsequent diagnostic and therapeutic surgical procedures during a 5-year period at the Institute for Pulmonary Diseases of Vojvodina. The following were analysed: adequacy of cytological samples for diagnosis and molecular testing, tumour localisation and dimensions, and cytological and histopathological characteristics. RESULTS The adequacy of the cytological samples was 93.15%. The proportion of adequate-diagnostic samples was higher in patients in whom the largest diameter of the lesion was >4 cm, and this difference showed statistical significance. Tumour localisation was not statistically significant for the adequacy of samples for cytological analysis. Cytological samples of lung adenocarcinoma had high projected adequacy for EGFR analyses of 91.55%, not dependent on the size and location of the lesion. The most commonly diagnosed lung tumour was adenocarcinoma (45.51%). Patients with a cytological diagnosis of non-small cell carcinoma not otherwise specified, after histopathological analyses, had adenocarcinoma in most cases (53.85%). The overall accuracy of TTNA in the diagnosis of PPN was 71%. The method's accuracy was 75.24% for malignant tumours, while it was 28.57% for benign tumours. The accuracy of cytological analysis for the histological type of tumour was 84.18%. CONCLUSION Transthoracic needle aspiration with cytological analysis is an effective and highly sensitive method in determining the aetiology of PPN.
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Affiliation(s)
- Aleksandra Lovrenski
- Department of Pathology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia.,Deparment of Pathology and Molecular Diagnostics, Institute for Pulmonary Diseases of Vojvodina, Sremska Kamenica, Serbia
| | - Nikola Gardic
- Department of Pathology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia
| | - Dragana Tegeltija
- Department of Pathology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia.,Deparment of Pathology and Molecular Diagnostics, Institute for Pulmonary Diseases of Vojvodina, Sremska Kamenica, Serbia
| | - Dejan Miljkovic
- Department of Histology and Embryology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia
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8
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Ma G, Yang D, Li Y, Li M, Li J, Fu J, Peng Z. Combined measurement of circulating tumor cell counts and serum tumor marker levels enhances the screening efficiency for malignant versus benign pulmonary nodules. Thorac Cancer 2022; 13:3393-3401. [PMID: 36284506 PMCID: PMC9715841 DOI: 10.1111/1759-7714.14702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/03/2022] [Accepted: 10/06/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND The high false-positive rate for pulmonary nodules (PNs) from using low-dose computed tomography (LDCT) screening can lead to overuse of invasive procedures, overtreatment, and patient anxiety. Therefore, it is very important to develop new diagnostic methods. METHODS A negative enrichment-fluorescence in situ hybridization (NE-FISH) approach was used to detect circulating tumor cells (CTCs) in patients with PNs. We evaluated whether or not the combination of CTC counts with serum tumor marker levels (CEA, CA 125, CYFRA 21-1, SCC) could improve the diagnostic ability for distinguishing patients with malignant pulmonary nodules (MPNs) from those with benign pulmonary nodules (BPNs). Moreover, the potential clinical application of this combination for the diagnosis of solitary pulmonary nodules (SPNs) with a diameter ≤2 cm was also investigated. RESULTS The combination of CTC counts and tumor marker levels had a sensitivity of 80.12% and the area under the receiver operating characteristics curve (AUCROC ) of 0.853 (95% confidence interval [CI]: 0.800-0.897, p < 0.001) for the differential diagnosis of PNs. For early cancer stages, the sensitivity was 75.38% (AUCROC = 0.780, 95% CI: 0.713-0.838, p < 0.001). In addition, for SPNs within 2 cm the combination of CTC counts and tumor marker levels was still the most valuable diagnostic tool with a sensitivity of 78.95% and AUCROC of 0.888. CONCLUSION The combination of CTC counts and serum tumor marker levels is helpful for improving the diagnosis of PNs, especially in the early stages of cancer and for SPNs within 2 cm.
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Affiliation(s)
- Guojun Ma
- Department of Thoracic Surgery, Shandong Provincial Hospital, Cheeloo College of MedicineShandong UniversityJinanChina,Department of Thoracic SurgeryLiaocheng People's HospitalLiaochengChina
| | - Dawei Yang
- Zhong Yuan Academy of Biological MedicineLiaocheng People's HospitalLiaochengChina
| | - Yang Li
- Zhong Yuan Academy of Biological MedicineLiaocheng People's HospitalLiaochengChina
| | - Meng Li
- Department of Thoracic Surgery, Shandong Provincial Hospital, Cheeloo College of MedicineShandong UniversityJinanChina
| | - Jingtao Li
- Department of Thoracic SurgeryLiaocheng People's HospitalLiaochengChina
| | - Jianhua Fu
- Department of Thoracic SurgeryLiaocheng People's HospitalLiaochengChina
| | - Zhongmin Peng
- Department of Thoracic Surgery, Shandong Provincial Hospital, Cheeloo College of MedicineShandong UniversityJinanChina
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Huang W, Wang J, Wang H, Zhang Y, Zhao F, Li K, Su L, Kang F, Cao X. PET/CT Based EGFR Mutation Status Classification of NSCLC Using Deep Learning Features and Radiomics Features. Front Pharmacol 2022; 13:898529. [PMID: 35571081 PMCID: PMC9092283 DOI: 10.3389/fphar.2022.898529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 04/11/2022] [Indexed: 12/24/2022] Open
Abstract
Purpose: This study aimed to compare the performance of radiomics and deep learning in predicting EGFR mutation status in patients with lung cancer based on PET/CT images, and tried to explore a model with excellent prediction performance to accurately predict EGFR mutation status in patients with non-small cell lung cancer (NSCLC). Method: PET/CT images of 194 NSCLC patients from Xijing Hospital were collected and divided into a training set and a validation set according to the ratio of 7:3. Statistics were made on patients' clinical characteristics, and a large number of features were extracted based on their PET/CT images (4306 radiomics features and 2048 deep learning features per person) with the pyradiomics toolkit and 3D convolutional neural network. Then a radiomics model (RM), a deep learning model (DLM), and a hybrid model (HM) were established. The performance of the three models was compared by receiver operating characteristic (ROC) curves, sensitivity, specificity, accuracy, calibration curves, and decision curves. In addition, a nomogram based on a deep learning score (DS) and the most significant clinical characteristic was plotted. Result: In the training set composed of 138 patients (64 with EGFR mutation and 74 without EGFR mutation), the area under the ROC curve (AUC) of HM (0.91, 95% CI: 0.86-0.96) was higher than that of RM (0.82, 95% CI: 0.75-0.89) and DLM (0.90, 95% CI: 0.85-0.95). In the validation set composed of 57 patients (32 with EGFR mutation and 25 without EGFR mutation), the AUC of HM (0.85, 95% CI: 0.77-0.93) was also higher than that of RM (0.68, 95% CI: 0.52-0.84) and DLM (0.79, 95% CI: 0.67-0.91). In all, HM achieved better diagnostic performance in predicting EGFR mutation status in NSCLC patients than two other models. Conclusion: Our study showed that the deep learning model based on PET/CT images had better performance than radiomics model in diagnosing EGFR mutation status of NSCLC patients based on PET/CT images. Combined with the most statistically significant clinical characteristic (smoking) and deep learning features, our hybrid model had better performance in predicting EGFR mutation types of patients than two other models, which could enable NSCLC patients to choose more personalized treatment schemes.
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Affiliation(s)
- Weicheng Huang
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
| | - Jingyi Wang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Haolin Wang
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
| | - Yuxiang Zhang
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
| | - Fengjun Zhao
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
| | - Kang Li
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
| | - Linzhi Su
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
| | - Fei Kang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xin Cao
- School of Information Science and Technology, Northwest University, Xi'an, China.,National and Local Joint Engineering Research Center for Cultural Heritage Digitization, Xi'an, China
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10
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Ye X, Fan W, Wang Z, Wang J, Wang H, Wang J, Wang C, Niu L, Fang Y, Gu S, Tian H, Liu B, Zhong L, Zhuang Y, Chi J, Sun X, Yang N, Wei Z, Li X, Li X, Li Y, Li C, Li Y, Yang X, Yang W, Yang P, Yang Z, Xiao Y, Song X, Zhang K, Chen S, Chen W, Lin Z, Lin D, Meng Z, Zhao X, Hu K, Liu C, Liu C, Gu C, Xu D, Huang Y, Huang G, Peng Z, Dong L, Jiang L, Han Y, Zeng Q, Jin Y, Lei G, Zhai B, Li H, Pan J. [Expert Consensus for Thermal Ablation of Pulmonary Subsolid Nodules (2021 Edition)]. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2021; 24:305-322. [PMID: 33896152 PMCID: PMC8174112 DOI: 10.3779/j.issn.1009-3419.2021.101.14] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
局部热消融技术在肺部结节治疗领域正处在起步与发展阶段,为了肺结节热消融治疗的临床实践和规范发展,由“中国医师协会肿瘤消融治疗技术专家组”“中国医师协会介入医师分会肿瘤消融专业委员会”“中国抗癌协会肿瘤消融治疗专业委员会”“中国临床肿瘤学会消融专家委员会”组织多学科国内有关专家,讨论制定了“热消融治疗肺部亚实性结节专家共识(2021年版)”。主要内容包括:①肺部亚实性结节的临床评估;②热消融治疗肺部亚实性结节技术操作规程、适应证、禁忌证、疗效评价和相关并发症;③存在的问题和未来发展方向。
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Affiliation(s)
- Xin Ye
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Weijun Fan
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510050, China
| | - Zhongmin Wang
- Department of Interventional Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China
| | - Junjie Wang
- Department of Radiation Oncology, Peking University Third Hospital, Beijing 100191, China
| | - Hui Wang
- Interventional Center, Jilin Provincial Cancer Hospital, Changchun 170412, China
| | - Jun Wang
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Chuntang Wang
- Department of Thoracic Surgery, Dezhou Second People's Hospital, Dezhou 253022, China
| | - Lizhi Niu
- Department of Oncology, Affiliated Fuda Cancer Hospital, Jinan University, Guangzhou 510665, China
| | - Yong Fang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China
| | - Shanzhi Gu
- Department of Interventional Radiology, Hunan Cancer Hospital, Changsha 410013, China
| | - Hui Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Baodong Liu
- Department of Thoracic Surgery, Xuan Wu Hospital Affiliated to Capital Medical University, Beijing 100053, China
| | - Lou Zhong
- Thoracic Surgery Department, Affiliated Hospital of Nantong University, Nantong 226001, China
| | - Yiping Zhuang
- Department of Interventional Therapy, Jiangsu Cancer Hospital, Nanjing 210009, China
| | - Jiachang Chi
- Department of Interventional Oncology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
| | - Xichao Sun
- Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Nuo Yang
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Zhigang Wei
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Xiao Li
- Department of Interventional Therapy, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiaoguang Li
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, Beijing 100730, China
| | - Yuliang Li
- Department of Interventional Medicine, The Second Hospital of Shandong University, Jinan 250033, China
| | - Chunhai Li
- Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Yan Li
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Xia Yang
- Department of Oncology, Shandong Provincial Hospital Afliated to Shandong First Medical University, Jinan 250101, China
| | - Wuwei Yang
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing 100071, China
| | - Po Yang
- Interventionael & Vascular Surgery, The Fourth Hospital of Harbin Medical University, Harbin 150001, China
| | - Zhengqiang Yang
- Department of Interventional Therapy, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yueyong Xiao
- Department of Radiology, Chinese PLA Gneral Hospital, Beijing 100036, China
| | - Xiaoming Song
- Department of Thoracic Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Kaixian Zhang
- Department of Oncology, Tengzhou Central People's Hospital, Tengzhou 277500, China
| | - Shilin Chen
- Department of Thoracic Surgery, Jiangsu Cancer Hospital, Nanjing 210009, China
| | - Weisheng Chen
- Department of Thoracic Surgery, Fujian Medical University Cancer Hospital, Fujian 350011, China
| | - Zhengyu Lin
- Department of Intervention, The First Affiliated Hospital of Fujian Medical University, Fujian 350005, China
| | - Dianjie Lin
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Zhiqiang Meng
- Minimally Invasive Therapy Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Xiaojing Zhao
- Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
| | - Kaiwen Hu
- Department of Oncology, Dongfang Hospital Affiliated to Beijing University of Chinese Medicine, Beijing 100078, China
| | - Chen Liu
- Department of Interventional Therapy, Beijing Cancer Hospital, Beijing 100161, China
| | - Cheng Liu
- Department of Radiology, Shandong Medical Imaging Research Institute, Jinan 250021, China
| | - Chundong Gu
- Department of Thoracic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| | - Dong Xu
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China
| | - Yong Huang
- Department of Imaging, Affiliated Cancer Hospital of Shandong First Medical University, Jinan 250117, China
| | - Guanghui Huang
- Department of Oncology, Shandong Provincial Hospital Afliated to Shandong First Medical University, Jinan 250101, China
| | - Zhongmin Peng
- Department of Thoracic Surgery , Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Liang Dong
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Lei Jiang
- Department of Radiology, The Convalescent Hospital of East China, Wuxi 214063, China
| | - Yue Han
- Department of Interventional Therapy, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Qingshi Zeng
- Department of Medical Imaging, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Yong Jin
- Interventionnal Therapy Department, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China
| | - Guangyan Lei
- Department of Thoracic Surgery, Shanxi Provincial Cancer Hospital, Xi'an 710061, China
| | - Bo Zhai
- Department of Interventional Oncology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
| | - Hailiang Li
- Department of Interventional Radiology, Henan Cancer Hospital, Zhengzhou 450003, China
| | - Jie Pan
- Department of Radiology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
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Cerci JJ, Bogoni M, Cerci RJ, Masukawa M, Neto CCP, Krauzer C, Fanti S, Sakamoto DG, Barreiros RB, Nanni C, Vitola JV. PET/CT-Guided Biopsy of Suspected Lung Lesions Requires Less Rebiopsy Than CT-Guided Biopsy Due to Inconclusive Results. J Nucl Med 2020; 62:1057-1061. [PMID: 33384323 DOI: 10.2967/jnumed.120.252403] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 12/04/2021] [Indexed: 12/25/2022] Open
Abstract
The purpose of this study was to compare 18F-FDG PET/CT and CT performance in guiding percutaneous biopsies with histologic confirmation of lung lesions. Methods: We prospectively evaluated 341 patients, of whom 216 underwent 18F-FDG PET/CT-guided biopsy and 125 underwent CT-guided biopsy. The pathology results, lesion size, complications, and rebiopsy rate in the 2 groups were evaluated. Results: Of the 216 biopsies with PET/CT guidance, histology demonstrated 170 lesions (78.7%) to be malignant and 46 (21.3%) to be benign. In the CT-guided group, of 125 lesions, 77 (61.6%) were malignant and 48 (38.4%) were benign (P = 0.001). Inconclusive results prompted the need for a second biopsy in 18 patients: 13 of 125 (10.4%) in the CT group and 5 of 216 (2.3%) in PET group (P = 0.001). Complications were pneumothorax (13.2%), hemothorax (0.8%), and hemoptysis (0.6%). No life-threatening adverse events or fatalities were reported. The difference in complication rates between the 2 groups was not significant (P = 0.6). Malignant lesions showed a greater mean size than benign lesions regardless of the group (P = 0.015). Conclusion: PET/CT-guided biopsy of lung lesions led to fewer inconclusive biopsies than CT-guided biopsy, with similar complication rates.
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Affiliation(s)
- Juliano J Cerci
- PET/CT Department, Quanta Diagnóstico e Terapia, Curitiba, Brazil;
| | - Mateos Bogoni
- PET/CT Department, Quanta Diagnóstico e Terapia, Curitiba, Brazil
| | - Rodrigo J Cerci
- PET/CT Department, Quanta Diagnóstico e Terapia, Curitiba, Brazil
| | | | - Carlos C P Neto
- PET/CT Department, Quanta Diagnóstico e Terapia, Curitiba, Brazil
| | - Cassiano Krauzer
- PET/CT Department, Quanta Diagnóstico e Terapia, Curitiba, Brazil
| | - Stefano Fanti
- Nuclear Medicine Department, University Hospital S. Orsola-Malpighi, Bologna, Italy
| | | | - Renan B Barreiros
- Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Brazil
| | - Cristina Nanni
- Nuclear Medicine Department, University Hospital S. Orsola-Malpighi, Bologna, Italy
| | - João V Vitola
- PET/CT Department, Quanta Diagnóstico e Terapia, Curitiba, Brazil
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12
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Solitary pulmonary nodules caused by Mycobacterium avium complex. Respir Investig 2019; 57:566-573. [PMID: 31402330 DOI: 10.1016/j.resinv.2019.07.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 06/13/2019] [Accepted: 07/09/2019] [Indexed: 01/08/2023]
Abstract
BACKGROUND The prevalence of Mycobacterium avium complex (MAC) pulmonary disease (PD) is increasing significantly in Japan. Among the patterns of MAC-PD, a solitary pulmonary nodule (SPN) is less common and often resembles lung cancer. The aim of this study was to identify the clinical features of MAC-SPN. METHODS SPNs culture-positive for MAC (definite cases) and culture-negative SPNs showing nucleic acid amplification test (NAAT)-positive status (probable cases) that presented between January 2007 and December 2017 were enrolled. The patients' clinical, laboratory, radiological, and microbiological findings and outcomes were investigated. RESULTS This study included 28 patients (median age, 66 years; 16 men, 12 women). All patients were asymptomatic when the disease was detected. Median SPN size was 23.5 mm. Twenty-six patients underwent video-assisted thoracoscopic surgery, while the others underwent percutaneous needle biopsy for diagnosis. Granulomatous inflammation was confirmed in all cases. Microbiologically, the 28 cases were divided into 17 in the definite group and 11 in the probable group. In both groups, M. avium was predominant. There were no significant differences in clinical and radiological findings and follow-up periods between the 2 groups. After diagnosis, 6 patients received medical treatment, while the others did not. The median follow-up period was 42 months, and no recurrence was observed in both groups. CONCLUSIONS MAC should be considered in the differential diagnosis of SPNs in asymptomatic patients. To overcome the difficulties in diagnosing MAC-SPN, this study underscores the importance of diagnostic interventions and identification of MAC by culture and/or NAAT in biopsied specimens.
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Diagnostic value and safety of color doppler ultrasound-guided transthoracic core needle biopsy of thoracic disease. Biosci Rep 2019; 39:BSR20190104. [PMID: 31127026 PMCID: PMC6554213 DOI: 10.1042/bsr20190104] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Revised: 05/15/2019] [Accepted: 05/22/2019] [Indexed: 01/10/2023] Open
Abstract
Objective: The aim of the present study was to explore the diagnostic value and safety of color Doppler ultrasound (US)-guided transthoracic core needle biopsy (CNB) of peripheral lung, chest wall and mediastinal lesions using automated biopsy guns.Materials and methods: We analyzed clinical and image data, histopathologic and microbiologic details and complications from 121 patients with peripheral lung, chest wall and mediastinal lesions who underwent color Doppler US-guided transthoracic CNB in Ningbo First Hospital between January 2015 and June 2018.Results: Color Doppler US-guided transthoracic CNB performed with a freehand technique using automated biopsy guns had a sensitivity of 93.94%, a specificity of 100%, a positive predictive value of 100%, a negative predictive value of 78.57%, and a diagnostic accuracy of 95.04%. Lesion size did not affect the diagnostic rate (P=0.40). No serious complications of the procedure were noted.Conclusion: Color Doppler US-guided transthoracic CNB of peripheral lung, chest wall and mediastinal lesions is a safe and inexpensive procedure. The diagnostic accuracy of color Doppler US-guided transthoracic CNB was higher than that of color Doppler US-guided transthoracic fine needle aspiration biopsy (FNAB).
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Sakai H, Takeda M. Percutaneous transthoracic needle biopsy of the lung in the era of precision medicine. J Thorac Dis 2019; 11:S1213-S1215. [PMID: 31245089 DOI: 10.21037/jtd.2019.03.20] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Hitomi Sakai
- Department of Medical Oncology, Kindai University Faculty of Medicine, Osaka, Japan
| | - Masayuki Takeda
- Department of Medical Oncology, Kindai University Faculty of Medicine, Osaka, Japan
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