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Han L, Jia H, Song P, Liu X, Wang Z, Zhang D. Lymph node metastases outside tumor-bearing lobes and/or segments in non–small cell lung cancer. Front Med (Lausanne) 2022; 9:960689. [PMID: 36111114 PMCID: PMC9468442 DOI: 10.3389/fmed.2022.960689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/12/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveHilar and lung lymph node metastases (N1) are defined as ipsilateral bronchial and intrapulmonary lymph nodes. However, the cleaning standards for ipsilateral bronchial lymph nodes in different lobes and segments within the same lobe in segmentectomy are not clearly defined.Materials and methodsSixty-six patients undergoing pulmonary resection for the treatment of lung cancer were evaluated. Intraoperatively visible non-tumor-bearing lobe (NTBL) and post-operatively non-tumor-bearing segment (NTBS) lymph nodes were removed and analyzed. The associations between the NTBL LNs and clinicopathological characteristics were analyzed.ResultsNon-tumor-bearing lobe LNs metastases were found in 8 (12.1%) of the 66 patients, NTBS LNs metastasis were not found (0/13). The presence of NTBL metastases was significantly associated with age (<60 years vs. ≥60 years, P = 0.037), differentiation (Grade 1 well differentiated vs. Grade 2 moderately differentiated vs. Grade 3 poorly differentiated, P = 0.012), CAT-scan-findings of Mediastinal and hilar lymph nodes metastasis (node-positive vs. node-negative, P = 0.022), pN stage (N0 vs. N1 vs. N2, P = 0.003) and p stage (I vs. II vs. III, P = 0.009). Multivariate logistic analysis showed that tumor differentiation (P = 0.048, HR 6.229; 95% CI 1.016–38.181) and pN (P = 0.024, HR 5.099; 95% CI 1.245–20.878) were statistically significant predictors.ConclusionsLobar lymph node metastasis of NTBL occurs frequently in patients with NSCLC, but lymph node metastases in NTBS LNs are rare. Advanced age, poorly differentiated and N1 and N2 status of CAT-scan-findings were independent risk factors for the involvement of the NTBL lobar lymph nodes. Although lymph node metastases in NTBS are rare, further investigation of the need to dissect is required.
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Affiliation(s)
- Lu Han
- Department of Thoracic Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Hui Jia
- Department of Respiratory Internal, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
- *Correspondence: Hui Jia,
| | - Pingping Song
- Department of Thoracic Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xibin Liu
- Department of Thoracic Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Zhendan Wang
- Department of Thoracic Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Dujian Zhang
- Department of Surgery, Zaozhuang Tumour Hospital, Zaozhuang, China
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Opposits G, Nagy M, Barta Z, Aranyi C, Szabó D, Makai A, Varga I, Galuska L, Trón L, Balkay L, Emri M. Automated procedure assessing the accuracy of HRCT-PET registration applied in functional virtual bronchoscopy. EJNMMI Res 2021; 11:69. [PMID: 34312736 PMCID: PMC8313651 DOI: 10.1186/s13550-021-00810-w] [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: 04/29/2021] [Accepted: 07/11/2021] [Indexed: 12/02/2022] Open
Abstract
Background Bronchoscopy serves as direct visualisation of the airway. Virtual bronchoscopy provides similar visual information using a non-invasive imaging procedure(s). Early and accurate image-guided diagnosis requires the possible highest performance, which might be approximated by combining anatomical and functional imaging. This communication describes an advanced functional virtual bronchoscopic (fVB) method based on the registration of PET images to high-resolution diagnostic CT images instead of low-dose CT images of lower resolution obtained from PET/CT scans. PET/CT and diagnostic CT data were collected from 22 oncological patients to develop a computer-aided high-precision fVB. Registration of segmented images was performed using elastix.
Results For virtual bronchoscopy, we used an in-house developed segmentation method. The quality of low- and high-dose CT image registrations was characterised by expert’s scoring the spatial distance of manually paired corresponding points and by eight voxel intensity-based (dis)similarity parameters. The distribution of (dis)similarity parameter correlating best with anatomic scoring was bootstrapped, and 95% confidence intervals were calculated separately for acceptable and insufficient registrations. We showed that mutual information (MI) of the eight investigated (dis)similarity parameters displayed the closest correlation with the anatomy-based distance metrics used to characterise the quality of image registrations. The 95% confidence intervals of the bootstrapped MI distribution were [0.15, 0.22] and [0.28, 0.37] for insufficient and acceptable registrations, respectively. In case of any new patient, a calculated MI value of registered low- and high-dose CT image pair within the [0.28, 0.37] or the [0.15, 0.22] interval would suggest acceptance or rejection, respectively, serving as an aid for the radiologist.
Conclusion A computer-aided solution was proposed in order to reduce reliance on radiologist’s contribution for the approval of acceptable image registrations.
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Affiliation(s)
- Gábor Opposits
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary.
| | - Marianna Nagy
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary.,Division of Radiology and Imaging Science, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Zoltán Barta
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Csaba Aranyi
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Dániel Szabó
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Attila Makai
- Department of Pulmonology, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Imre Varga
- Department of Pulmonology, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - László Galuska
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Lajos Trón
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - László Balkay
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
| | - Miklós Emri
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98., Debrecen, 4032, Hungary
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