1
|
Zhu J, Fu CH, Chen L, Zhu Q, Zhu SS, Zheng J, Liao W, Li K, Wen W. Unveiling the synergetic benefits of the tunneling technique using stapler tractor in precise resection of lung segments: a retrospective cohort study. Front Oncol 2024; 14:1417871. [PMID: 39184038 PMCID: PMC11341400 DOI: 10.3389/fonc.2024.1417871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 07/23/2024] [Indexed: 08/27/2024] Open
Abstract
Background Tunneling technique has shown preliminary promise in lung segmentectomy which requires the use of staplers in specific procedures. However, the obstacle when staples pass is the most obvious factor hindering the implementation and development of this technique. This study investigated whether the obstacle of the technology could be addressed by using an innovative self-designed stapler tractor and analyzed the combined and respective advantages of them. Methods The clinical data of patients with lung nodules located near anatomical sites with potential tunnel creation treated by segmentectomy were analyzed in this retrospective case-control study. The data were divided into four groups according to four distinct surgical strategies: In Group A, the tunneling technique was performed with a stapler tractor; in Group B, the tunneling technique was performed without a stapler tractor; in Group C, didn't perform the tunneling technique but using stapler tractor in a normal approach; and in Group D, neither performed the technique nor used the stapler tractor. The general linear data, operation times, intraoperative adverse events, postoperative recovery and complications were compared. Results Compared with other groups, Group A exhibited the best surgical outcomes in comprehensive aspects. Separately, the tunnel groups (Group A&B) had better outcomes in the macro implementation of operation, including resection margin, the number of sampled intrapulmonary lymph nodes and resected subsegments, while the staple tractor groups (Group A&C) performed better on details of the procedure, including operation time, conversion to thoracotomy, and intraoperative bleeding (p < 0.05). Both of them were beneficial for shorter hospital stay, and the tunnel group was more advantageous. Conclusion The tunneling technique is an advanced and beneficial surgical strategy for performing precise resection of lung segments while a stapler tractor can promote and facilitate it as a supplementary instrument. They show more combined benefits in effectively minimizing the occurrence of erroneous injuries and enhancing the operational efficacy.
Collapse
Affiliation(s)
- Jian Zhu
- Department of Thoracic Cardiovascular Surgery, General Hospital of Central Theater Command of the People’s Liberation Army, Wuhan, China
| | - Cheng-Hao Fu
- Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Liang Chen
- Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Quan Zhu
- Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Shu-Sheng Zhu
- Department of Thoracic Surgery, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, China
| | - Jianan Zheng
- Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Wei Liao
- Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Kun Li
- Department of Anesthesiology, General Hospital of Central Theater Command of the Chinese People’s Liberation Army, Wuhan, China
| | - Wei Wen
- Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| |
Collapse
|
2
|
Sarnaik KS, Linden PA, Gasnick A, Bassiri A, Manyak GA, Jarrett CM, Sinopoli JN, Tapias Vargas L, Towe CW. Computational risk model for predicting 2-year malignancy of pulmonary nodules using demographic and radiographic characteristics. J Thorac Cardiovasc Surg 2024; 167:1910-1924.e2. [PMID: 37717851 DOI: 10.1016/j.jtcvs.2023.09.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/14/2023] [Accepted: 09/11/2023] [Indexed: 09/19/2023]
Abstract
OBJECTIVES To determine whether discriminatory performance of a computational risk model in classifying pulmonary lesion malignancy using demographic, radiographic, and clinical characteristics is superior to the opinion of experienced providers. We hypothesized that computational risk models would outperform providers. METHODS Outcome of malignancy was obtained from selected patients enrolled in the NAVIGATE trial (NCT02410837). Five predictive risk models were developed using an 80:20 train-test split: univariable logistic regression model based solely on provider opinion, multivariable logistic regression model, random forest classifier, extreme gradient boosting model, and artificial neural network. Area under the receiver operating characteristic curve achieved during testing of the predictive models was compared to that of prebiopsy provider opinion baseline using the DeLong test with 10,000 bootstrapped iterations. RESULTS The cohort included 984 patients, 735 (74.7%) of which were diagnosed with malignancy. Factors associated with malignancy from multivariable logistic regression included age, history of cancer, largest lesion size, lung zone, and positron-emission tomography positivity. Testing area under the receiver operating characteristic curve were 0.830 for provider opinion baseline, 0.770 for provider opinion univariable logistic regression, 0.659 for multivariable logistic regression model, 0.743 for random forest classifier, 0.740 for extreme gradient boosting, and 0.679 for artificial neural network. Provider opinion baseline was determined to be the best predictive classification system. CONCLUSIONS Computational models predicting malignancy of pulmonary lesions using clinical, demographic, and radiographic characteristics are inferior to provider opinion. This study questions the ability of these models to provide additional insight into patient care. Expert clinician evaluation of pulmonary lesion malignancy is paramount.
Collapse
Affiliation(s)
- Kunaal S Sarnaik
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Philip A Linden
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio; Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Allison Gasnick
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Aria Bassiri
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio; Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Grigory A Manyak
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Craig M Jarrett
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio; Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Jillian N Sinopoli
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio; Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Leonidas Tapias Vargas
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio; Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Christopher W Towe
- Department of Surgery, Case Western Reserve University School of Medicine, Cleveland, Ohio; Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio.
| |
Collapse
|
3
|
Fan N, Fang H, Huang F, Zhou J, Liu P, Li MJ, Ding YY. Metagenome next-generation sequencing plays a key role in the diagnosis and selection of effective antibiotics on the treatment of Nocardia pneumonia: a case report. Front Med (Lausanne) 2024; 11:1373319. [PMID: 38860208 PMCID: PMC11163097 DOI: 10.3389/fmed.2024.1373319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 05/09/2024] [Indexed: 06/12/2024] Open
Abstract
Nocardia disease is an opportunistic infection, the occurrence is rare and mostly occurs in patients with immune deficiency. Even if the patient is immunocompetent, it can still be life-threatening. This case report describes a previously healthy 78-year-old male farmer with lung lesions discovered on a computerized tomography scan. Combined with the patient's history of fever and the results of elevated laboratory markers associated with inflammation, the patient was diagnosed with a lung infection. After escalating empirical broad-spectrum antibiotics, antiviral and antifungal therapy, the patient continued to deteriorate to septic shock. In the meanwhile, the patient's sputum was cultured repeatedly, and no obvious positive pathogenic bacteria were found. Considering the patient was elderly and that these lesions were solid with burr signs, as well as the progression after antimicrobial therapy cancer was considered in the differential diagnosis. Artificial intelligence (YITU, Hangzhou Yitu Medical Technology Limited Company) was also applied, and it also calculated that these lesions were cancerous. The patient received a puncture biopsy of the largest lung lesion. During the puncture pus was withdrawn from largest lung lesion. Culture and metagenome next-generation sequencing (mNGS) detection performed on pus indicated Nocardia otitidiscaviarum. The test report of the mNGS is also attached with a susceptibility report of commonly used clinical antibiotics to this Nocardia spp. Using this result, the patient's disease was quickly controlled after selecting the targeted drug compound sulfamethoxazole and intravenous meropenem for treatment. In view of the high misdiagnosis rate and poor sensitivity of culture for Nocardia spp., this case emphasized mNGS playing a key role in the diagnosis and selection of effective antibiotics for the treatment of Nocardia spp. lung infections.
Collapse
Affiliation(s)
- Na Fan
- Department of Respiratory Oncology, Renmin Hospital of Qingxian, Cangzhou, China
| | - Huang Fang
- Department of Neurology, General Hospital of Central Theater Command of the People’s Liberation Army, Wuhan, China
| | - Fang Huang
- Department of Laboratory Medicine, Renmin Hospital of Qingxian, Cangzhou, China
| | - Jie Zhou
- Department of Respiratory Oncology, Renmin Hospital of Qingxian, Cangzhou, China
| | - Peng Liu
- Department of Respiratory Oncology, Renmin Hospital of Qingxian, Cangzhou, China
| | - Meng-Jie Li
- Department of Respiratory Oncology, Renmin Hospital of Qingxian, Cangzhou, China
| | - Ye-Ying Ding
- Department of Infectious Diseases, Hospital 902 of Joint Logistics Support Force of People’s Liberation Army, Bengbu, China
| |
Collapse
|
4
|
Li CP, Li L, Su LM, Zhu SS, Li MJ. Challenging Diagnosis: Unmasking the Enigma of Imaging Findings with Lung Schwannomas. Cancer Manag Res 2023; 15:1343-1347. [PMID: 38046891 PMCID: PMC10691372 DOI: 10.2147/cmar.s441736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 11/23/2023] [Indexed: 12/05/2023] Open
Abstract
Schwannomas are benign slow-growing tumors arising from the embryonic neural crest cells of the nerve sheaths of peripheral and cranial nerves, and they are a rare type of soft tissue mass that is usually always solitary. Generally, it grows in the head, neck, and flexor portions of the limbs, where many nerves are located. Schwannomas of the lung are extremely rare. Fewer than ten cases of schwannomas in this organ region have been reported in the existing literature. In this case report, a 40-year-old male non-smoker was hospitalized with occasional chest pain. His chest computed tomographic scan revealed a 3.8 cm space occupying lesion in the upper lobe of the right lung. This lesion has clear boundaries and uneven internal density. And it was concluded as a benign lesion possibility, it is preferred to be considered as a haematoma. This space occupying lesion was eventually confirmed as a schwannoma by needle biopsy tissues. Due to the presence in rare locations, such as the lung, the clinical presentation of this space occupying lesion is non-specific, making diagnosis difficult. The data presented in this case report can help clinicians to obtain information on the identification of this disease, which highlighted lung schwannoma as a differential diagnosis for patients with intermittent pain. It can also alert clinicians and radiologists to observe every detail of the radiology imaging findings.
Collapse
Affiliation(s)
- Cui-Ping Li
- Department of Pathology, Renmin Hospital of Qingxian, Cangzhou, People’s Republic of China
| | - Lei Li
- Department of the First Surgery, Wuhan Jin-Yin-Tan Hospital, Wuhan, People’s Republic of China
| | - Lin-Ming Su
- Department of Radiology, Renmin Hospital of Qingxian, Cangzhou, People’s Republic of China
| | - Shu-Sheng Zhu
- Department of Thoracic Surgery, Taizhou Hospital of Traditional Chinese Medicine, Taizhou, People’s Republic of China
| | - Meng-Jie Li
- Department of Respiratory Oncology, Renmin Hospital of Qingxian, Cangzhou, People’s Republic of China
| |
Collapse
|