18F-FDG PET-based radiomics model for predicting occult lymph node metastasis in clinical N0 solid lung adenocarcinoma

Background: To date, postoperative intractable cough (PIC) has not received adequate attention, and the complex perioperative factors when performing pulmonary resection often prevent researchers from addressing this issue. This study aimed to investigate the clinicopathological and radiographic indicators related to PIC in lung cancer patients.Methods: In all, 112 patients who had had right upper lobectomy for primary lung cancer from January 2019 to December 2020 were retrospectively reviewed. We collected data via the electronic medical database of our department. Bronchial morphological features were investigated comprehensively via threedimensional chest computer tomography reconstruction images.Results: During outpatient follow-up visits, 41 (36.6%) patients complained about persistent dry cough after surgery. Compared with the non-cough group, patients in the refractory cough group showed significant differences in smoking history, right upper lobe stump length, changes of right bronchus intermedius (RBI) diameter, changes of right lower lobe (RLL) basal bronchus diameter, changes of RBI/ RLL bronchial angle, and bronchial kink. However, according to multivariable regression analysis, stump length, bronchial kink, and diameter change of the right lower lobe basal bronchus were independently associated with postoperative refractory cough. A nebulization drug was prescribed for the 41 patients diagnosed with PIC, and 33 (80.5%) patients had improved by the next visit.Conclusions: After right upper lobectomy, the morphology of the remaining bronchial tree in the residual lung changed significantly. The bronchial morphological alterations were independent risk factors for PIC.

Section: Introductionmentioning

confidence: 99%

Bronchial morphological changes are associated with postoperative intractable cough after right upper lobectomy in lung cancer patients

Lu¹,

Min²,

Biao³

et al. 2022

“…However, the measurement of solid tumor size differed using different software and among the different observers (28,29). 18 F-FDG PET-CT integrates anatomical and metabolic information and is currently the primary tool for staging NSCLC (30), and previous studies have demonstrated that SUV max was related to VPI, LVI, and LNM. Tsutani et al (31) reported that the SUV max on 18 F-FDG PET-CT helped predict pathological invasiveness in clinical stage IA lung AC and 18 F-FDG uptake was closely related to solid tumor size.…”

Section: Discussionmentioning

confidence: 99%

Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on 18F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study

Li¹,

Shi²,

Niu³

et al. 2022

Background: Sublobar resection is not suitable for patients with pathological invasiveness [including lymph node metastasis (LNM), visceral pleural invasion (VPI), and lymphovascular invasion (LVI)] of peripheral clinical T1 (cT1) non-small-cell lung cancer (NSCLC), while primary tumor maximum standardized uptake value (SUV max ) on 18 F-FDG PET-CT is related to pathological invasiveness, the significance differed among different institutions is still challenging. This study explored the relationship between the tumor-to-blood standardized uptake ratio (SUR) of 18 F-FDG PET-CT and primary tumor pathological invasiveness in peripheral cT1 NSCLC patients.Methods: This retrospective study included 174 patients with suspected lung neoplasms who underwent preoperative 18 F-FDG PET-CT. We compared the differences of the clinicopathological variables, metabolic and morphological parameters in the pathological invasiveness and less-invasiveness group. We performed a trend test for these parameters based on the tertiles of SUR. The relationship between SUR and pathological invasiveness was evaluated by univariate and multivariate logistics regression models (included unadjusted, simple adjusted, and fully adjusted models), odds ratios (ORs), and 95% confidence intervals (95% CIs) were calculated. A smooth fitting curve between SUR and pathological invasiveness was produced by the generalized additive model (GAM).Results: Thirty-eight point five percent of patients had pathological invasiveness and tended to have a higher SUR value than the less-invasiveness group [6.50 (4.82-11.16) vs. 4.12 (2.04-6.61), P<0.001]. The trend of SUV max , mean standardized uptake value (SUV mean ), metabolic tumor volume (MTV), total lesion glycolysis (TLG), mean CT value (CT mean ), size of the primary tumor, neuron-specific enolase (NSE), the incidence of LNM, adenocarcinoma (AC), and poor differentiation in the tertiles of SUR value were statistically significant (P were <0.

“…It is therefore necessary to develop a novel signature to improve the prediction of death or recurrence risk in patients with LUAD. Radiomics is an emerging technique that converts conventional medical images into high dimensional features, providing valuable data to develop noninvasive signatures for cancer prognosis (12,42,43). Compared with tumor phenotypic radiomic features derived from CT or PET/CT, which are sensitive to the multicenter effect (28), metabolic features are more repeatable and reproducible across multicenter cohorts and are more suitable for clinical application.…”

Section: Discussionmentioning

confidence: 99%

Identifying 18F-FDG PET-metabolic radiomic signature for lung adenocarcinoma prognosis via the leveraging of prognostic transcriptomic module

Li¹,

Liu²,

Dong³

et al. 2022

Background: Imaging with 18 F-fluorodeoxyglucose positron emission tomography ( 18 F-FDG PET), which identifies molecular and metabolic abnormalities within tumor cells, could support prognostic assessment of lung adenocarcinoma (LUAD). We aimed to develop a radiomic signature with the aid of a transcriptomic module for individualized clinical prognostic assessment of LUAD patients.Methods: Using a gene expression profile consisting of 334 stage I-IIIA LUAD patients, prognosticrelated gene coexpression modules were constructed via a weighted correlation network analysis algorithm.The robustness and prognostic performance of the coexpression modules were then tested across 2 gene expression datasets totaling 331 patients. Finally, using a discovery dataset with matched transcriptomic and 18 F-FDG PET radiomic data of 15 patients and multiple linear regression analysis, we developed a PETmetabolic radiomic signature that had optimal correlation with the expression of a robust prognostic module.Results: We selected a superior coexpression module for LUAD prognosis in which the genes were significantly enriched in important biological processes associated with tumors (e.g., cell cycle, DNA replication and p53 signaling pathway). The prognostic performance of the module for overall survival (OS) and recurrence-free survival (RFS) was validated in 2 independent gene expression datasets (log-rank P<0.05).Through the leveraging of this prognostic coexpression module, a radiomic signature consisting of 3 PET features associated with metabolic processes was developed in the discovery dataset. The radiomic signature was significantly associated with patients' OS and RFS in an independent PET dataset consisting of 72 LUAD patients (OS: log-rank P=0.0006; RFS: log-rank P=0.0013). Multivariate Cox analysis demonstrated that the radiomic signature was an independent prognostic factor for OS and RFS. Furthermore, the novel proposed radiomic nomograms for OS and RFS had significantly better performance (concordance indices) than did the clinicopathological nomograms. Conclusions:The radiomic signature, which reflects biological processes in tumors (e.g., cell cycle and p53 signaling pathway), could noninvasively identify LUAD patients with poor prognosis who should receive ^ ORCID: Yixin Liu, 0000-0002-5988-722X; Lishuang Qi, 0000-0002-2991-6544. 2 Li et al. 18 F-FDG PET radiomic signature for lung cancer prognosis