Simultaneous Bilateral Thoracoscopic Pneumonectomy for Early Multiple Primary Lung Cancer Feasibility Analysis

Objective:To analyze the feasibility of simultaneous bilateral thoracoscopic lung resection in the treatment of multiple primary lung cancers in the early stage.Methods:The study time range is between March 2019 and March 2021.A sample of 30 patients with early multiple primary lung cancer admitted to this hospital were included,and they were divided into a study group,a control group,and samples within the group using a random number table scheme n=15,patients in the control group underwent staged bilateral thoracoscopic pneumonectomy,and patients in the study group underwent bilateral thoracoscopic pneumonectomy at the same time.The indicators of the two groups were compared and analyzed.Results:There was no significant difference in the operation time and intraoperative blood loss between the two groups(P>0.05).There were significant differences in the VAS score,total length of hospital stay,and total surgical costs on the first day after surgery(P<0.05);there was no significant difference in the two groups'postoperative recovery indicators and the incidence of complications(P>0.05).Conclusion:It is safe and feasible to treat patients with multiple primary lung cancer in both lungs at the same time with simultaneous bilateral thoracoscopic surgery,and is suitable for promotion.

Lack of evolutionary convergence in multiple primary lung cancer suggests insufficient specificity of personalized therapy

Multiple primary lung cancer(MPLC)is an increasingly prevalent subtype of lung cancer.According to recent genomic studies,the different lesions of a single MPLC patient exhibit functional similarities that may reflect evolutionary convergence.We perform whole-exome sequencing for a unique cohort of MPLC patients with multiple samples from each lesion found.Using our own and other relevant public data,evolutionary tree reconstruction reveals that cancer driver gene mutations occurred at the early trunk,indicating evolutionary contingency rather than adaptive convergence.Additionally,tumors from the same MPLC patient are as genetically diverse as those from different patients,while within-tumor genetic heterogeneity is significantly lower.Furthermore,the aberrant molecular functions enriched in mutated genes for a sample show a strong overlap with other samples from the same tumor,but not with samples from other tumors or other patients.Overall,there is no evidence of adaptive convergence during the evolution of MPLC.Most importantly,the similar between-tumor diversity and between-patient diversity suggest that personalized therapies may not adequately account for the genetic diversity among different tumors in an MPLC patient.To fully exploit the strategic value of precision medicine,targeted therapies should be designed and delivered on a per-lesion basis.

A pairwise radiomics algorithm–lesion pair relation estimation model for distinguishing multiple primary lung cancer from intrapulmonary metastasis

Background:Distinguishing multiple primary lung cancer(MPLC)from intrapulmonary metastasis(IPM)is critical for their disparate treatment strategy and prognosis.This study aimed to establish a non-invasive model to make the differentiation pre-operatively.Methods:We retrospectively studied 168 patients with multiple lung cancers(307 pairs of lesions)including 118 cases for modeling and internal validation,and 50 cases for independent external validation.Radiomic features on computed tomography(CT)were extracted to calculate the absolute deviation of paired lesions.Features were then selected by correlation coefficients and random forest classifier 5-fold cross-validation,based on which the lesion pair relation estimation(PRE)model was developed.A major voting strategy was used to decide diagnosis for cases with multiple pairs of lesions.Cases from another institute were included as the external validation set for the PRE model to compete with two experienced clinicians.Results:Seven radiomic features were selected for the PRE model construction.With major voting strategy,the mean area under receiver operating characteristic curve(AUC),accuracy,sensitivity,and specificity of the training versus internal validation versus external validation cohort to distinguish MPLC were 0.983 versus 0.844 versus 0.793,0.942 versus 0.846 versus 0.760,0.905 versus 0.728 versus 0.727,and 0.962 versus 0.910 versus 0.769,respectively.AUCs of the two clinicians were 0.619 and 0.580.Conclusions:The CT radiomic feature-based lesion PRE model is potentially an accurate diagnostic tool for the differentiation of MPLC and IPM,which could help with clinical decision making.