Clinical Stage IA Research Articles

P3.13C.08 Optimal Treatment Strategies for Older Adults with Clinical Stage IA Small Cell Lung Cancer

P3.13C.08 Optimal Treatment Strategies for Older Adults with Clinical Stage IA Small Cell Lung Cancer

Predicting Recurrence after Sublobar Resection in Patients with Lung Adenocarcinoma Using Preoperative Chest CT Scans.

Background Sublobar resection for lung cancer is usually guided by cutoff values for consolidation size (maximal diameter of the solid tumor component) and consolidation-to-tumor ratio (CTR). The effects of these factors as continuous variables and the reason for established cutoffs are, to the knowledge of the authors, unexplored. Purpose To quantitatively assess the predictive value of CTR and consolidation size for cancer recurrence risk after sublobar resection in clinical stage IA lung adenocarcinoma. Materials and Methods This retrospective study reviewed sublobar resection for clinical stage IA lung adenocarcinoma performed between January 2010 and December 2019. A restricted cubic spline function verified linearity by estimating recurrence probabilities using CTR and consolidation size obtained on preoperative CT scans. Statistical analyses included a Cox proportional hazards model to identify risk factors for cancer recurrence and the Cochran-Armitage trend test for the association between CTR and consolidation size. Results Of 1032 enrolled patients (age, 63.9 years ± 9.9 [SD]; 464 male patients), 523 (50.7%) and 509 (49.3%) underwent wedge resection and segmentectomy, respectively. Among patients with a CTR between 1% and 50% (n = 201), 187 (93.0%) had a consolidation size of less than or equal to 10 mm (P < .001). There was a positive association between the risk of recurrence with CTR and consolidation size (r2 = 0.727; P < .001). The recurrence rate showed the greatest increase when CTR was greater than 50% or consolidation size was greater than 10 mm. Specifically, the recurrence rate increased from 2.1% (three of 146) at 26%-50% CTR to 8.3% (nine of 108) at 51%-75% CTR, and from 4.4% (eight of 183) for 6-10-mm consolidation size to 11.9% (23 of 194) for 11-15-mm consolidation size. The probability of recurrence exhibited linearity and increased with CTR and consolidation size. Conclusion Cancer recurrence risk after sublobar resection for stage IA adenocarcinoma consistently rises with CTR and consolidation size. Current guideline cutoffs for sublobar resection remain clinically relevant given observed recurrence rates. © RSNA, 2024 Supplemental material is available for this article.

Long-term prognostic characteristics of patients with clinical stage IA part-solid lung adenocarcinoma: a conditional survival analysis.

Despite excellent 5-year survival, there are limited data on the long-term prognostic characteristics of clinical stage IA part-solid lung adenocarcinoma. The objective was to elucidate the dynamics of prognostic characteristics through conditional survival analysis. Consecutive patients who underwent complete resection for clinical stage IA part-solid lung adenocarcinoma between 2011 and 2015 were retrospectively reviewed. Conditional survival is defined as the probability of surviving further y years, conditional on the patient has already survived x years. The conditional recurrence-free survival (CRFS) and conditional overall survival (COS) were analysed to evaluate prognosis over time, with conditional Cox regression analysis performed to identify time-dependent prognostic factors. A total of 1539 patients were included with a median follow-up duration of 98.4 months, and 80 (5.2%) patients experienced recurrence. Among them, 20 (1.3%) recurrence cases occurred after 5 years of follow-up with 100% intrathoracic recurrence. The 5-year CRFS increased from 95.8% to 97.4%, while the 5-year COS maintained stable. Multivariable Cox analysis revealed that histologic subtype was always an independent prognostic factor for CRFS even after 5 years of follow-up, while the independent prognostic value of consolidation-to-tumour ratio, visceral pleural invasion and lymph node metastasis was observed only within 5 years. Besides, age, pathologic size and lymph node metastasis maintained independent predictive value for COS during long-term follow-up, while consolidation-to-tumour ratio was predictive for COS only within 5 years of follow-up. The independent prognostic factors for clinical stage IA part-solid lung adenocarcinoma changed over time, along with gradually increasing 5-year CRFS and stable 5-year COS.

The impact of postoperative adjuvant therapy on EGFR-mutated stage IA lung adenocarcinoma with micropapillary pathological subtypes

BackgroundMicropapillary (MPP) adenocarcinoma is considered one of the most aggressive pathological types of lung adenocarcinoma (LADC). This retrospective study aimed to evaluate the prognostic significance and benefit of postoperative adjuvant therapy (PAT) in stage IA LADC patients with different proportions of MPP components.Materials and methodsWe retrospectively examined clinical stage IA LADC patients who underwent surgical resection between August 2012 and December 2019. In terms of the proportion of MPP components (TPM), the tumors were reclassified into three categories: MPP patterns absent (TPMN); low proportions of MPP components (TPML); and high proportions of MPP components (TPMH). The dates of recurrence and metastasis were identified based on physical examinations and were confirmed by histopathological examination.ResultsOverall, 505 (TPMN, n = 375; TPML, n = 92; TPMH, n = 38) patients harboring EGFR mutations were enrolled in the study. Male sex (P = 0.044), high pathological stage (P < 0.001), and MPP pathological subtype (P < 0.001) were more frequent in the TPM-positive (TPMP) group than in the TPM-negative (TPMN) group. Five-year disease-free survival (DFS) rates were significantly lower in the TPMP group than in the TPMN group (84.5% vs. 93.4%, P = 0.006). In addition, patients with high proportions (greater than 10%) of MPP components had worse overall survival (OS) (91.0% vs. 98.9%, P = 0.025) than those with low proportions (5%≤ TPM ≤ 10%). However, postoperative EGFR tyrosine kinase inhibitors (TKIs) or adjuvant chemotherapy (ACT) cannot improve DFS and OS between EGFR-mutated patients with different proportions of MPP components.ConclusionMPP was related to earlier recurrence and shortened survival time, even in stage IA. Further research needs a larger sample size to clarify that EGFR-mutated stage IA patients with MPP components obtain survival benefits from adjuvant therapy.

CT-based radiomic consensus clustering association with tumor biological behavior in clinical stage IA adenocarcinoma: a retrospective study.

Research has demonstrated that radiomics models are capable of forecasting the characteristics of lung cancer. Nevertheless, due to radiomics' poor interpretability, its applicability in clinical settings remains restricted. This investigation sought to verify the correlation between radiomics features (RFs) and the biological behavior of clinical stage IA adenocarcinomas. A retrospective analysis was conducted on patients diagnosed with clinical stage IA lung adenocarcinoma who underwent resection between May 2005 and December 2018. Detailed radiomics examination of the primary tumor was carried out utilizing preoperative computed tomography (CT) images. Subsequently, patients were grouped based on their RFs using consensus clustering, enabling comparison of tumor biological characteristics among the clusters. Survival disparities among the clusters were evaluated through Kaplan-Meier and Cox analyses. A consensus cluster analysis was performed on 669 patients [median age, 58 years; interquartile range (IQR), 50-64 years, 257 males, 412 females], and three distinct clusters were identified. Cluster 2 was associated with radiological solid adenocarcinoma [119 of 324 (36.7%), P<0.001], larger tumors with median tumor size of 2.1 cm with IQR of 1.7 to 2.5 cm (P<0.001), central tumor [91 of 324 (28.1%), P=0.002], pleural invasion [87 of 324 (26.9%), P<0.001], occult lymph node metastasis (ONM) [106 of 324 (32.7%), P<0.001], and a higher frequency of metastasis or recurrence [62 of 324 (19.1%), P<0.001]. The frequency of histological grade 3 was the highest in Cluster 3 [8 of 34 (23.5%), P<0.001]. Cluster 1 was associated with pure ground glass nodules (pGGNs) [184 of 310 (59.4%), P<0.001], smaller tumors with median tumor size of 1.1 cm with IQR of 0.8 to 1.4 cm (P<0.001), no pleural invasion [276 of 310 (89.0%), P<0.001], histological grade 1 [114 of 248 (46.0%), P<0.001], ONM negative [292 of 310 (94.2%), P<0.001], and a lower rate of metastasis or recurrence [298 of 310 (96.1%), P<0.001]. Differences in tumor biological behavior were detected among consensus clusters based on the RFs of clinical stage IA adenocarcinoma.

Gene mutation characteristics of clinical stage ⅠA lung adenocarcinoma and their relations with patients' long-term prognosis

Objective: To explore the gene mutation characteristics and the relationship between gene mutations and long-term prognosis in clinical stage ⅠA lung adenocarcinoma patients. Methods: A retrospective analysis was conducted on 63 clinical stage ⅠA lung adenocarcinoma patients who underwent surgical resection at the Cancer Hospital of the Chinese Academy of Medical Sciences from January 2007 to October 2012, with documented postoperative recurrence or metastasis, as well as those who had a follow-up duration of 10 years or more without recurrence or metastasis. Whole exome sequencing (WES) technology was used to analyze the gene mutation profiles in tumor tissues and univariate and multivariate Cox regression analysis were used to clarify the influencing factors for patient prognosis. Results: After long term follow-up, 13 out of the 63 patients (21%) experienced recurrence or metastasis. WES technology analysis revealed that the most common tumor related gene mutations occurred in epidermal growth factor receptor (EGFR), with a mutation rate of 65.1% (41/63), followed by tumor protein p53 (TP53), fatatypical cadherin 1 (FAT1), low density lipoprotein receptor-related protein 1B (LRP1B), mechanistic target of rapamycin (MTOR), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma (PIK3CG), and SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily A, member 4 (SMARCA4), with mutation rates of 30.2% (19/63), 20.6% (13/63), 15.9% (10/63), 15.9% (10/63), 15.9% (10/63), and 15.9% (10/63), respectively. Multivariate Cox regression analysis showed that PIK3CG mutations (HR=21.52, 95% CI: 3.19-145.01),smoothened (SMO) mutations (HR=35.28, 95% CI: 3.12-398.39), catenin beta 1 (CTNNB1) mutations (HR=332.86, 95% CI: 15.76-7 029.05), colony stimulating factor 1 receptor (CSF1R) mutations (HR=8 109.60, 95% CI: 114.19-575 955.17), and v-Raf murine sarcoma viral oncogene homolog B (BRAF) mutations (HR=23.65, 95% CI: 1.86-300.43) were independent risk factors affecting the prognosis of clinical stage ⅠA lung adenocarcinoma patients. Conclusions: PIK3CG, SMO, CTNNB1, CSF1R, BRAF gene mutations are closely related to long-term recurrence or metastasis in clinical stage ⅠA lung adenocarcinoma. Patients with these gene mutations should be given closer clinical attention.

Utility of PET for Nodal Staging in Subsolid Clinical Stage IA (T1 N0) Lung Adenocarcinoma

BackgroundPositron emission tomography (PET) is the standard of care for non-small cell lung cancer (NSCLC) clinical staging, but it may have limited utility in evaluating subsolid lung adenocarcinomas that can have relatively indolent behavior without hypermetabolic activity. MethodsThe sensitivity and specificity of PET for determining pathologic lymph node status and disease-free survival were assessed in patients operated on for cT1 N0 subsolid lung adenocarcinoma from January 2006 to June 2022 (at Stanford University School of Medicine, Stanford, CA). Patients with clinical or pathologic tumor size >30 mm, hilar or mediastinal lymph node size >1cm, and purely solid tumors were excluded. ResultsPET was available in 498 of 534 (93.2%) patients and more often was used in older patients with larger and more solid tumors. The overall pathologic lymph node–positive rate was 8.4% (45 of 534). PET specificity was 95.1%, but sensitivity was only 20.0%. A tumor diameter of 18.5 mm and a solid component percentage of 62.5% had the maximum predictive accuracy for pathologic lymph node positivity, with a 0% and 1.5% rate of pathologic and PET lymph node positivity, respectively, for tumors with values lower than those thresholds. There was no significant difference in 5-year disease-free survival between individuals who did and did not undergo PET scanning (76.6% vs 96.8%; P = .07). Conversely, 134 (26.9%) patients who underwent PET scanning had 171 incidentally detected hypermetabolic lesions unrelated to lung cancer, with only 13 of 134 (9.7%) patients identified as having non-NSCLC premalignant or malignant conditions requiring further therapy. ConclusionsPET scan use for subsolid lung adenocarcinoma has high specificity but limited sensitivity for predicting pathologic lymph node positivity. PET also has no association with disease-free survival and often detects clinically unimportant findings rather than changing lung cancer management, particularly for patients with smaller and less solid tumors.

Commentator Discussion: Preoperatively predicting survival outcome for clinical stage IA pure-solid non–small cell lung cancer by radiomics-based machine learning

Commentator Discussion: Preoperatively predicting survival outcome for clinical stage IA pure-solid non–small cell lung cancer by radiomics-based machine learning

Investigation of mediastinal lymph node dissection in clinical stage IA pure-solid non-small cell lung cancer patients

ObjectiveTo explore the independent predictors of pathological mediastinal lymph node (pN2) metastasis in clinical stage IA (cIA) pure-solid non-small cell lung cancer (NSCLC) patients, and to find an appropriate method of mediastinal lymph node dissection.MethodsThis study retrospectively evaluated 533 cIA pure-solid NSCLC patients who underwent radical resection of lung cancer (lobectomy combined with systematic lymph node dissection) from January 2014 to December 2016. The relationship between clinicopathological characteristics and pN2 metastasis was analyzed, and the independent predictors of pN2 metastasis were determined by univariate and multivariate logistic regression analysis. We defined the new factor Y as composed of preoperative cT, CEA, and NSE.ResultsThere were 72 cases (13.5%) of pN2 metastasis in cIA pure-solid NSCLC patients. Preoperative clinical tumor diameter (cT), serum CEA level, serum NSE level, and pathological status of station 10 lymph nodes were independent predictors of pN2 metastasis. Patients with cT ≤ 21.5 mm, CEA ≤ 3.85 ng/mL, NSE ≤ 13.40 ng/mL and negative station 10 lymph node group showed lower rates of pN2 metastasis. The new factor Y was an independent predictor of pN2 metastasis. Only 3 (2.1%) of 143 patients in the Y low-risk group showed pN2 metastasis.ConclusionFor patients with low risk of pN2 metastasis, it might be feasible to take lobe-specific lymph node sampling or systematic lymph node sampling. As for those with high risk of pN2 metastasis, systematic lymph node dissection would be recommended.

Does clinical T1N0 GGN really require checking for distant metastasis during initial staging for lung cancer?

BackgroundAccurate clinical staging is crucial for selection of optimal oncological treatment strategies in non-small cell lung cancer (NSCLC). Although brain MRI, bone scintigraphy and whole-body PET/CT play important roles in detecting distant metastases, there is a lack of evidence regarding the indication for metastatic staging in early NSCLCs, especially ground-grass nodules (GGNs). Our aim was to determine whether checking for distant metastasis is required in cases of clinical T1N0 GGN.MethodsThis was a retrospective study of initial staging using imaging tests in patients who had undergone complete surgical R0 resection for clinical T1N0 Stage IA NSCLC.ResultsA total of 273 patients with cT1N0 GGNs (n = 183) or cT1N0 solid tumors (STs, n = 90) were deemed eligible. No cases of distant metastasis were detected on initial routine imaging evaluations. Among all cT1N0M0 cases, there were 191 incidental findings on various modalities (128 in the GGN). Most frequently detected on brain MRI was cerebral leukoaraiosis, which was found in 98/273 (35.9%) patients, while cerebral infarction was detected in 12/273 (4.4%) patients. Treatable neoplasms, including brain meningioma and thyroid, gastric, renal and colon cancers were also detected on PET/CT (and/or MRI). Among those, 19 patients were diagnosed with a treatable disease, including other-site cancers curable with surgery.ConclusionsExtensive staging (MRI, scintigraphy, PET/CT etc.) for distant metastasis is not required for patients diagnosed with clinical T1N0 GGNs, though various imaging modalities revealed the presence of adventitious diseases with the potential to increase surgical risks, lead to separate management, and worsen patient outcomes, especially in elderly patients. If clinically feasible, it could be considered to complement staging with whole-body procedures including PET/CT.

Outcomes of Patients Undergoing Segmentectomy for Occult Node-Positive Clinical Stage IA Lung Cancer

BackgroundResults of recent clinical trials suggest that segmentectomy may be an acceptable alternative to lobectomy for selected patients with early-stage non-small cell lung cancer (NSCLC). Increased use of segmentectomy may result in a concomitant increase in occult node-positive (N+) disease on surgical pathology examination. The optimal management for such patients remains unknown. MethodsClinicopathologic data were abstracted from a prospective institutional database to identify patients with pathologic N+ disease after segmentectomy for cT1 N0 M0 NSCLC. Propensity score matching identified a comparable lobectomy cohort for assessment of cumulative incidence of recurrence and overall survival (OS). ResultsOf 759 included patients, 27 (4%) had nodal upstaging on the final pathology report. Of these 27 patients, 4 (15%) had skip metastasis to N2 stations, and 20 (74%) received adjuvant therapy; no completion lobectomies were performed. Ten patients (37%) had disease recurrence: 3 isolated locoregional (11%) and 7 distant (26%). The median time to recurrence among patients with recurrence was 1.8 years; OS after recurrence was 3.4 years. After 5:1 matching with 109 patients who underwent lobectomy, all variables were balanced between the groups, except pathologic N2 stage and open surgical approach. The 5-year cumulative incidence of recurrence was not significantly different between segmentectomy and lobectomy (42% vs 52%, respectively; Gray’s P = .1). The 5-year OS (63% and 50%) and rate of locoregional recurrence (12% vs 13%) were not statistically different between the groups. ConclusionsPatients with occult N+ disease after segmentectomy for cT1 N0 M0 NSCLC had limited isolated locoregional recurrences and outcomes similar to those in patients who underwent lobectomy. Lobectomy may not provide an advantage in these patients.

Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma

BackgroundAccurate prediction of visceral pleural invasion (VPI) in lung adenocarcinoma before operation can provide guidance and help for surgical operation and postoperative treatment. We investigate the value of intratumoral and peritumoral radiomics nomograms for preoperatively predicting the status of VPI in patients diagnosed with clinical stage IA lung adenocarcinoma.MethodsA total of 404 patients from our hospital were randomly assigned to a training set (n = 283) and an internal validation set (n = 121) using a 7:3 ratio, while 81 patients from two other hospitals constituted the external validation set. We extracted 1218 CT-based radiomics features from the gross tumor volume (GTV) as well as the gross peritumoral tumor volume (GPTV5, 10, 15), respectively, and constructed radiomic models. Additionally, we developed a nomogram based on relevant CT features and the radscore derived from the optimal radiomics model.ResultsThe GPTV10 radiomics model exhibited superior predictive performance compared to GTV, GPTV5, and GPTV15, with area under the curve (AUC) values of 0.855, 0.842, and 0.842 in the three respective sets. In the clinical model, the solid component size, pleural indentation, solid attachment, and vascular convergence sign were identified as independent risk factors among the CT features. The predictive performance of the nomogram, which incorporated relevant CT features and the GPTV10-radscore, outperformed both the radiomics model and clinical model alone, with AUC values of 0.894, 0.828, and 0.876 in the three respective sets.ConclusionsThe nomogram, integrating radiomics features and CT morphological features, exhibits good performance in predicting VPI status in lung adenocarcinoma.

The Role of Emphysema on Postoperative Prognosis in Early-Stage Nonsmall Cell Lung Cancer

BackgroundEmphysema is generally considered a poor prognostic factor for patients with nonsmall cell lung cancer; however, whether the poor prognosis is due to highly malignant tumors or emphysema itself remains unclear. This study was designed to determine the prognostic value of emphysema in patients with early-stage nonsmall cell lung cancer.MethodsA total of 721 patients with clinical stage IA nonsmall cell lung cancer who underwent complete resection between April 2007 and December 2018 were retrospectively analyzed regarding clinicopathological findings and prognosis related to emphysema.ResultsThe emphysematous and normal lung groups comprised 197 and 524 patients, respectively. Compared with the normal lung group, lymphatic invasion (23.9% vs. 14.1%, P = 0.003), vascular invasion (37.6% vs. 17.2%, P < 0.001), and pleural invasion (18.8% vs. 10.9%, P = 0.006) were observed more frequently in the emphysema group. Additionally, the 5-year overall survival rate was lower (77.1% vs. 91.4%, P < 0.001), and the cumulative incidence of other causes of death was higher in the emphysema group (14.0% vs. 3.50%, P < 0.001). Multivariable Cox regression analysis of overall survival revealed that emphysema (vs. normal lung, hazard ratio 2.02, P = 0.0052), age > 70 years (vs. < 70 years, hazard ratio 4.03, P < 0.001), and SUVmax > 1.8 (vs. ≤ 1.8, hazard ratio 2.20, P = 0.0043) were independent prognostic factors.ConclusionsEarly-stage nonsmall cell lung cancer with emphysema has a tendency for the development of highly malignant tumors. Additionally, emphysema itself may have an impact on poor prognosis.

Postoperative pulmonary function of patients with lung cancer and interstitial lung abnormalities.

We investigated the impact of radiological interstitial lung abnormalities on the postoperative pulmonary functions of patients with non-small cell lung cancer. A total of 1191 patients with clinical stage IA non-small cell lung cancer who underwent lung resections and pulmonary function tests ≥ 6months postoperatively were retrospectively reviewed. Postoperative pulmonary function reduction rates were compared between patients with and without interstitial lung abnormalities and according to the radiological interstitial lung abnormality classifications. Surgical procedures were divided into wedge resection, 1-2 segment resection, and 3-5 segment resection groups. No significant differences in postoperative pulmonary function reduction rates 6months after wedge resection were observed between the interstitial lung abnormality [n = 202] and non-interstitial lung abnormality groups [n = 989] [vital capacity [VC]: 6.82% vs. 5.00%; forced expiratory volume in 1s [FEV1]: 7.05% vs. 7.14%]. After anatomical resection, these values were significantly lower in the interstitial lung abnormality group than in the non-interstitial lung abnormality group [VC: 1-2 segments, 12.50% vs. 9.93%; 3-5 segments, 17.42% vs. 14.23%; FEV1: 1-2 segments: 13.36% vs. 10.27%; 3-5 segments: 17.36% vs. 14.39%]. No significant differences in postoperative pulmonary function reduction rates according to the radiological interstitial lung abnormality classifications were observed. The presence of interstitial lung abnormalities had a minimal effect on postoperative pulmonary functions after wedge resections; however, pulmonary functions significantly worsened after segmentectomy or lobectomy, regardless of the radiological interstitial lung abnormality classification in early-stage non-small cell lung cancer.

Preoperatively predicting survival outcome for clinical stage IA pure-solid non–small cell lung cancer by radiomics-based machine learning

ObjectiveClinical stage IA non–small cell lung cancer (NSCLC) showing a pure-solid appearance on computed tomography is associated with a worse prognosis. This study aimed to develop and validate machine-learning models using preoperative clinical and radiomic features to predict overall survival (OS) in clinical stage IA pure-solid NSCLC. MethodsPatients who underwent lung resection for NSCLC between January 2012 and December 2020 were reviewed. The radiomic features were extracted from the intratumoral and peritumoral regions on computed tomography. The machine-learning models were developed using random survival forest and eXtreme Gradient Boosting (XGBoost) algorithms, whereas the Cox regression model was set as a benchmark. Model performance was assessed using the integrated time-dependent area under the curve (iAUC) and validated by 5-fold cross-validation. ResultsIn total, 642 patients with clinical stage IA pure-solid NSCLC were included. Among 3748 radiomic and 34 preoperative clinical features, 42 features were selected. Both machine-learning models outperformed the Cox regression model (iAUC, 0.753; 95% confidence interval [CI], 0.629-0.829). The XGBoost model showed a better performance (iAUC, 0.832; 95% CI, 0.779-0.880) than the random survival forest model (iAUC, 0.795; 95% CI, 0.734-0.856). The XGBoost model showed an excellent survival stratification performance with a significant OS difference among the low-risk (5-year OS, 100.0%), moderate low-risk (5-year OS, 88.5%), moderate high-risk (5-year OS, 75.6%), and high-risk (5-year OS, 41.7%) groups (P < .0001). ConclusionsA radiomics-based machine-learning model can preoperatively and accurately predict OS and improve survival stratification in clinical stage IA pure-solid NSCLC.

Limited resection is comparable to lobectomy for tumor size ≤ 2 cm pulmonary invasive mucinous adenocarcinoma

ObjectivesInvasive mucinous adenocarcinoma (IMA) has a rare incidence with better prognosis than nonmucinous adenocarcinoma. We aimed to investigate the prognosis between limited resection and lobectomy for patients with clinical stage IA IMA ≤ 2 cm.MethodsData were taken from two cohorts: In Shanghai Pulmonary Hospital (SPH) corhort, we identified 403 patients with clinical stage IA IMA who underwent surgery. In the SEER corhort, 480 patients with stage T1 IMA who after surgery were included. Recurrence-free survival (RFS) for SPH corhort, lung cancer–specific survival (LCSS) for the SEER corhort and overall survival (OS) for both corhort were compared between patients undergoing lobectomy and limited resection by Log-rank and Cox proportional hazard regression model.ResultsIn SPH corhort, patients who underwent limited resection had equivalent prognosis than those underwent lobectomy (5-year RFS: 79.3% versus. 82.6%, p = 0.116; 5-year OS: 86.2% versus. 88.3%, p = 0.235). However, patients with IMA > 2 to 3 cm had worse prognosis than those with IMA ≤ 2 cm (5-year RFS: 73.7% versus. 86.1%, p = 0.007). In the analysis of IMA > 2 to 3 cm subgroup, multivariate analysis showed that limited resection was an independent risk factor of RFS (hazard ratio, 2.417; 95% confidence interval, 1.157–5.049; p = 0.019), while OS (p = 0.122) was not significantly different between two groups. For IMA ≤ 2 cm, limited resection was not a risk factor of RFS (p = 0. 953) and OS (p = 0.552). In the SEER corhort, IMA ≤ 2 cm subgroup, limited resection was equivalent prognosis in LCSS (p = 0.703) and OS (p = 0.830).ConclusionsLimited resection could be a potential surgical option which comparable to lobectomy in patients with clinical stage IA IMA ≤ 2 cm.

No prognostic impact of staging bone scan in patients with stage IA non-small cell lung cancer.

To investigate the survival benefit of preoperative bone scan in asymptomatic patients with early-stage non-small cell lung cancer (NSCLC). This retrospective study included patients with radical resection for stage T1N0M0 NSCLC between March 2013 and December 2018. During postoperative follow-up, we monitored patient survival and the development of bone metastasis. We compared overall survival, bone metastasis-free survival, and recurrence-free survival in patients with or without preoperative bone scan. Propensity score matching and inverse probability of treatment weighting were used to minimize election bias. A total of 868 patients (58.19 ± 9.69years; 415 men) were included in the study. Of 87.7% (761 of 868) underwent preoperative bone scan. In the multivariable analyses, bone scan did not improve overall survival (hazard ratio [HR] 1.49; 95% confidence intervals [CI] 0.91-2.42; p = 0.113), bone metastasis-free survival (HR 1.18; 95% CI 0.73-1.90; p = 0.551), and recurrence-free survival (HR 0.89; 95% CI 0.58-1.39; p = 0.618). Similar results were obtained after propensity score matching (overall survival [HR 1.28; 95% CI 0.74-2.23; p = 0.379], bone metastasis-free survival [HR 1.00; 95% CI 0.58-1.72; p = 0.997], and recurrence-free survival [HR 0.76; 95% CI 0.46-1.24; p = 0.270]) and inverse probability of treatment weighting. There were no significant differences in overall survival, bone metastasis-free survival, and recurrence-free survival between asymptomatic patients with clinical stage IA NSCLC with or without preoperative bone scan.

Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography

PurposeThis study aims to assess the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUVmax) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC).MethodsA retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUVmax, and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set.ResultsSUVmax, consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUVmax and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing sets, respectively. Subgroup analysis revealed a 2.69 times higher STAS-positive rate in solid nodules compared to part-solid nodules. SUVmax was an independent predictor for predicting STAS in solid nodular NSCLC, while CTR and an emphysema background were independent predictors for STAS in part-solid nodular NSCLC.ConclusionOur nomogram based on preoperative 18F-FDG PET/CT radiological features and SUVmax effectively predicts STAS status in clinical-stage IA NSCLC. Furthermore, our study highlights that metabolic parameters and CT variables associated with STAS differ between solid and part-solid nodular NSCLC.

Clinical Utility of a CT-based AI Prognostic Model for Segmentectomy in Non-Small Cell Lung Cancer.

Background Currently, no tool exists for risk stratification in patients undergoing segmentectomy for non-small cell lung cancer (NSCLC). Purpose To develop and validate a deep learning (DL) prognostic model using preoperative CT scans and clinical and radiologic information for risk stratification in patients with clinical stage IA NSCLC undergoing segmentectomy. Materials and Methods In this single-center retrospective study, transfer learning of a pretrained model was performed for survival prediction in patients with clinical stage IA NSCLC who underwent lobectomy from January 2008 to March 2017. The internal set was divided into training, validation, and testing sets based on the assignments from the pretraining set. The model was tested on an independent test set of patients with clinical stage IA NSCLC who underwent segmentectomy from January 2010 to December 2017. Its prognostic performance was analyzed using the time-dependent area under the receiver operating characteristic curve (AUC), sensitivity, and specificity for freedom from recurrence (FFR) at 2 and 4 years and lung cancer-specific survival and overall survival at 4 and 6 years. The model sensitivity and specificity were compared with those of the Japan Clinical Oncology Group (JCOG) eligibility criteria for sublobar resection. Results The pretraining set included 1756 patients. Transfer learning was performed in an internal set of 730 patients (median age, 63 years [IQR, 56-70 years]; 366 male), and the segmentectomy test set included 222 patients (median age, 65 years [IQR, 58-71 years]; 114 male). The model performance for 2-year FFR was as follows: AUC, 0.86 (95% CI: 0.76, 0.96); sensitivity, 87.4% (7.17 of 8.21 patients; 95% CI: 59.4, 100); and specificity, 66.7% (136 of 204 patients; 95% CI: 60.2, 72.8). The model showed higher sensitivity for FFR than the JCOG criteria (87.4% vs 37.6% [3.08 of 8.21 patients], P = .02), with similar specificity. Conclusion The CT-based DL model identified patients at high risk among those with clinical stage IA NSCLC who underwent segmentectomy, outperforming the JCOG criteria. © RSNA, 2024 Supplemental material is available for this article.

An advanced nomogram model using deep learning radiomics and clinical data for predicting occult lymph node metastasis in lung adenocarcinoma

PurposeTo evaluate the effectiveness of deep learning radiomics nomogram in distinguishing the occult lymph node metastasis (OLNM) status in clinical stage IA lung adenocarcinoma. MethodsA cohort of 473 cases of lung adenocarcinomas from two hospitals was included, with 404 cases allocated to the training cohort and 69 cases to the testing cohort. Clinical characteristics and semantic features were collected, and radiomics features were extracted from the computed tomography (CT) images. Additionally, deep transfer learning (DTL) features were generated using RseNet50. Predictive models were developed using the logistic regression (LR) machine learning algorithm. Moreover, gene analysis was conducted on RNA sequencing data from 14 patients to explore the underlying biological basis of deep learning radiomics scores. ResultThe training and testing cohorts achieved AUC values of 0.826 and 0.775 for the clinical model, 0.865 and 0.801 for the radiomics model, 0.927 and 0.885 for the DTL-radiomics model, and 0.928 and 0.898 for the nomogram model. The nomogram model demonstrated superiority over the clinical model. The decision curve analysis (DCA) revealed a net benefit in predicting OLNM for all models. The investigation into the biological basis of deep learning radiomics scores identified an association between high scores and pathways related to tumor proliferation and immune cell infiltration in the microenvironment. ConclusionsThe nomogram model, incorporating clinical-semantic features, radiomics, and DTL features, exhibited promising performance in predicting OLNM. It has the potential to provide valuable information for non-invasive lymph node staging and individualized therapeutic approaches.