Which will carry more weight when CTR > 0.5, solid component size, CTR, tumor size or SUVmax?

Impact of FDG PET Standardized Uptake Value in Resected Clinical Stage IA Non-Small Cell Lung Cancer

BACKGROUND

A significant proportion of patients with clinical stage IA non-small cell lung cancer (NSCLC) experience will recurrence and decreased survival after surgery. This study examined the impact of preoperative primary tumor positron emission tomography (PET) scan maximum standardized uptake value (SUVmax) on oncologic outcomes after surgery.

METHODS

This was a retrospective review of 251 patients who underwent surgical treatment of clinical stage IA NSCLC at an academic medical center (2005-2014). Patients were classified according to PET SUVmax level (low vs high) for analysis of upstaging, tumor recurrence, and overall survival.

RESULTS

Median SUVmax values were higher in squamous cell carcinoma than in adenocarcinoma (median 3.3 vs 7.2; P < .0001). There were 109 (43.4%) patients in the SUVmax low group and 142 (56.6%) in the SUVmax high group. Patients with SUVmax high had larger tumors. SUVmax high was associated with higher rates of nodal upstaging (16.2% vs 4.6% in SUVmax low; P = .004), particularly in N1 nodes. SUVmax high was independently associated with nodal upstaging (adjusted odds ratio, 3.95; 95% CI, 1.36-11.46; P = .011). SUVmax high was associated with time to recurrence (hazard ratio, 1.62; 95% CI, 1.03-2.54; P = .036), but this association was lost on multivariable analysis (hazard ratio, 1.52; 95% CI, 0.91-2.54; P = .106). SUVmax was not associated with overall survival.

CONCLUSIONS

Preoperative PET SUVmax level is strongly associated with nodal upstaging, particularly in N1 nodes, in patients with clinical stage IA NSCLC who undergo resection. PET SUVmax should be regarded as a risk factor when considering candidacy for sublobar resections and in future trials involving patients with stage I NSCLC.

Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma

OBJECTIVES

To develop and validate a machine learning model using 18F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma.

METHODS

Eight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocarcinoma were enrolled. After segmentation, 1688 radiomics features were extracted from PET/CT and selected to construct predictive models. Then, we developed a nomogram based on PET/CT radiomics integrated with clinical features. Receiver operating curves, calibration curves, and decision curve analysis (DCA) were performed for diagnostics assessment and test of the developed models for distinguishing patients with MP/S components from the patients without.

RESULTS

PET/CT radiomics-clinical combined model could well distinguish patients with MP/S components from those without MP/S components (AUC = 0.87), which performed better than PET (AUC = 0.829, p < 0.05) or CT (AUC = 0.827, p < 0.05) radiomics models in the training cohort. In test cohorts, radiomics-clinical combined model outperformed the PET radiomics model in test cohort 1 (AUC = 0.859 vs 0.799, p < 0.05) and the CT radiomics model in test cohort 2 (AUC = 0.880 vs 0.829, p < 0.05). Calibration curve indicated good coherence between all model prediction and the actual observation in training and test cohorts. DCA revealed PET/CT radiomics-clinical model exerted the highest clinical benefit.

CONCLUSION

18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of MP/S components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies. The PET/CT radiomics-clinical combined model performed best. CRITICAL RELEVANCE STATEMENT: 18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of micropapillary and solid components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies.

A Multi-institutional Analysis of the Combined Effect of Micropapillary Component and Consolidation-to-Tumor Ratio >0.5 on the Prognosis of Pathological, Stage IA3, Lung Adenocarcinoma

INTRODUCTION

The study investigated the synergistic effect of the micropapillary (MIP) component and consolidation-to-tumor ratio (CTR) on the recurrence and survival of patients with pathologic stage IA3 lung adenocarcinoma.

METHODS

We enrolled 419 patients confirmed pathological stage IA3 adenocarcinoma from four institutions. Kaplan-Meier analysis was performed to examine the value of the MIP component and CTR on relapse-free survival (RFS) and overall survival (OS). The cumulative recurrence between different stages was analyzed by using cumulative event curves.

RESULTS

RFS (P < 0.0001) and OS (P = 0.008) in the presence of the MIP group were significantly lower than those in the absence of the MIP group, and CTR > 5 only reduced RFS (P = 0.0004), but not OS (P = 0.063), in the patients. In addition, the prognosis of patients with both the MIP component and CTR > 5 was worse than that of those without the MIP component or CTR ≤ 5. Therefore, we established new subtypes of the stage IA3: IA3a, IA3b, and IA3c. RFS and OS for IA3c staging were significantly lower than those for IA3a and IA3b. For IA3c, the cumulative incidence of local recurrence (P < 0.001) and that of distant metastasis (P = 0.004) were significantly higher than those for IA3a and IA3b.

CONCLUSIONS

The MIP component combined with CTR > 0.5 can effectively predict the prognosis of patients with pathological stage IA3 lung adenocarcinoma and may offer more detailed recurrence and survival information according to the established subtype stage of IA3.