Incidence rate of occult lymph node metastasis in clinical T1-2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research.

BACKGROUND: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data. METHODS: By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV). RESULTS: The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients. CONCLUSIONS: The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

Effectiveness of CT radiomic features combined with clinical factors in predicting prognosis in patients with limited-stage small cell lung cancer.

BACKGROUND: The prognosis of SCLC is poor and difficult to predict. The aim of this study was to explore whether a model based on radiomics and clinical features could predict the prognosis of patients with limited-stage small cell lung cancer (LS-SCLC). METHODS: Simulated positioning CT images and clinical features were retrospectively collected from 200 patients with histological diagnosis of LS-SCLC admitted between 2013 and 2021, which were randomly divided into the training (n = 140) and testing (n = 60) groups. Radiomics features were extracted from simulated positioning CT images, and the t-test and the least absolute shrinkage and selection operator (LASSO) were used to screen radiomics features. We then constructed radiomic score (RadScore) based on the filtered radiomics features. Clinical factors were analyzed using the Kaplan-Meier method. The Cox proportional hazards model was used for further analyses of possible prognostic features and clinical factors to build three models including a radiomic model, a clinical model, and a combined model including clinical factors and RadScore. When a model has prognostic predictive value (AUC > 0.7) in both train and test groups, a nomogram will be created. The performance of three models was evaluated using area under the receiver operating characteristic curve (AUC) and Kaplan-Meier analysis. RESULTS: A total of 1037 features were extracted from simulated positioning CT images which were contrast enhanced CT of the chest. The combined model showed the best prediction, with very poor AUC for the radiomic model and the clinical model. The combined model of OS included 4 clinical features and RadScore, with AUCs of 0.71 and 0.70 in the training and test groups. The combined model of PFS included 4 clinical features and RadScore, with AUCs of 0.72 and 0.71 in the training and test groups. T stages, ProGRP and smoke status were the independent variables for OS in the combined model, whereas T stages, ProGRP and prophylactic cranial irradiation (PCI) were the independent factors for PFS. There was a statistically significant difference between the low- and high-risk groups in the combined model of OS (training group, p < 0.0001; testing group, p = 0.0269) and PFS (training group, p < 0.0001; testing group, p < 0.0001). CONCLUSION: Combined models involved RadScore and clinical factors can predict prognosis in LS-SCLC and show better performance than individual radiomics and clinical models.

Rational and design of prophylactic cranial irradiation (PCI) and brain MRI surveillance versus brain MRI surveillance alone in patients with limited-stage small cell lung cancer achieving complete remission (CR) of tumor after chemoradiotherapy: a multicenter prospective randomized study.

BACKGROUND: Prophylactic cranial irradiation (PCI) is part of standard care in limited-stage small cell lung cancer (SCLC) at present. As evidence from retrospective studies increases, the benefits of PCI for limited-stage SCLC are being challenged. METHODS: A multicenter, prospective, randomized controlled study was designed. The key inclusion criteria were: histologically or cytologically confirmed small cell carcinoma, age ≥ 18 years, KPS ≥ 80, limited-stage is defined as tumor confined to one side of the chest including ipsilateral hilar, bilateral mediastinum and supraclavicular lymph nodes, patients have received definitive thoracic radiotherapy (regardless of the dose-fractionation of radiotherapy used) and chemotherapy, evaluated as complete remission (CR) of tumor 4-6 weeks after the completion of chemo-radiotherapy. Eligible patients will be randomly assigned to two arms: (1) PCI and brain MRI surveillance arm, receiving PCI (2.5 Gy qd to a total dose of 25 Gy in two weeks) followed by brain MRI surveillance once every three months for two years; (2) brain MRI surveillance alone arm, undergoing brain MRI surveillance once every three months for two years. The primary objective is to compare the 2-year brain metastasis-free survival (BMFS) rates between the two arms. Secondary objectives include 2-year overall survival (OS) rates, intra-cranial failure patterns, 2-year progression-free survival rates and neurotoxicity. In case of brain metastasis (BM) detect during follow-up, stereotactic radiosurgery (SRS) will be recommended if patients meet the eligibility criteria. DISCUSSION: Based on our post-hoc analysis of a prospective study, we hypothesize that in limited-stage SCLC patients with CR after definitive chemoradiotherapy, and ruling out of BM by MRI, it would be feasible to use brain MRI surveillance and omit PCI in these patients. If BM is detected during follow-up, treatment with SRS or whole brain radiotherapy does not appear to have a detrimental effect on OS. Additionally, this approach may reduce potential neurotoxicity associated with PCI.

Evaluating CD133 as a Radiotheranostic Target in Small-Cell Lung Cancer.

Despite decades of work, small-cell lung cancer (SCLC) remains a frustratingly recalcitrant disease. Both diagnosis and treatment are challenges: low-dose computed tomography (the approved method used for lung cancer screening) is unable to reliably detect early SCLC, and the malignancy's 5 year survival rate stands at a paltry 7%. Clearly, the development of novel diagnostic and therapeutic tools for SCLC is an urgent, unmet need. CD133 is a transmembrane protein that is expressed at low levels in normal tissue but is overexpressed by a variety of tumors, including SCLC. We previously explored CD133 as a biomarker for a novel autoantibody-to-immunopositron emission tomography (PET) strategy for the diagnosis of SCLC, work that first suggested the promise of the antigen as a radiotheranostic target in the disease. Herein, we report the in vivo validation of a pair of CD133-targeted radioimmunoconjugates for the PET imaging and radioimmunotherapy of SCLC. To this end, [89Zr]Zr-DFO-αCD133 was first interrogated in a trio of advanced murine models of SCLC─i.e., orthotopic, metastatic, and patient-derived xenografts─with the PET probe consistently producing high activity concentrations (>%ID/g) in tumor lesions combined with low uptake in healthy tissues. Subsequently, a variant of αCD133 labeled with the ß-emitting radiometal 177Lu─[177Lu]Lu-DTPA-A″-CHX-αCD133─was synthesized and evaluated in a longitudinal therapy study in a subcutaneous xenograft model of SCLC, ultimately revealing that treatment with a dose of 9.6 MBq of the radioimmunoconjugate produced a significant increase in median survival compared to a control cohort. Taken together, these data establish CD133 as a viable target for the nuclear imaging and radiopharmaceutical therapy of SCLC.

Synchronous double primary small cell lung cancer and invasive ductal breast carcinoma: a case report.

BACKGROUND: Although lung and breast cancers are common malignancies, the occurrence of primary synchronous neoplasms involving these organs has been rarely reported in literature. CASE PRESENTATION: A 75-year-old female patient presented at a local hospital with a ten-day history of dizziness and slurred speech. A CT contrast-enhanced scan revealed a 4.2 cm mass in the lower lobe of the right lung and a 3.8 cm space-occupying lesion in the right breast. Subsequent breast ultrasound identified a hypoechoic lesion measuring5.41 × 4.75 × 3.06 cm in the right breast, and an ultrasound-guided biopsy confirmed the presence of infiltrating ductal carcinoma of the right breast. The immunohistochemistry analysis of the breast mass revealed positive staining for ER, PR, HER-2, AR and Ki67 in the tumor cells, while negative staining was observed for P63, Calponin, CK5/6 and CK14. MR imaging of the head detected abnormal signals in the right frontal lobe (3.6 cm×2.9 cm in size), left cerebellar hemisphere, and punctate enhancement in the left temporal lobe, indicating potential metastasis. Pathological examination of a lung biopsy specimen confirmed the presence of small cell lung cancer (SCLC). Furthermore, immunohistochemistry analysis of the lung lesions demonstrated positive staining for TTF-1, CK-Pan, Syn, CgA, CD56, P53 (90%) and Ki67 (70%), and negative staining for NapsinA and P40 in the tumor cells. The patient's diagnosis of SCLC with stage cT2bN0M1c IVB and brain metastases (BM), as well as invasive ductal breast carcinoma (IDC), was confirmed based on the aforementioned results. Whereupon we proposed a treatment plan consisting of whole-brain radiation (40 Gy/20fractions), focal radiotherapy (60 Gy/20fractions), and adjuvant concurrent chemotherapy with oral etoposide (50 mg on days 1 to 20). CONCLUSIONS: To the best of our knowledge, the present case is the first of its kind to describe the synchronous double cancer, consisting of primary SCLC and IDC.

Brain metastases from small cell lung cancer and non-small cell lung cancer: comparison of spatial distribution and identification of metastatic risk regions.

PURPOSE: This study aims to investigate the spatial distribution difference of brain metastases (BM) between small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) and to identify the metastatic risk in brain regions. METHODS: T1-enhanced MR images of 2997 BM from 728 eligible patients with SCLC and NSCLC were retrospectively reviewed by three independent medical institutions in China. All images were spatially normalised according to the Montreal Neurological Institute space, following BM delineation confirmed by three senior radiologists. The brain regions in the normalised images were identified based on the merged Anatomical Automatic Labeling atlas, and all BM locations were mapped onto these brain regions. Two-tailed proportional hypothesis testing was used to compare the BM observed rate with the expected rate based on the region's volume, and metastatic risk regions were finally identified. RESULTS: In SCLC and NSCLC, BM was mainly present in the deep white matter (22.51% and 17.96%, respectively), cerebellar hemisphere (9.84% and 7.46%, respectively) and middle frontal gyrus (6.72% and 7.97%, respectively). The cerebellar hemisphere was a high-risk brain region in the SCLC. The precentral gyrus, middle frontal gyrus, paracentral lobule and cerebellar hemisphere were high-risk BM in the NSCLC. The inferior frontal gyrus and the temporal pole were a low-risk brain region in the SCLC and NSCLC, respectively. CONCLUSION: The spatial BM distribution between SCLC and NSCLC is similar. Several critical brain regions had relatively low BM frequency in both SCLC and NSCLC, where a low-dose radiation distribution can be delivered due to adequate preoperative evaluations.

Survival benefit of prophylactic cranial irradiation in limited-stage small-cell lung cancer in modern magnetic resonance imaging staging: a systematic review and meta-analysis.

BACKGROUND: The use of prophylactic cranial irradiation (PCI) in patients suffering from limited-stage small-cell lung cancer (LS-SCLC) remains controversial in modern brain magnetic resonance imaging (MRI) staging. To this end, a systematic review with meta-analysis was hereby performed to investigate the overall survival (OS) in these patients. METHODS: Relevant studies from the PubMed and EMBASE databases were reviewed, and pooled hazard risks were obtained using fixed-effects models. The PRISMA 2020 checklist was used. RESULTS: Fifteen retrospective studies were identified, with a total of 2,797 patients with LS-SCLC included in the analysis, 1,391 of which had received PCI. For all included patients, PCI was associated with improved OS [hazard ratio (HR): 0.64, 95% confidence interval (CI): 0.58-0.70]. The combination of subgroup analysis and sensitivity analysis suggested that the effect of PCI on OS was independent of primary tumor treatment, proportion of complete response (CR), median age, PCI dose, publication years, etc. Additionally, the OS curve of 1,588 patients having undergone thoracic radiotherapy (TRT) as the primary tumor treatment from 8 studies were reconstructed, and the pooled 2-, 3- and 5-year OS rates of limited stage patients were 59% vs. 42%, 42% vs. 29% and 26% vs. 19% (HR: 0.69, 95% CI: 0.61-0.77) in the PCI group and the no PCI group, respectively. Another reconstructed OS curve of 339 patients having undergone radical surgery as the primary tumor treatment from 2 studies presented better results, and the pooled 2-, 3- and 5-year OS rates of in the PCI group and the no PCI group were 85% vs. 71%, 70% vs. 56% and 52% vs. 39% (HR: 0.59, 95% CI: 0.40-0.87), respectively. CONCLUSIONS: This meta-analysis demonstrates a significant beneficial effect of PCI on the OS in patients with LS-SCLC in modern pretreatment MRI staging. However, considering the absence of a strict follow-up of brain MRI recommended by the guideline for the control group from most of the included studies, the superiority of PCI to the treatment strategy of no PCI plus brain MRI surveillance remains unclear.

When chronic obstructive pulmonary disease meets small cell lung cancer: an unusual case report of rapid progression.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease and a risk factor for lung cancer. Small cell lung cancer is a neuroendocrine tumor with a high degree of malignancy and an overall five-year survival rate of less than 7%. CASES PRESENTATION: Herein, we report the case of an 68-year-old male presented to the respiratory department with cough, sputum, and dyspnea. He was diagnosed as community acquired pneumonia and treated with intravenous anti-infection. Previous pulmonary function was definitively diagnosed as COPD. About 7 months after discharge, the patient returned to the hospital for cough and dyspnea. After diagnosis of the tumor, cisplatin, etoposide and durvalumab were administered. Finally the patient died of respiratory failure approximately 9 months after his diagnosis. CONCLUSIONS: For COPD patients with immunocompromised manifestations, it is necessary to be alert to complications and shorten the follow-up interval of chest CT. COPD may accelerate the formation and progression of SCLC.

Significance of marginal vessels in differentiating peripheral small-cell lung cancer and benign lung tumor.

BACKGROUND: Some peripheral small cell lung cancers (pSCLCs) and benign lung tumors (pBLTs) have similar morphological features but different treatment and prognosis. PURPOSE: To determine the significance of marginal vessels in differentiating pSCLCs and pBLTs. MATERIAL AND METHODS: A total of 57 and 95 patients with pathological confirmed nodular (≤3 cm) pSCLC and pBLT with similar morphological features were enrolled in this study retrospectively. The patients' clinical characteristics and computed tomography (CT) features of tumors and marginal vessels (vessels connecting with tumors) were analyzed and compared. RESULTS: Compared with pBLTs, pSCLCs had a larger diameter (P = 0.001) but lower enhancement (P = 0.015) and fewer had calcification (P = 0.013). Compared with pBLTs, more lesions had proximal (70.2% vs. 22.1%) and distal (59.6% vs. 4.2%) marginal vessels in pSCLCs (each P < 0.0001). In addition, in pSCLCs, the numbers of proximal (1.3 ± 1.4 vs. 0.3 ± 0.6), distal (2.4 ± 3.1 vs. 0.1 ± 0.5), and total (3.6 ± 3.5 vs. 0.4 ± 1.0) marginal vessels were all more than those in pBLTs (each P < 0.001). Receiver operating characteristic curve analysis revealed the positive distal marginal vessel sign had the highest specificity (95.8%), and the number of total marginal vessels had the best performance in discriminating pSCLC from pBLT (cutoff value = 1.5, AUC = 0.80, 95% CI = 0.72-0.89, sensitivity = 70.2%, and specificity = 91.6%). CONCLUSION: For peripheral solid nodules similar to pBLTs but without any calcification, the possibility of pSCLC should be considered if they have multiple marginal vessels (≥2), especially the distal ones.

Contribution of F-18 fluorodeoxyglucose PET/CT and contrast-enhanced thoracic CT texture analyses to the differentiation of benign and malignant mediastinal lymph nodes.

BACKGROUND: Texture analysis and machine learning methods are useful in distinguishing between benign and malignant tissues. PURPOSE: To discriminate benign from malignant or metastatic mediastinal lymph nodes using F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and contrast-enhanced computed tomography (CT) texture analyses with machine learning and determine lung cancer subtypes based on the analysis of lymph nodes. MATERIAL AND METHODS: Suitable texture features were entered into the algorithms. Features that statistically significantly differed between the lymph nodes with small cell lung cancer (SCLC), adenocarcinoma (ADC), and squamous cell carcinoma (SCC) were determined. RESULTS: The most successful algorithms were decision tree with the sensitivity, specificity, and area under the curve (AUC) values of 89%, 50%, and 0.692, respectively, and naive Bayes (NB) with the sensitivity, specificity, and AUC values of 50%, 81%, and 0.756, respectively, for PET/CT, and NB with the sensitivity, specificity, and AUC values of 10%, 96%, and 0.515, respectively, and logistic regression with the sensitivity, specificity, and AUC values of 21%, 83%, and 0.631, respectively, for CT. In total, 13 features were able to differentiate SCLC and ADC, two features SCLC and SCC, and 33 features ADC and SCC lymph node metastases in PET/CT. One feature differed between SCLC and ADC metastases in CT. CONCLUSION: Texture analysis is beneficial to discriminate between benign and malignant lymph nodes and differentiate lung cancer subtypes based on the analysis of lymph nodes.

A CT-based radiomics nomogram for predicting the progression-free survival in small cell lung cancer: a multicenter cohort study.

PURPOSE: To develop a radiomics nomogram based on computed tomography (CT) to estimate progression-free survival (PFS) in patients with small cell lung cancer (SCLC) and assess its incremental value to the clinical risk factors for individual PFS estimation. METHODS: 558 patients with pathologically confirmed SCLC were retrospectively recruited from three medical centers. A radiomics signature was generated by using the Pearson correlation analysis, univariate Cox analysis, and multivariate Cox analysis. Association of the radiomics signature with PFS was evaluated. A radiomics nomogram was developed based on the radiomics signature, then its calibration, discrimination, reclassification, and clinical usefulness were evaluated. RESULTS: In total, 6 CT radiomics features were finally selected. The radiomics signature was significantly associated with PFS (hazard ratio [HR] 4.531, 95% confidence interval [CI] 3.524-5.825, p < 0.001). Incorporating the radiomics signature into the radiomics nomogram resulted in better performance for the estimation of PFS (concordance index [C-index] 0.799) than with the clinical nomogram (C-index 0.629), as well as high 6 months and 12 months area under the curves of 0.885 and 0.846, respectively. Furthermore, the radiomics nomogram also significantly improved the classification accuracy for PFS outcomes, based on the net reclassification improvement (33.7%, 95% CI 0.216-0.609, p < 0.05) and integrated discrimination improvement (22.7%, 95% CI 0.168-0.278, p < 0.05). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the clinical nomogram. CONCLUSION: A CT-based radiomics nomogram exhibited a promising performance for predicting PFS in patients with SCLC, which could provide valuable information for individualized treatment.

Prognostic value of metabolic parameters on baseline 18F-FDG PET/CT in small cell lung cancer.

BACKGROUND: Maximum standardized uptake value (SUVmax) is the primary quantitave parameter given in 18F-FDG PET/CT reports. Calculations derived from three dimensional metabolic volumetric images have been proposed to be more successful than SUVmax alone in prognostification with a lower interobserver variability in many cancers. We aimed to determine the prognostic value of metabolic parameters derived from 18F-FDG PET/CT studies in small cell lung cancer (SCLC) patient population with a long follow-up time. METHODS: In this study, 38 consecutive SCLC patients (34M, 4F, age:65.76 ±8.18 years) who were referred to 18F-FDG PET/CT for staging between October 2006-January 2011 were included. SUVmax, SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Overall survival (OS) was calculated from the date of the initial PET/CT to death from any cause. Survival tables were obtained and Kaplan Meier curves were reconstructed. Mantel-Cox regression analysis was performed in order to investigate if any of these parameters have an effect on survival along with other clinical risk factors. RESULTS: Median SUVmax, SUVmean, SUVpeak, MTV, TLG and LDH values were calculated as 13.9 g/dL, 6.4 g/dL,10.69 g/dL, 147 cm3, 1898.52 and 375U/L respectively. Median follow-up was 761.23±873.21 days (25.37 months, range:110-3338 days). Since basal 18F-FDG PET/CT scans, all patients were lost in the follow-up except for two patients. MTV was a significant prognostic factor in SCLC patients. Estimated mean survival times were 261.0±45.6 (95% CI: 171.6-350.3) days in patients with MTV value above the calculated median 147, and 577.0±124.0 (95% CI: 333.7-820.2) days in patients with MTV<147. The difference was statistically significant with a P=0.037. CONCLUSIONS: Baseline whole body MTV reflecting total tumor load is a prognostic index in SCLC. SUV is insufficient to predict prognosis.

Small Cell Lung Cancer Staging: Prospective Comparison of Conventional Staging Tests, FDG PET/CT, Whole-Body MRI, and Coregistered FDG PET/MRI.

BACKGROUND. Whole-body MRI and FDG PET/MRI have shown encouraging results for staging of thoracic malignancy but are poorly studied for staging of small cell lung cancer (SCLC). OBJECTIVE. The purpose of our study was to compare the performance of conventional staging tests, FDG PET/CT, whole-body MRI, and FDG PET/MRI for staging of SCLC. METHODS. This prospective study included 98 patients (64 men, 34 women; median age, 74 years) with SCLC who underwent conventional staging tests (brain MRI; neck, chest, and abdominopelvic CT; and bone scintigraphy), FDG PET/CT, and whole-body MRI within 2 weeks before treatment; coregistered FDG PET/MRI was generated. Two nuclear medicine physicians independently reviewed conventional tests and FDG PET/CT examinations in separate sessions, and two chest radiologists independently reviewed whole-body MRI and FDG PET/MRI examinations in separate sessions. Readers assessed T, N, and M categories; TNM stage; and Veterans Administration Lung Cancer Study Group (VALSG) stage. Reader pairs subsequently reached consensus. Stages determined clinically during tumor board sessions served as the reference standard. RESULTS. Accuracy for T category was higher (p < .05) for whole-body MRI (94.9%) and FDG PET/MRI (94.9%) than for FDG PET/CT (85.7%). Accuracy for N category was higher (p < .05) for whole-body MRI (84.7%), FDG PET/MRI (83.7%), and FDG PET/CT (81.6%) than for conventional staging tests (75.5%). Accuracy for M category was higher (p < .05) for whole-body MRI (94.9%), FDG PET/MRI (94.9%), and FDG PET/CT (94.9%) than for conventional staging tests (84.7%). Accuracy for TNM stage was higher (p < .05) for whole-body MRI (88.8%) and FDG PET/MRI (86.7%) than for FDG PET/CT (77.6%) and conventional staging tests (72.4%). Accuracy for VALSG stage was higher (p < .05) for whole-body MRI (95.9%), FDG PET/MRI (95.9%), and FDG PET/CT (98.0%) than for conventional staging tests (82.7%). Interobserver agreement, expressed as kappa coefficients, ranged from 0.81 to 0.94 across imaging tests and staging endpoints. CONCLUSION. FDG PET/CT, whole-body MRI, and coregistered FDG PET/MRI outperformed conventional tests for various staging endpoints in patients with SCLC. Whole-body MRI and FDG PET/MRI outperformed FDG PET/CT for T category and thus TNM stage, indicating the utility of MRI for assessing extent of local invasion in SCLC. CLINICAL IMPACT. Incorporation of either MRI approach may improve initial staging evaluation in SCLC.

Outcomes of prophylactic cranial irradiation in patients with small cell lung cancer in the modern era of baseline magnetic resonance imaging of the brain.

BACKGROUND: For decades many patients with small cell lung cancer (SCLC) have been offered prophylactic cranial irradiation (PCI) to prevent brain metastases (BM). However, the role of PCI is debated in the modern era of increased brain magnetic resonance imaging (MRI) availability. BM in SCLC patients may respond to chemotherapy, and if a negative MRI is used in the decision to use of PCI in the treatment strategy, the timing of brain MRI may be crucial when evaluating the effect of PCI. This retrospective study investigates the impact of PCI outcomes in patients with SCLC staged with brain MRI prior to chemotherapy. MATERIALS AND METHODS: This study included 245 patients diagnosed SCLC/mixed NSCLC-SCLC treated between 2012 and 2019. The population was analyzed separately for limited disease (LS-SCLC) and extensive disease (ES-SCLC). Patients were divided into groups based on baseline brain MRI prior to chemotherapy and PCI. The primary endpoint was time to symptomatic BM. Secondary endpoints were overall survival (OS), and progression-free survival (PFS). RESULTS: In patients with LS-SCLC staged with brain MRI the probability of developing symptomatic BM at one year was 4% vs. 22% (p < 0.05), median OS was 55 vs. 24 months (p < 0.05), and median PFS was 30 vs. 10 months (p < 0.05) with and without PCI, respectively. No differences in probability of symptomatic BM and survival outcomes were observed in ES-SCLC. In a multivariate regression analysis, no variables were statistically significant associated with the risk of developing symptomatic BM in patients with LS-SCLC and ES-SCLC. For patients with ES-SCLC staged with brain MRI, PS (HR = 3.33, CI; 1.41-7.89, p < 0.05) was associated with poor survival. CONCLUSION: This study found that PCI in LS-SCLC patients staged with brain MRI had lower incidence of symptomatic BM and improved survival outcomes suggesting PCI as standard of care. Similar benefit of PCI in patients with ES-SCLC was not found.

A Comparative Analysis of White Matter Structural Networks on SCLC Patients After Chemotherapy.

Previous sMRI, DTI and rs-fMRI studies in small cell lung cancer (SCLC) patients have reported that patients after chemotherapy had gray and white matter structural alterations along with functional deficits. Nonetheless, few are known regarding the potential alterations in the topological organization of the WM structural network in SCLC patients after chemotherapy. In this context, the scope of the present study is to evaluate the WM structural network of 20 SCLC patients after chemotherapy and to 14 healthy controls, by applying a combination of DTI with graph theory. The results revealed that both SCLC and healthy controls groups demonstrated small world properties. The SCLC patients had decreased values in the clustering coefficient, local efficiency and degree metrics as well as increased shortest path length when compared to the healthy controls. Moreover, the two groups reported different topological reorganization of hub distribution. Lastly, the SCLC patients exhibited significantly decreased structural connectivity in comparison to the healthy group. These results underline that the topological organization of the WM structural network in SCLC patients was disrupted and hence constitute new vital information regarding the effects that chemotherapy and cancer may have in the patients' brain at network level.

MRI-based radiomics analysis in differentiating solid non-small-cell from small-cell lung carcinoma: a pilot study.

AIM: To investigate the ability of a T2-weighted (W) magnetic resonance imaging (MRI)-based radiomics signature to differentiate solid non-small-cell lung carcinoma (NSCLC) from small-cell lung carcinoma (SCLC). MATERIALS AND METHODS: The present retrospective study enrolled 152 eligible patients (NSCLC = 125, SCLC = 27). All patients underwent MRI using a 3 T scanner and radiomics features were extracted from T2W MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression model was used to identify the optimal radiomics features for the construction of a radiomics model to differentiate solid NSCLC from SCLC. Threefold cross validation repeated 10 times was used for model training and evaluation. The conventional MRI morphology features of the lesions were also evaluated. The performance of the conventional MRI morphological features, and the radiomics signature model and nomogram model (combining radiomics signature with conventional MRI morphological features) was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: Five optimal features were chosen to build a radiomics signature. There was no significant difference in age, gender, and the largest diameter. The radiomics signature and conventional MRI morphological features (only pleural indentation and lymph node enlargement) were independent predictive factors for differentiating solid NSCLC from SCLC. The area under the ROC curves (AUCs) for MRI morphological features, and the radiomics model, and nomogram model was 0.69, 0.85, and 0.90 (ROC), respectively. CONCLUSIONS: The T2W MRI-based radiomics signature is a potential non-invasive approach for distinguishing solid NSCLC from SCLC.

[Survival analysis of unexpected small cell lung cancer following surgery].

Objective: To investigate the survival and influencing factors of unexpected small cell lung cancer following surgery. Methods: We respectively reviewed the clinical characters of 104 patients who underwent surgical treatment and be proved as small cell lung cancer by pathology between January 2000 to October 2020 in Chinese PLA General Hospital. Overall survival (OS) of patients was evaluated using Kaplan-Meier and Cox proportional hazards analysis. Results: Of 104 patients, 27 cases showed central lesions, and other 77 showed peripheral nodules. The margin of nodules was smooth in 42 cases on CT imaging. The median OS was 34.3 months and 5-year OS rate was 45.8%. Postoperative 5-year OS rates for patients were 52.1%, 45.4%, and 27.8% for clinical stages Ⅰ, Ⅱ, and Ⅲ, respectively. Univariate analyses identified the age, surgical access, surgical approach, N stage, TNM stage and vascular cancer emboli were associated with OS (P<0.05). The N stage was an independent factor for the OS of patients (P<0.05). Conclusions: Patients with unexpected SCLC, including Ⅰ, Ⅱ and part ⅢA stage have favorable outcome and can benefit from surgery and systemic postoperative treatment. Standard lobectomy plus systemic lymph node dissection is commended.

Paraneoplastic sensorimotor neuropathy and ventral cauda equina nerve root enhancement as initial presentation of small cell lung carcinoma: a case study.

BACKGROUND: Paraneoplastic neurologic syndromes (PNS) are rare, however, are important to recognize as oftentimes they precede the detection of an occult malignancy. Our case highlights a rare circumstance of paraneoplastic radiculoneuropathy and the importance of recognizing PNS in antibody negative disease, as is the case in up to 16% of sensory neuronopathies, and the process of excluding other etiologies. CASE PRESENTATION: We discuss a 51-year-old man who presented with asymmetric subacute sensorimotor deficits in the lower limbs. Initial clinical examination showed weakness throughout the right lower limb and normal strength on the left with objective numbness in a mixed dermatomal and stocking-glove distribution. Electrophysiology was consistent with axonal sensorimotor neuropathy. Cerebrospinal fluid showed pleocytosis and elevated protein. Intravenous immunoglobulin treatment was given with some improvement in pain symptoms but no measurable motor improvement. Following clinical and electrophysiologic deterioration the patient was transferred to a tertiary centre. Magnetic resonance imaging of the spine showed smooth enhancement of the ventral caudal nerve roots. Chest computed tomography revealed left lower vascular scarring. Further positron emission tomography scan imaging identified fluorodeoxyglucose avid right lung lymphadenopathy. Bronchoscopy-guided biopsy revealed small cell lung carcinoma. Onconeural and antiganglioside antibodies were negative. The patient was then transferred to a medical oncology ward where he underwent chemoradiotherapy and subsequently experienced improvement in his motor function, supporting that his neurological condition was indeed secondary to a paraneoplastic process. CONCLUSIONS: Onconeural negative paraneoplastic radiculoneuropathy can precede diagnosis of small cell lung carcinoma. If considered early and adequately investigated, it can allow earlier diagnosis and treatment of underlying malignancy, improving overall and neurological prognosis.

Differentiation of brain metastases from small and non-small lung cancers using apparent diffusion coefficient (ADC) maps.

BACKGROUND: Brain metastases are particularly common in patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC showing a less  aggressive clinical course and lower chemo- and radio sensitivity compared to SCLC. Early adequate therapy is highly desirable and depends on a reliable classification of tumor type. The apparent diffusion coefficient is a noninvasive neuroimaging marker with the potential to differentiate between major histological subtypes. Here we determine the sensitivity and specificity of the apparent diffusion coefficient to distinguish between NSCLC and SCLC. METHODS: We enrolled all NSCLC and SCLC patients diagnosed between 2008 and 2019 at the University Medical Center Göttingen. Cranial MR scans were visually inspected for brain metastases and the ratio of the apparent diffusion coefficient (ADC) was calculated by dividing the ADC measured within the solid part of a metastasis by a reference ADC extracted from an equivalent region in unaffected tissue on the contralateral hemisphere. RESULTS: Out of 411 enrolled patients, we detected 129 patients (83 NSCLC, 46 SCLC) with sufficiently large brain metastases with histologically classified lung cancer and no hemorrhage. We analyzed 185 brain metastases, 84 of SCLC and 101 of NSCLC. SCLC brain metastases showed an ADC ratio of 0.68 ± 0.12 SD, and NSCLC brain metastases showed an ADC ratio of 1.47 ± 0.31 SD. Receiver operating curve statistics differentiated brain metastases of NSCLC from SCLC with an area under the curve of 0.99 and a 95% CI of 0.98 to 1, p < 0.001. Youden's J cut-point is 0.97 at a sensitivity of 0.989 and a specificity of 0.988. CONCLUSIONS: In patients with lung cancer and brain metastases with solid tumor parts, ADC ratio enables an ad hoc differentiation of SCLC and NSCLC, easily achieved during routine neuroradiological examination. Non-invasive MR imaging enables an early-individualized management of brain metastases from lung cancer. TRIAL REGISTRATION: The study was registered in the German Clinical Trials Register (DRKS00023016).

Correlation between quantitative perfusion histogram parameters of DCE-MRI and PTEN, P-Akt and m-TOR in different pathological types of lung cancer.

BACKGROUND: To explore if the quantitative perfusion histogram parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlates with the expression of PTEN, P-Akt and m-TOR protein in lung cancer. METHODS: Thirty-three patients with 33 lesions who had been diagnosed with lung cancer were enrolled in this study. They were divided into three groups: squamous cell carcinoma (SCC, 15 cases), adenocarcinoma (AC, 12 cases) and small cell lung cancer (SCLC, 6 cases). Preoperative imaging (conventional imaging and DCE-MRI) was performed on all patients. The Exchange model was used to measure the phar- macokinetic parameters, including Ktrans, Vp, Kep, Ve and Fp, and then the histogram parameters meanvalue, skewness, kurtosis, uniformity, energy, entropy, quantile of above five parameters were analyzed. The expression of PTEN, P-Akt and m-TOR were assessed by immunohistochemistry. Spearman correlation analysis was used to compare the correlation between the quantitative perfusion histogram parameters and the expression of PTEN, P-Akt and m-TOR in different pathological subtypes of lung cancer. RESULTS: The expression of m-TOR (P = 0.013) and P-Akt (P = 0.002) in AC was significantly higher than those in SCC. Vp (uniformity) in SCC group, Ktrans (uniformity), Ve (kurtosis, Q10, Q25) in AC group, Fp (skewness, kurtosis, energy), Ve (Q75, Q90, Q95) in SCLC group was positively correlated with PTEN, and Fp (entropy) in the SCLC group was negatively correlated with PTEN (P < 0.05); Kep (Q5, Q10) in the SCLC group was positively correlated with P-Akt, and Kep (energy) in the SCLC group was negatively correlated with P-Akt (P < 0.05); Kep (Q5) in SCC group and Vp (meanvalue, Q75, Q90, Q95) in SCLC group was positively correlated with m-TOR, and Ve (meanvalue) in SCC group was negatively correlated with m-TOR (P < 0.05). CONCLUSIONS: The quantitative perfusion histogram parameters of DCE-MRI was correlated with the expression of PTEN, P-Akt and m-TOR in different pathological types of lung cancer, which may be used to indirectly evaluate the activation status of PI3K/Akt/mTOR signal pathway gene in lung cancer, and provide important reference for clinical treatment.