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Background: To construct a CT-based radiomics nomogram, enabling the estimation of overall survival (OS) in small cell lung cancer (SCLC) patients and facilitating the identification of prophylactic cranial irradiation (PCI) beneficiaries through risk stratification using the radiomics score (RS)., Methods: A retrospective recruitment of 375 patients with pathologically confirmed SCLC was conducted across three medical centers, followed by their division into different cohorts. To generate the RS, a series of analyses were performed, including Pearson correlation analysis, univariate Cox analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Subsequently, patients were stratified into either the low RS or high RS group, determined by identifying the optimal RS cutoff value. Subsequently, a radiomics nomogram was constructed using the RS, followed by assessments of its discrimination, calibration, clinical utility and reclassification. Moreover, we evaluated the potential benefits of PCI following stratification by RS., Results: For the internal and external validation cohorts, the radiomics nomogram (concordance index [C-index]: 0.770, 0.763) outperformed clinical nomogram (C-index: 0.625, 0.570) in predicting OS. Besides, patients with high RS had survival benefit from PCI in both the limited and extensive stage (hazard ratio [HR]: 0.304, 95% confidence interval [CI]: 0.087-1.065, P = 0.003; HR: 0.481, 95% CI: 0.270-0.860, P = 0.019, respectively), while no significant association were observed in patients with low RS., Conclusion: A radiomics nomogram based on CT shows potential in predicting OS for individuals with SCLC. The RS could assist in tailoring treatment plans to identify patients likely to benefit from PCI., Competing Interests: Declarations. Ethics approval and consent to participate: This retrospective study involving human participants was reviewed and approved by the ethics committees of The First Affiliated Hospital of Anhui Medical University (PJ2022-13–48), The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China (2024-RE-101), and Anhui Provincial Cancer Hospital (2023-YXK-13). Informed consent was waived due to the retrospective nature. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The PRIMALung EORTC-1901 trial investigates brain MRI ± PCI in all-stages of SCLC, aiming for non-inferior survival, improve cognition in the era of immunotherapy. @finn_corinne., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: AL, Grant for Academic Research: Roche, Beigene, Phamamar, AstraZeneca; TB, Advisory role: InhaTarget Therapeutics; NA, Advisory role: AstraZeneca; CFF, Advisory role: AstraZeneca., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The presented surgical video (Video 1) demonstrates the resection of an intradural extramedullary metastasis in a 62-year-old female patient with a history of metastatic small cell lung cancer (SCLC). SCLC commonly metastasizes to the central nervous system. 1 , 2 However, the vast majority of such metastases are to the brain. 1 , 2 Interestingly, the presented patient had a cerebellar SCLC metastasis operated on 10 months earlier. Several cases of intradural extramedullary spinal drop metastases arising from cerebellar tumors have been described in the literature, suggesting that a drop metastasis is a likely mechanism to explain this rare topography. 3-5 Preoperatively, the patient presented with 1 month of back pain and rapidly progressing left lower extremity weakness and myelopathic signs so surgery was offered. 6-10 Interval imaging showed an intradural extramedullary T4-T5 lesion suspicious for metastatic disease. The patient consented to the procedure. Intraoperatively, fluoroscopy was used to identify the T4-T6 pedicles, and laminectomies were performed. A T4-T6 durotomy was then performed under ultrasound guidance to ensure adequate tumor exposure. Careful dissection was carried out around the cranial and caudal poles of the lesion. Subsequently, central debulking was performed and the tumor was resected in piecemeal fashion. Complete resection required sacrifice of the left T5 nerve root and cutting of the dentate ligament in 2 locations for adequate visualization. Postoperative neurologic exam demonstrated improvement in her lower extremity weakness, and postoperative magnetic resonance imaging showed gross total resection. The postoperative course was uneventful, and the patient was discharged home on postoperative day 6., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Recent advancements in magnetic resonance imaging (MRI) for staging have highlighted the critical question of the need for prophylactic cranial irradiation (PCI) in managing early to mid-stage small cell lung cancer (SCLC). This study assesses the impact of PCI on overall survival (OS) and intracranial control among patients with stage I-IIB SCLC., Methods: Data from 148 stage I-IIB SCLC patients treated with thoracic radiation therapy (TRT) at two centers were examined. Patients were categorized based on PCI administration: 63 received PCI, while 85 did not. All underwent pretreatment MRI, achieving at least a partial response to therapy. A 1:1 propensity score matching analysis corrected for potential biases., Results: Propensity scores were generated to 116 patients, considering patient demographics, disease progression, and treatment methods. Death was included as a competing risk. The 3-year brain metastases (BM) occurrence rate was significantly higher in patients who did not receive PCI (30.0%) compared to those who did (14.8%), however, the difference was not statistically significant (No PCI vs. PCI, hazard ratio [HR]: 2.08, 95% CI [0.93-4.55], P = .07). No significant effect of PCI on OS was observed [PCI vs. No PCI, HR: 0.80, 95% CI (0.45-1.43), P = .45]. A subgroup analysis of stage IIB patients showed a significant increase in BM risk and mortality for those not receiving PCI (No PCI vs. PCI, BM risk HR: 5.85, 95% CI: 1.83-18.87, P = .003; mortality HR: 2.78, 95% CI: 1.14-6.67, P = .02), with less pronounced effects in stages I-IIA., Conclusion: With modern MRI-based screening, PCI may markedly benefit stage IIB SCLC patients by reducing BM and improving OS after initial sensitive treatment. This benefit does not appear to extend to stage I-IIA patients., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purposes: To evaluate the impact of prophylactic cranial irradiation (PCI) on the prognosis of patients with limited-stage small cell lung cancer (SCLC) in the era of MRI surveillance., Methods: Limited-stage SCLC patients with complete remission (CR) or partial remission (PR) of tumor after definitive chemo-radiotherapy (CRT) were retrospectively analyzed. Survival data were calculated by Kaplan-Meier methods, Cox proportional hazards model was applied for multivariate prognostic analysis., Results: Between June 2002 and January 2017, 620 patients with limited-stage SCLC were accrued in our study. After CRT, 228 (36.8%) patients achieved CR, of whom, 29 patients did not receive PCI, among the rest 199 patients, 172 (86.4%) received brain MRI to exclude brain metastasis (BM) before PCI. With a median follow-up time of 25.6 months, the cumulative BM rate was 17.1% and 37.9% in patients who received or did not receive PCI (P = 0.011). The median survival time was 30.2 months and 30.5 months, respectively and the 1 -, 3 -, 5-year survival rates were 93.7%, 42.9%, 35.8% and 83.4%, 46.5%, 41.9%, respectively (P = 0.98). Multivariate analysis indicated that baseline KPS ≥ 90 was a favorable independent prognostic factor for OS in CR patients (HR: 0.33, 95% CI: 0.23-0.46, P = 0.000). After CRT, 392 (63.2%) patients achieved PR, 53 cases did not receive PCI and 310 (91.4%) of the remaining 339 patients received brain MRI before PCI. With a median follow-up time of 15.5 months, the cumulative brain metastasis rate was 12.7% and 46.2% respectively (P = 0.000). The median survival time was 25.7 months and 18.6 months, respectively. The 1 -, 3 -, and 5-year survival rates were 87.6%, 40.2%, 29.2% and 75.7%, 16.7%, 10.3% (P = 0.000). Baseline KPS ≥ 90 (HR: 0.32, 95% CI: 0.25-0.41, P = 0.000) and PCI (HR: 0.57, 95% CI: 0.41-0.79, P = 0.001) were favorable prognostic factors for OS in PR patients., Conclusions: In this study, PCI significantly reduced the incidence of BM in patients with limited-stage SCLC who were evaluated as CR and PR after CRT, but it has no significantly positive impact on overall survival in CR patients. Further prospective randomized studies were warranted., Competing Interests: Declarations Ethics approval and consent to participate The study was approved be ethical committee of Zhejiang Cancer Hospital. Consent for publication The authors give their permission for the submission. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Objective: The goal of the work described here was to investigate the role of multimodal contrast-enhanced ultrasound in the differential diagnosis of peripheral lung cancer., Methods: From April 2017 to July 2021, 109 patients with confirmed pulmonary malignant lesions who underwent CEUS examination were involved in our study. Seven patients were excluded because of the short duration of CEUS video or unsatisfactory imaging. Finally,102 patients with peripheral lung cancer were enrolled in this study. The maximum diameter of the lesions ranged from 1.6 to 13.0 cm (mean 6.2 ± 2.3 cm). On the basis of the pathological results, the patients were divided into the small cell lung cancer (SCLC) group and non-small cell lung cancer (NSCLC) group (including adenocarcinoma, lung squamous cell carcinoma and large cell neuroendocrine carcinoma). A Logiq E9 ultrasonic machine equipped with a 3.5 to 5.0 MHz C5-1 probe was used. Patient clinical information, CEUS features, CPI patterns and TIC parameters were analyzed and compared between different groups. Statistical analyses were performed with SPSS software and MedCalc software. The receiver operating characteristic curve was plotted., Results: In the differential diagnosis of SCLC and NSCLC, color parametric imaging indicated great performance. NSCLC exhibited a centripetal enhancement pattern more frequently (72.7%), while SCLC exhibited an eccentric enhancement pattern more frequently (92.9%) (p < 0.001). In the differential diagnosis of adenocarcinoma and squamous cell carcinoma, logistic regression analysis revealed that patient age of onset ≤60 y, difference in arrival time between lung and tumor ≤3.8 s, drop time of the time-intensity curve >23.2 s and absence of internal necrosis on CEUS were independent predictors for adenocarcinoma (area under the curve = 0.861)., Conclusion: In our study, multimodal contrast-enhanced ultrasound provided useful information in the differential diagnosis between small cell lung cancer and non-small cell lung cancer, especially between adenocarcinoma and squamous cell carcinoma., Competing Interests: Conflict of Interest The authors report no conflicts of interest., (Copyright © 2024 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

The prognosis of extensive-stage small cell lung cancer is usually poor. In this study, a combined model based on pre-treatment CT radiomics and clinical features was constructed to predict the OS of extensive-stage small cell lung cancer after chemotherapy with immunotherapy.Clinical data of 111 patients with extensive stage small-cell lung cancer who received first-line immunotherapy combined with chemotherapy in our hospital from December 2019 to December 2021 were retrospectively collected. Finally, 93 patients were selected for inclusion in the study, and CT images were obtained through PACS system before treatment. All patients were randomly divided into a training set (n = 66) and a validation set (n = 27). Images were imported into ITK-SNAP to outline areas of interest, and Python software was used to extract radiomics features. A total of 1781 radiomics features were extracted from each patient's images. The feature dimensions were reduced by MRMR and LASSO methods, and the radiomics features with the greatest predictive value were screened. The weight coefficient of radiomics features was calculated, and the linear combination of the feature parameters and the weight coefficient was used to calculate Radscore. Univariate cox regression analysis was used to screen out the factors significantly associated with prognosis from the radiomics and clinical features, and multivariate cox regression analysis was performed to establish the prognosis prediction model of extensive stage small cell lung cancer. The degree of metastases was selected as a significant clinical prognostic factor by univariate cox regression analysis. Seven radiomics features with significance were selected by LASSO-COX regression analysis, and the Radscore was calculated according to the coefficient of the radiomics features. An alignment diagram survival prediction model was constructed by combining Radscore with the number of metastatic lesions. The study population was stratified into those who survived less than 11 months, and those with a greater than 11 month survival. The C-index was 0.722 (se = 0.044) and 0.68(se = 0.074) in the training and the validation sets, respectively. The Log&#95;rank test results of the combination model were as follows: training set: p < 0.0001, validation set: p = 0.00042. In this study, a combined model based on radiomics and clinical features could predict OS in patients with extensive stage small cell lung cancer after chemotherapy with immunotherapy, which could help guide clinical treatment strategies., (© 2024. The Author(s).)

Rationale: Positron Emission Tomography (PET) using the somatostatin receptor 2 (SSTR2)-antagonist satoreotide trizoxetan ( 68 Ga-SSO120) is a novel, promising imaging modality for small-cell lung cancer (SCLC), which holds potential for theranostic applications. This study aims to correlate uptake in PET imaging with SSTR2 expression in immunohistochemistry (IHC) and to assess the prognostic value of 68 Ga-SSO120 PET at initial staging of patients with SCLC. Methods: We analyzed patients who underwent 68 Ga-SSO120 PET/CT during initial diagnostic workup of SCLC as part of institutional standard-of-care. SSTR2 expression in IHC was evaluated on a 4-level scale and correlated with normalized standardized uptake values and tumor-to-liver ratios (SUV max and TLR peak ) in 68 Ga-SSO120 PET on a lesion level. Highest lesion SUV max /TLR peak per patient, SSTR2 score in IHC, M status according to TNM classification, and other parameters were analyzed for association with overall survival (OS) and time to treatment failure (TTF) by univariate, multivariate (cut-off values were identified on data for best separation), and stratified Cox regression. Results: We included 54 patients (24 men/30 women, median age 65 years, 21 M0/33 M1 according to TNM classification). In 43 patients with available surplus tumor tissue samples, hottest lesion SUV max /TLR peak showed a significant correlation with the level of SSTR2-expression by tumor cells in IHC (Spearman's rho 0.86/0.81, both p < 0.001; ANOVA p < 0.001). High SSTR2 expression in IHC, 68 Ga-SSO120 SUV max and TLR peak of the hottest lesion per patient, whole-body TLR mean , MTV, TLG, M status, and serum LDH showed a significant association with inferior TTF/OS in univariate analysis. In separate multivariate Cox regression (including sex, age, M stage, and LDH) higher hottest-lesion TLR peak showed a significant association with shorter OS (HR = 0.26, 95%CI: 0.08-0.84, p = 0.02) and SSTR2 expression in IHC with significantly shorter TTF (HR = 0.24, 95%CI: 0.08-0.71, p = 0.001) and OS (HR = 0.22, 95%CI: 0.06-0.84, p = 0.03). In total, 12 patients (22.2%) showed low (< 1), 21 (38.9%) intermediate (≥ 1 but < 2), 14 (25.9%) high (≥ 2 but < 5), and 7 (13.0%) very high (≥ 5) whole-body mean TLR mean . Conclusion: In patients with SCLC, SSTR2 expression assessed by 68 Ga-SSO120 PET and by IHC were closely correlated and associated with shorter survival. More than 75% of patients showed higher whole-body 68 Ga-SSO120 tumor uptake than liver uptake and almost 40% high or very high uptake, possibly paving the way towards theranostic applications., Competing Interests: Competing Interests: Filiz Oezkan received personal fees from Sanofi Aventis, Janssen, DeciBio, ERBE and Genentech/Roche Ltd.; program funding to the institution was received from Olympus, Astrazeneca, ERBE and Janssen, all outside the submitted work. Lale Umutlu is a Speaker / Advisory Board Member for Bayer Healthcare and Siemens Healthcare and received research grants from Siemens Healthcare outside the submitted work. Rainer Hamacher was supported by the Clinician Scientist Program of the University Medicine Essen Clinician Scientist Academy (UMEA; Faculty of Medicine and Deutsche Forschungsgemeinschaft [DFG]); reports travel grants from Lilly, Novartis, and PharmaMar; and reports personal fees from Lilly and PharmaMar outside the submitted work. Jens Siveke is supported by German Cancer Aid (grant 70112505, PIPAC; grant 70113834, PREDICT-PACA), the Wilhelm-Sander Foundation (grant 2019.008.1), the DFG through grant SI1549/3-1 (Clinical Research Unit KFO337) and SI1549/4-1, and the Federal Ministry of Education and Research (BMBF; SATURN3 consortium); receives honoraria as a consultant or for continuing medical education presentations from AstraZeneca, Bayer, Immunocore, Roche, and Servier; receives research funding (to the institution) from Bristol Myers Squibb, Celgene, and Roche; and holds ownership and serves on the board of directors of Pharma15—all outside the submitted work. Wolfgang Fendler reports fees from SOFIE Biosciences (research funding), Janssen (consultant, speaker), Calyx (consultant, image review), Bayer (consultant, speaker, research funding), Novartis (speaker, consultant), Telix (speaker), GE Healthcare (speaker), Eczacıbaşı Monrol (speaker), Abx (speaker), Amgen (speaker), and Urotrials, all outside the submitted work. Marcel Wiesweg reports honoraria and advisory role from Amgen, AstraZeneca, Daiichi Sankyo, GlaxoSmithKline, Janssen, Novartis, Pfizer, Roche, Takeda, and research funding from Bristol-Myers Squibb, Takeda outside the submitted work. Ken Herrmann reports personal fees from Bayer, personal fees and other from Sofie Biosciences, personal fees from SIRTEX, non-financial support from ABX, personal fees from Adacap, personal fees from Curium, personal fees from Endocyte, grants and personal fees from BTG, personal fees from IPSEN, personal fees from Siemens Healthineers, personal fees from GE Healthcare, personal fees from Amgen, personal fees from Novartis, personal fees from ymabs, personal fees from Aktis Oncology, personal fees from Theragnostics, personal fees from Pharma15, outside the submitted work. Martin Schuler reports personal fees as a consultant from Amgen, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Merck Serono, Novartis, Roche, Sanofi, and Takeda; honoraria for continuing medical education presentations from Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Janssen, MSD, and Novartis; and research funding (to the institution) from AstraZeneca and Bristol Myers Squibb, all outside the submitted work. Hubertus Hautzel reports personal fees from Roche and Urenco, and other fees from Pari, Roche and Urenco, outside the submitted work. David Kersting reports speaker honoraria from Pfizer and Novartis outside the submitted work. A research grant from Pfizer outside the submitted work and funding by the German Research Foundation (DFG, KE2933/1-1), outside the submitted work., (© The author(s).)

Background: Small cell lung carcinoma (SCLC) is highly susceptible to metastasis in the early stages of the disease. However, the stomach is an uncommon site of metastasis in SCLC, and only a few cases of this type of metastasis have been reported. Therefore, SCLC gastric metastases have not been systematically characterized and are easily missed and misdiagnosed., Case Summary: We report three cases of gastric metastasis from SCLC in this article. The first patient presented primarily with cough, hemoptysis, and epigastric fullness. The other two patients presented primarily with abdominal discomfort, epigastric distension, and pain. All patients underwent gastroscopy and imaging examinations. Meanwhile, the immunohistochemical results of the lesions in three patients were suggestive of small cell carcinoma. Finally, the three patients were diagnosed with gastric metastasis of SCLC through a comprehensive analysis. The three patients did not receive appropriate treatment and died within a short time., Conclusion: Here, we focused on summarizing the characteristics of gastric metastasis of SCLC to enhance clinicians' understanding of this disease., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background and Purpose: In the context of the widespread availability of magnetic resonance imaging (MRI) and aggressive salvage irradiation techniques, there has been controversy surrounding the use of prophylactic cranial irradiation (PCI) for small-cell lung cancer (SCLC) patients. This study aimed to explore whether regular brain MRI plus salvage brain irradiation (SBI) is not inferior to PCI in patients with limited-stage SCLC (LS-SCLC)., Methods: This real-world multicenter study, which was conducted between January 2014 and September 2020 at three general hospitals, involved patients with LS-SCLC who had a good response to initial chemoradiotherapy and no brain metastasis confirmed by MRI. Overall survival (OS) was compared between patients who did not receive PCI for various reasons but chose regular MRI surveillance and followed salvage brain irradiation (SBI) when brain metastasis was detected and patients who received PCI., Results: 120 patients met the inclusion criteria. 55 patients received regular brain MRI plus SBI (SBI group) and 65 patients received PCI (PCI group). There was no statistically significant difference in median OS between the two groups (27.14 versus 33.00 months; P = 0.18). In the SBI group, 32 patients underwent whole brain radiotherapy and 23 patients underwent whole brain radiotherapy + simultaneous integrated boost. On multivariate analysis, only extracranial metastasis was independently associated with poor OS in the SBI group., Conclusion: The results of this real-world study showed that MRI surveillance plus SBI is not inferior to PCI in OS for LS-SCLC patients who had a good response to initial chemoradiotherapy., (© 2024. The Author(s).)

Objective: Combined small cell lung cancer is the only subtype of small cell lung cancer and is a relatively rare histology. However, its histopathological and molecular biological characteristics are not well understood to date., Methods: There were 512 surgical resections for lung cancer performed in our department from June 1, 2019 to June 1, 2023. Among them, 5 cases( 1.0%) were diagnosed postoperatively as combined small cell lung cancer., Results: The median age was 75 years. Tumor markers showed elevated newron specific enolage (NSE) in all cases measured. Imagingly, all patients had irregular, solid mass shadows on chest computed tomography( CT) scan. Abnormal fluorodeoxyglucose-positron emission tomography( FDG-PET) accumulation was also observed. Postoperative histopathological examination revealed that one patient was staged upstaging from the preoperative stage, and four patients were treated with carboplatin and etoposide as adjuvant therapy., Conclusions: Preoperative diagnosis of combined small cell lung cancer is difficult, but it is important to keep this disease in mind in terms of preoperative lymph node evaluation. Postoperative adjuvant therapy should be administered as in small cell carcinoma. However, further case series are needed, as gene mutations and treatment with immune checkpoint inhibitors are also attracting attention.

Abstract: 99m Tc-MIBI scintigraphy is a nuclear medicine imaging modality commonly used for the preoperative localization of parathyroid adenomas in patients with hyperparathyroidism. In addition, 99m Tc-MIBI can also be used for imaging various tumors due to its unique mechanism of intracellular accumulation. Here, we introduced a case of a single 99m Tc-MIBI SPECT/CT simultaneously visualized two different malignant tumors, such as papillary thyroid cancer and small cell lung cancer, along with a parathyroid adenoma in a patient with hyperparathyroidism. The clinical usefulness of 99m Tc-MIBI SPECT/CT was also explored by comparing it with 18 F-FDG PET/CT among the three tumors., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The prevalence of malignant central airway obstruction at diagnosis and its 5-year incidence are largely unknown, as are basic epidemiological data pertaining to this serious condition. To address these data limitations, we retrospectively collected data from the cohort of patients diagnosed with lung cancer at our institution in 2015 and followed cohort patients 5 years forward, until 2020., Methods: We reviewed index PET/CT or CT scans at the time of lung cancer diagnosis to identify the presence, subtype, and severity of malignant central airway obstruction as well as progression/development over the next 5 years., Results: The prevalence of malignant central airway obstruction affecting the airway lumen by 25% or greater was 17%, and its 5-year incidence of development was 8.2%. Notable associations from the multivariate analysis included a younger age and a stepwise increase in obstruction with increasing stage of disease. Squamous cell carcinoma and small-cell lung cancer were the 2 histologic subtypes with the strongest association with obstruction. The presence of malignant central airway obstruction either at time of diagnosis or on follow-up imaging was associated with significantly shortened survival (multivariate Cox proportional HR for MCAO=1.702, P<0.001)., Conclusion: This study provides the first systematic characterization of fundamental epidemiological data on malignant central airway obstructions at a tertiary cancer center in the United States. This data is important to inform research directions and funding efforts of this serious complication. It also serves as a baseline value against which to compare for future studies., Competing Interests: Disclosure: (within the past 36 mo): N.M.I. acknowledges serving as the principal investigator of the Phase II follow-up clinical study in a NIH/NCI award R44CA265656 made to Simphotek Inc. Payments were made to Roswell Park Comprehensive Cancer Center. N.M.I. also acknowledges receiving grant funding from the Johnson & Johnson Lung Cancer Initiative. G.S. acknowledges receiving research grant support, including free Photofrin and fibers from Pinnacle Biologics Inc. G.S. acknowledges current service on a scientific advisory board with honoraria and stock options from Lumeda Inc. (Rocky Hill, CT, USA). G.S. acknowledges grant support from the Lung Cancer Initiative at Johnson & Johnson, and grant support from POP Biotechnologies, LLC, and R44CA265656 to Simphotek Inc. through NCI/NIH awards. The remaining authors declare there is no conflict of interest or other disclosures., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparametric MRI to differentiate the pathological subtypes of brain metastasis (BM) in lung cancer patients. This retrospective analysis collected 246 patients (456 BMs) from five medical centers from July 2016 to June 2022. The BMs were from small-cell lung cancer (SCLC, n = 230) and non-small-cell lung cancer (NSCLC, n = 226; 119 adenocarcinoma and 107 squamous cell carcinoma). Patients from four medical centers were assigned to training set and internal validation set with a ratio of 4:1, and we selected another medical center as an external test set. An attention-guided residual fusion network (ARFN) model for T1WI, T2WI, T2-FLAIR, DWI, and contrast-enhanced T1WI based on the ResNet-18 basic network was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. Compared with models based on five single-sequence and other combinations, a multiparametric MRI model based on five sequences had higher specificity in distinguishing BMs from different types of lung cancer. In the internal validation and external test sets, AUCs of the model for the classification of SCLC and NSCLC brain metastasis were 0.796 and 0.751, respectively; in terms of differentiating adenocarcinoma from squamous cell carcinoma BMs, the AUC values of the prediction models combining the five sequences were 0.771 and 0.738, respectively. DL together with multiparametric MRI has discriminatory feasibility in identifying pathology type of BM from lung cancer., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Background and Purpose: To develop a computed tomography (CT)-based deep learning model to predict overall survival (OS) among small-cell lung cancer (SCLC) patients and identify patients who could benefit from prophylactic cranial irradiation (PCI) based on OS signature risk stratification., Materials and Methods: This study retrospectively included 556 SCLC patients from three medical centers. The training, internal validation, and external validation cohorts comprised 309, 133, and 114 patients, respectively. The OS signature was built using a unified fully connected neural network. A deep learning model was developed based on the OS signature. Clinical and combined models were developed and compared with a deep learning model. Additionally, the benefits of PCI were evaluated after stratification using an OS signature., Results: Within the internal and external validation cohorts, the deep learning model (concordance index [C-index] 0.745, 0.733) was far superior to the clinical model (C-index: 0.635, 0.630) in predicting OS, but slightly worse than the combined model (C-index: 0.771, 0.770). Additionally, the deep learning model had excellent calibration, clinical usefulness, and improved accuracy in classifying survival outcomes. Remarkably, patients at high risk had a survival benefit from PCI in both the limited and extensive stages (all P < 0.05), whereas no significant association was observed in patients at low risk., Conclusions: The CT-based deep learning model exhibited promising performance in predicting the OS of SCLC patients. The OS signature may aid in individualized treatment planning to select patients who may benefit from PCI., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T 1 - 2 N 0 M 0 (cT 1 - 2 N 0 M 0 ) 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 cT 1 - 2 N 0 M 0 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&#95;score (GTV and PTV)., Results: The initial investigation revealed a 33.9% OLM positivity rate in cT 1 - 2 N 0 M 0 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 cT 1 - 2 N 0 M 0 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 cT 1 - 2 N 0 M 0 SCLC., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)

Abstract: Patients with dermatomyositis are prone to have occult malignancy. A previously healthy 68-year-old man with dermatomyositis underwent FDG PET/CT to detect possible malignancy of unknown origin. The images showed not only diffuse increased activity in the muscle, which was related to the known dermatomyositis, but also intense activity in the anterior chest with foci of abnormal activity throughout the body. Pathology examination confirmed small cell carcinoma of the lung with widespread metastases., Competing Interests: Conflicts of interest and sources of funding: Inner Mongolia Autonomous Region “Grassland Talents” project young innovative and entrepreneurial talents., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background/aim: Chemo-immunotherapy, including the programmed death ligand 1 (PD-L1) antibody, is an effective treatment for patients with extensive-stage small-cell lung cancer (ES-SCLC). However, no biomarker has been established for the prediction of chemo-immunotherapy. Therefore, we investigated the potential of 18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) as a predictive marker., Patients and Methods: Forty-six patients with ES-SCLC who received 18 F-FDG-PET immediately before combined platinum-based chemotherapy with PD-L1 blockade as a first-line treatment were eligible, and the maximum standard uptake value (SUV max ), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on 18 F-FDG uptake were evaluated., Results: PD-L1 and tumor infiltrative lymphocytes (TILs) were immunohistochemically analyzed in 36 of the 46 patients. A high MTV was significantly associated with poor performance status and low albumin levels, and there was a significant association between low albumin and high TLG. Univariate analysis identified sex, Brinkman index, and MTV as significant predictors of progression-free survival (PFS), and sex, SUV max , MTV, and TLG as significant factors of overall survival (OS). Multivariate analysis revealed that sex, Brinkman index, and MTV were independent prognostic factors for PFS, and sex, SUV max , MTV, and TLG were significant predictors of OS. SUV max was significantly higher in patients with positive PD-L1 expression than in those with negative expression but was not significantly different between positive and negative TILs. Moreover, the levels of MTV and TLG were not closely associated with the levels of PD-L1 and TILs., Conclusion: MTV or TLG metabolic tumor activity is suitable for the prediction of chemo-immunotherapy outcomes in patients with ES-SCLC., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

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, [ 89 Zr]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 β-emitting radiometal 177 Lu─[ 177 Lu]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.

Rationale and Objectives: To evaluate the validity of CT-based delta radiomics signatures in predicting overall survival (OS) and local recurrence (LR) in small cell lung cancer (SCLC) patients after chemotherapy., Materials and Methods: Retrospectively enrolled 136 SCLC patients were split into training and testing cohorts. Radiomics features were extracted from CT images before, after the second, and the fourth cycle of chemotherapy. Delta radiomics features were obtained by calculating the net changes of features. Three radiomics signatures (R1, R2, and R3) and three delta radiomics signatures (R21, R31, and R32) were developed. The best signature was defined as the radiomics risk signature (RRS). The significant clinicoradiological factors and RRS of OS or LR were applied to build the combined model. RRS was also investigated in the subgroups based on stage and treatment regimens, respectively., Results: Delta radiomics models presented improved performance. R32 signature demonstrated the highest C-indices in the training and testing cohorts, with C-indices of 0.850 and 0.834 in the OS arm, and 0.723 and 0.737 in the LR arm, respectively. The incremental performance was observed after the clinicoradiological characteristics integrated into the RRS OS , with C-indexes of 0.857 and 0.836, respectively. Furthermore, the stratified analysis also confirmed the ability of RRS based on the stage and treatment regimen subgroups in the OS and LR arms, respectively., Conclusion: Delta radiomics signatures could improve the personalized prediction of OS and LR at the early stage of chemotherapy in SCLC patients. R32 signature performed the highest performance., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: Brain metastases (BMs) are common in small cell lung cancer (SCLC), and the efficacy of immune checkpoint inhibitors (ICIs) in these patients is uncertain. In this study we aimed to develop and validate a radiomics nomogram based on magnetic resonance imaging (MRI) for intracranial efficacy prediction of ICIs in patients with BMs from SCLC., Methods: The training and validation cohorts consisted of 101 patients from two centers. The interclass correlation coefficient (ICC), logistic univariate regression analysis, and random forest were applied to select the radiomic features, generating the radiomics score (Rad-score) through the formula. Using multivariable logistic regression analysis, a nomogram was created by the combined model. The discrimination, calibration, and clinical utility were used to assess the performance of the nomogram. Kaplan-Meier curves were plotted based on the nomogram scores., Results: Ten radiomic features were selected for calculating the Rad-score as they could differentiate the intracranial efficacy in the training (area under the curve [AUC], 0.759) and the validation cohort (AUC, 0.667). A nomogram was created by combining Rad-score, treatment lines, and neutrophil-to-lymphocyte ratio (NLR). The training cohort obtained an AUC of 0.878 for the combined model, verified in the validation cohort (AUC = 0.875). Kaplan-Meier analyses showed the nomogram was associated with progression-free survival (PFS) (p = 0.0152) and intracranial progression-free survival (iPFS) (p = 0.0052) but not overall survival (OS) (p = 0.4894)., Conclusion: A radiomics nomogram model for predicting the intracranial efficacy of ICIs in SCLC patients with BMs can provide suggestions for exploring individual-based treatments for patients., (© 2024 The Authors. Thoracic Cancer published by John Wiley & Sons Australia, Ltd.)

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., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)

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., (© 2023. The Author(s).)

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., (© 2023. Italian Society of Medical Radiology.)

Background: Small cell lung cancer (SCLC) is a common subtype of lung cancer, and there is currently no established method for the early identification of SCLC. We prepared a novel rare-earth near-infrared (NIR) downconversion nanoprobe to identify SCLC cells., Methods: The shell precursors Gd-OA and Na-TFA-OA were prepared, and the NaYF 4 :Nd@NaGdF 4 -ProGRP antibody probe was obtained after synthesizing downconversion fluorescent nanocrystals. The probe was used for NIR identification of cancer cells and subcutaneous tumors in nude mice. The biotoxicity of the probe to SCLC cells and nude mice was studied., Results: The NaYF 4 :Nd@NaGdF 4 -ProGRP antibody probe was successfully prepared, with a size of 44 nm, an NIR emission peak at approximately 1060 nm, and a concentration of 40 μmol/mL. The probe could achieve accurate NIR identification of SCLC cells and subcutaneous tumors in nude mice. Optimal images of the subcutaneous tumor model were obtained approximately 10 minutes after probe injection. There was no significant change in the hematology indices, respiratory rate, or heart rate of nude mice after the probe was injected (all P > 0.05)., Conclusion: We have successfully prepared a low-toxicity probe that can identify SCLC cells, which may be useful for the early detection of SCLC. And conduct theoretical exploration for non-invasive identification and identification of some early metastatic lesions without pathological sampling in the future., Competing Interests: The authors report no conflicts of interest regarding this article., (© 2023 Xu et al.)

PET imaging using the somatostatin receptor 2 (SSTR2) antagonist satoreotide trizoxetan (SSO-120, previously OPS-202) could offer accurate tumor detection and screening for SSTR2-antagonist radionuclide therapy in patients with SSTR2-expressing small cell lung cancer (SCLC). The aim of this single-center study was to investigate tumor uptake and detection rates of 68 Ga-SSO-120 in comparison to 18 F-FDG PET in the initial staging of SCLC patients. Methods: Patients with newly diagnosed SCLC who underwent additional whole-body 68 Ga-SSO-120 PET/CT during the initial diagnostic workup were retrospectively included. The mean administered activity was 139 MBq, and the mean uptake time was 60 min. Gold-standard staging 18 F-FDG PET/CT was evaluated if available within 2 wk before or after 68 Ga-SSO-120 PET if morphologic differences in CT images were absent. 68 Ga-SSO-120- or 18 F-FDG-positive lesions were reported in 7 anatomic regions (primary tumor, thoracic lymph node metastases, and distant metastases including pleural, contralateral pulmonary, liver, bone, and other) according to the TNM classification for lung cancer (eighth edition). Consensus TNM staging (derived from CT, endobronchial ultrasound-guided transbronchial needle aspiration, PET, and brain MRI) by a clinical tumor board served as the reference standard. Results: Thirty-one patients were included, 12 with limited and 19 with extensive disease according to the Veterans Administration Lung Study Group classification. 68 Ga-SSO-120-positive tumor was detected in all patients (100%) and in 90 of the 217 evaluated regions (41.5%). Thirteen patients (42.0%) had intense average 68 Ga-SSO-120 uptake (region-based mean SUV max ≥ 10); 28 patients (90.3%) had average 68 Ga-SSO-120 uptake greater than liver uptake (region-based mean peak tumor-to-liver ratio > 1). In 25 patients with evaluable 18 F-FDG PET, primary tumor, thoracic lymph node metastases, and distant metastases were detected in 100%, 92%, and 64%, respectively, of all investigated patients by 68 Ga-SSO-120 and in 100%, 92%, and 56%, respectively, by 18 F-FDG PET. 68 Ga-SSO-120 PET detected additional contralateral lymph node, liver, and brain metastases in 1, 1, and 2 patients, respectively (no histopathology available), and 18 F-FDG PET detected additional contralateral lymph node metastases in 3 patients (1 confirmed, 1 systematic endobronchial ultrasound-guided transbronchial needle aspiration-negative, and 1 without available histopathology). None of these differences altered Veterans Administration Lung Study Group staging. The region-based monotonic correlation between 68 Ga-SSO-120 and 18 F-FDG uptake was low (Spearman ρ = 0.26-0.33). Conclusion: 68 Ga-SSO-120 PET offers high diagnostic precision with comparable detection rates and additional complementary information to the gold standard, 18 F-FDG PET. Consistent uptake in most patients warrants exploration of SSTR2-directed radionuclide therapy., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

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.

Background: Small cell lung cancer (SCLC) is a highly malignant cancer characterized by metastasis and an extremely poor prognosis. Although combined chemoimmunotherapy improves the prognosis of extensive-stage (ES)-SCLC, the survival benefits remain limited. Furthermore, no reliable biomarker is available so far to predict the treatment outcomes for chemoimmunotherapy., Methods: This retrospective study included patients with ES-SCLC treated with first-line combined atezolizumab or durvalumab with standard chemotherapy between Janauray 1, 2019 and October 1, 2022 at five medical centers in China as the chemoimmunotherapy group. The patients were divided into one training cohort and two independent external validation cohorts. Additionally, we created a control group of ES-SCLC who was treated with first-line standard chemotherapy alone. The Radiomics Score was derived using machine learning algorithms based on the radiomics features extracted in the regions of interest delineated on the chest CT obtained before treatment. Cox proportional hazards regression analysis was performed to identify clinical features associated with therapeutic efficacy. The log-rank test, time-dependent receiver operating characteristic curve, and Concordance Index (C-index) were used to assess the effectiveness of the models., Results: A total of 341 patients (mean age, 62±8.7 years) were included in our study. After a median follow-up time of 12.1 months, the median progression-free survival (mPFS) was 7.1 (95% CI 6.6 to 7.7) months, whereas the median overall survival (mOS) was not reached. The TNM stage, Eastern Cooperative Oncology Group performance status, and Lung Immune Prognostic Index showed significant correlations with PFS. We proposed a predictive model based on eight radiomics features to determine the risk of chemoimmunotherapy resistance among patients with SCLC (validation set 1: mPFS, 12.0 m vs 5.0 m, C-index=0.634; validation set 2: mPFS, 10.8 m vs 6.1 m, C-index=0.617). By incorporating the clinical features associated with PFS into the radiomics model, the predictive efficacy was substantially improved. Consequently, the low-progression-risk group exhibited a significantly longer mPFS than the high-progression-risk group in both validation set 1 (mPFS, 12.8 m vs 4.5 m, HR=0.40, p=0.028) and validation set 2 (mPFS, 9.2 m vs 4.6 m, HR=0.30, p=0.012). External validation set 1 and set 2 yielded the highest 6-month area under the curve and C-index of 0.852 and 0.820, respectively. Importantly, the integrated prediction model also exhibited considerable differentiation power for survival outcomes. The HR for OS derived from the low-progression-risk and high-progression-risk groups was 0.28 (95% CI 0.17 to 0.48) in all patients and 0.20 (95% CI 0.08 to 0.54) in validation set. By contrast, no significant differences were observed in PFS and OS, between high-progression-risk patients receiving chemoimmunotherapy and the chemotherapy cohort (mPFS, 5.5 m vs 5.9 m, HR=0.90, p=0.547; mOS, 14.5 m vs 13.7 m, HR=0.97, p=0.910)., Conclusions: The integrated clinical and radiomics model can predict the treatment outcomes in patients with ES-SCLC receiving chemoimmunotherapy, rendering a convenient and low-cost prognostic model for decision-making regarding patient management., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The prognostic impact of tumor SUVmax (t-SUVmax) in small cell lung cancer (SCLC) has been questioned with controversial results, and the significance of the ratio of tumor SUVmax to primary tumor size (SUVmax/t-size) in SCLC has yet to be clarified as well. In this study, a retrospective analysis was carried out to figure out the prognostic and predictive powers of pretreatment primary t‑SUVmax and t‑SUVmax/t-size ratio in patients with SCLC., Methods: A total of 349 SCLC patients who underwent pretreatment staging with PET/CT scan were enrolled in the study and analyzed retrospectively., Results: In limited disease SCLC (LD-SCLC), tumor size was significantly associated with both t‑SUVmax (p = 0.02) and t‑SUVmax/t-size (p = 0.0001). Furthermore, performance status, tumor size (p = 0.001), and liver metastasis were significantly associated with t‑SUVmax in extended disease SCLC (ED-SCLC). Moreover, tumor size (p = 0.0001), performance status, cigarette smoking history, and pulmonary/pleural metastasis were found to be correlated with t‑SUVmax/t-size. No associations were found between clinical stages and either t‑SUVmax or t‑SUVmax/t-size (p = 0.9 for both), and t‑SUVmax and t‑SUVmax/t-size values were found to have similar survival rates in both LD-SCLC and ED-SCLC patients. In univariate and multivariate analyses, both t‑SUVmax and t‑SUVmax/t-size were found not to be associated with overall survival (p > 0.05) CONCLUSION: This study does not advocate the use of either t‑SUVmax or t‑SUVmax/t-size on pretreatment 18 F‑FDG-PET/CT scan as prognostic and predictive tools for both LD-SCLC and ED-SCLC patients. Likewise, we did not find that t‑SUVmax/t-size was superior to t‑SUVmax in that respect., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Background: Small-cell lung cancer (SCLC) is highly aggressive with a nearly incurable disease in most cases. The most important prognostic factor is the status of the mediastinal lymph nodes. Only a small proportion of patients can be diagnosed at early stages and directed to curative multimodal treatment. Therefore, accuracy of nodal staging by (18F)-Fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) computed tomography (18F-FDG-PET/CT) in (very) limited disease SCLC, although not well investigated, is highly important., Methods: Treatment naive, non-bulky patients treated or diagnosed with SCLC between June 2012 and April 2020 with complete data including FDG-PET/CT and invasive mediastinal staging were retrospectively analyzed ( n  = 19). Sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and accuracy of mediastinal lymph node staging of 18F-FDG-PET/CT was calculated., Results: The FDG-PET/CT showed a sensitivity of 91%, and the specificity was calculated as 87.5%. In this cohort, the disease prevalence in lymph nodes was 58% ( n  = 11). Positive predictive value was 91%, NPV 88% and accuracy calculated at 89%. One patient was upstaged from single-level N2 to multilevel N2. In one patient, upstaging in invasive staging was performed from N2 to N3, and one patient was downstaged from N1 to N0., Conclusions: FDG-PET/CT is a valuable tool for the detection of distant metastases, but in mediastinal staging of SCLC some limitations might remain. Invasive methods remain the gold standard. Therefore, the mediastinal lymph nodal status of patients with SCLC screened for multimodal treatment should be further evaluated by additional invasive techniques to verify the exact N-staging and to optimize treatment stratification.

Background: Lung is the most common primary site of brain metastases (BMs). For different pathological types of BMs have some similar characteristics, it is still a challenge to confirm the origin based on their characteristics directly. BMs of small cell lung cancer (SCLC) have favorable therapeutic expectations due to their high sensitivity to radiotherapy. This study sought to identify unique characteristics of BMs in SCLC, aiming to assist in clinical decision-making., Methods: Patients diagnosed with BMs of lung cancer who received radiotherapy from January 2017 to January 2022 were reviewed (N = 284). Definitive diagnosis of BMs of SCLC was reached for 36 patients. All patients underwent head examination using magnetic resonance imaging. The number, size, location, and signal characteristics of lesions were analyzed., Results: There were 7 and 29 patients with single focus and non-single focus, respectively. Ten patients had diffuse lesions, and the remaining 26 patients had a total of 90 lesions. These lesions were divided into three groups according to size: <1, 1-3, and >3 cm (43.33%, 53.34%, and 3.33%, respectively). Sixty-six lesions were located in the supratentorial area, primarily including cortical and subcortical lesions (55.56%) and deep brain lesions (20%). Moreover, 22 lesions were located in the infratentorial area. According to diffusion-weighted imaging and T1-weighted contrast enhancement, the imaging characteristics were classified into six patterns. Hyperintensity in diffusion-weighted imaging and homogeneous enhancement was the most common pattern of BMs in SCLC (46.67%), while partial lesions showed hyperintensity in diffusion-weighted imaging without enhancement (7.78%)., Conclusions: The manifestations of BMs in SCLC were multiple lesions (diameter: 1-3 cm), hyperintensity in diffusion-weighted imaging, and homogeneous enhancement. Interestingly, hyperintensity in diffusion-weighted imaging without enhancement was also one of the characteristics., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Objective: The aim of this study was to investigate the correlation between high-resolution CT (HRCT) signs and serum tumor markers, to improve the diagnostic level and identify different pathological types of lung cancer., Patients and Methods: 102 patients with pathologically confirmed lung cancer were selected as the observation group. HRCT scan and serum tumor markers [cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), and neuron-specific enolase (NSE)] were performed to analyze the correlation., Results: Among the 102 cases of lung cancer, 88 cases were of lobulation sign, 78 cases of speculation sign, 45 cases of pleural indentation sign, 35 cases of vessel tracking sign, and 34 cases of vacuole sign. CA125 had the highest concentration in lung adenocarcinoma (55.74±14.18) ng/ml, and SCCA had the highest concentration in lung squamous cell carcinoma (18.98±6.37) ng/ml. The concentration of NSE in small cell lung cancer was the highest (48.12±16.19) ng/ml., Conclusions: Pleural indentation sign and vacuole sign were more likely to happen in lung adenocarcinoma and lung squamous cell carcinoma, respectively. The significant increase of CA125, SCCA, and NSE concentrations suggested that lung cancer patients were more likely to suffer from lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung cancer, respectively.

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.

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.

Abstract: A 70-year-old man with a history of small cell lung carcinoma 2 years earlier was addressed for the suspicion of a paraneoplastic limbic encephalitis. Brain 18FDG PET/CT revealed a bilateral amygdalian and hippocampal hypermetabolism, confirming a limbic encephalitis, and concurrent whole-body 18FDG PET/CT showed a small cell lung carcinoma plurifocal metastatic recurrence, consistent with a paraneoplastic limbic encephalitis. 18FDG PET/CT follow-up under chemotherapy revealed an almost complete normalization of brain metabolism and a partial metabolic response of the metastatic recurrence, consistent with the good clinical neurological evolution of the patient. This case highlights the clinical-metabolic imaging correlation in paraneoplastic limbic encephalitis., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Lung cancer is the leading cause of cancer-related death in many countries, and an accurate histopathological diagnosis is of great importance in subsequent treatment. The aim of this study was to establish the random forest (RF) model based on radiomic features to automatically classify and predict lung adenocarcinoma (ADC), lung squamous cell carcinoma (SCC), and small cell lung cancer (SCLC) on unenhanced computed tomography (CT) images. Eight hundred and fifty-two patients (mean age: 61.4, range: 29-87, male/female: 536/316) with preoperative unenhanced CT and postoperative histopathologically confirmed primary lung cancers, including 525 patients with ADC, 161 patients with SCC, and 166 patients with SCLC, were included in this retrospective study. Radiomic features were extracted, selected, and then used to establish the RF classification model to analyse and classify primary lung cancers into three subtypes, including ADC, SCC, and SCLC according to histopathological results. The training (446 ADC, 137 SCC, and 141 SCLC) and testing cohorts (79 ADC, 24 SCC, and 25 SCLC) accounted for 85% and 15% of the whole datasets, respectively. The prediction performance of the RF classification model was evaluated by F1 scores and the receiver operating characteristic (ROC) curve. On the testing cohort, the areas under the ROC curve (AUC) of the RF model in classifying ADC, SCC, and SCLC were 0.74, 0.77, and 0.88, respectively. The F1 scores achieved 0.80, 0.40, and 0.73 in ADC, SCC, and SCLC, respectively, and the weighted average F1 score was 0.71. In addition, for the RF classification model, the precisions were 0.72, 0.64, and 0.70; the recalls were 0.86, 0.29, and 0.76; and the specificities were 0.55, 0.96, and 0.92 in ADC, SCC, and SCLC. The primary lung cancers were feasibly and effectively classified into ADC, SCC, and SCLC based on the combination of RF classification model and radiomic features, which has the potential for noninvasive predicting histological subtypes of primary lung cancers., Competing Interests: The authors declare that there are no conflicts of interest., (Copyright © 2023 Jianfeng Huang et al.)

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., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

In recent years, molecular imaging addressing the C-X-C motif chemokine receptor 4 (CXCR4) has increasingly been used in various clinical settings. Here, we aimed to assess radiopharmaceutical uptake and image contrast to determine the most relevant clinical applications for CXCR4-directed imaging. We also investigated the impact of specific activity on scan contrast. Methods: Patients ( n = 690) with a variety of neoplasms underwent a total of 777 PET/CT scans with 68 Ga-Pentixafor, serving as the CXCR4-specific radioligand. A semiquantitative target lesion analysis was conducted (providing SUV max and target-to-blood pool ratio [TBR], defined as SUV max [from target lesion] divided by SUV mean [from blood pool]). The applied specific activity (in MBq/μg) was compared with semiquantitative assessments. Results: Of the 777 scans, 242 did not show discernible uptake in disease sites, leaving 535 PET scans (68.9%) for further analysis. Very high tracer uptake (SUV max > 12) was found in multiple myeloma ( n = 113), followed by adrenocortical carcinoma ( n = 30), mantle cell lymphoma ( n = 20), adrenocortical adenoma ( n = 6), and small cell lung cancer ( n = 12). Providing information on image contrast, comparable results for TBR were recorded, with TBR (>8) in multiple myeloma, mantle cell lymphoma, and acute lymphoblastoid leukemia ( n = 6). When comparing specific activity with semiquantitative parameters, no significant correlation was found for SUV max or TBR ( P ≥ 0.612). Conclusion: In this large cohort, 68 Ga-Pentixafor demonstrated high image contrast in a variety of neoplasms, particularly for hematologic malignancies, small cell lung cancer, and adrenocortical neoplasms. The present analysis may provide a roadmap for detecting patients who may benefit from CXCR4-targeted therapies., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

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., (Copyright © 2022. Published by Elsevier Ltd.)