FDG PET/CT in the Staging of Lung Cancer

The Potential of Basal F-18-FDG PET/CT in Evaluating Prognosis and Benefit From Adjuvant Chemotherapy After Tumor Resection of Stage IB(T2, ≤ 3 cm With VPI, N0, M0)NSCLC

OBJECTIVES

To investigated whether the basal F-18-FDG PET/CT could evaluate the prognosis or the benefit from adjuvant chemotherapy after surgery of patients with early-stage NSCLC with visceral pleural invasion.

MATERIALS AND METHODS

A total of 116 patients with stage IB (T2, ≤ 3 cm with VPI, N0, M0) NSCLC underwent tumor resection and F-18-FDG PET/CT 1-3 weeks before surgery and were followed up for 1-79 months after surgery. SUVpeak, SUVmax, SUVmean, MTV, and TLG of tumors were obtained. The primary and secondary endpoints were progression-free survival (PFS) and overall survival (OS), respectively. ROC curve analysis, Cox regression test, and the Kaplan-Meier method were used for statistical analysis.

RESULTS

High SUVs, TLG, and MTV were associated with postoperative progression of NSCLC (the area under the ROC curve: 0.695 to 0.750, P < .001). The increase of SUVs, TLG or MTV was associated with short postoperative PFS (P < .001) while an increase in TLG (P = .016) or MTV (P = .018) was associated with short postoperative OS. TLG > 16.81 was an independent indicator of both the short PFS (HR = 5.534, P = .002) and the short OS (HR = 5.075, P = .031). Further, adjuvant chemotherapy was associated with longer PFS in NSCLCs with TLG > 16.81 (treated vs. untreated: 63 vs. 52 months; HR = 2.242, P = .022) rather than those with TLG ≤ 16.81.

CONCLUSION

SUV-based parameters on F-18-FDG PET/CT have the potential to evaluate the prognosis and benefit from adjuvant chemotherapy after tumor resection in stage IB (T2, ≤ 3 cm with VPI, N0, M0) NSCLC and therefore may be helpful for lung cancer treatment.

Predictive value of 18F-FDG PET/CT metabolic parameters for lymph node metastasis of non-small cell lung cancer

BACKGROUND

Lymph node metastasis is closely associated with the prognosis of patients with non-small cell lung cancer (NSCLC). This study aimed to evaluate the role of preoperative 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) parameters in mediastinal lymph node metastasis in NSCLC.

METHODS

One hundred patients with NSCLC who underwent surgery, systematic lymph node dissection, who had undergone 18FFDG PET/CT for initial staging were divided into two groups: lymph node metastasis and non-metastasis. The maximum standardized uptake value (SUVmax), average standardized uptake value (SUVmean), SUV in the liver (SURliver), mediastinal blood pool (SURblood), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were detected in both groups. Receiver operating characteristic (ROC) curves were used to evaluate the parameters for predicting the diagnostic efficacy.

RESULTS

The SUVmax, SUVmean, SURblood, SURliver, MTV, and TLG were higher in the group with lymph node metastasis than in the group without lymph node metastasis. The ROC analysis showed that 18F-FDG PET/CT demonstrated acceptable predictive ability with AUC of 0.964 (95% CI, 0.930-0.998).

CONCLUSIONS

The relative 18F-FDG PET/CT primary uptake and substitution parameters showed acceptable predictive efficacy for mediastinal lymph node metastasis in patients with NSCLC. Additional, SURblood has potential for clinical application.

Uncertainty-aware automatic TNM staging classification for [18F] Fluorodeoxyglucose PET-CT reports for lung cancer utilising transformer-based language models and multi-task learning

BACKGROUND

[18F] Fluorodeoxyglucose (FDG) PET-CT is a clinical imaging modality widely used in diagnosing and staging lung cancer. The clinical findings of PET-CT studies are contained within free text reports, which can currently only be categorised by experts manually reading them. Pre-trained transformer-based language models (PLMs) have shown success in extracting complex linguistic features from text. Accordingly, we developed a multi-task 'TNMu' classifier to classify the presence/absence of tumour, node, metastasis ('TNM') findings (as defined by The Eight Edition of TNM Staging for Lung Cancer). This is combined with an uncertainty classification task ('u') to account for studies with ambiguous TNM status.

METHODS

2498 reports were annotated by a nuclear medicine physician and split into train, validation, and test datasets. For additional evaluation an external dataset (n = 461 reports) was created, and annotated by two nuclear medicine physicians with agreement reached on all examples. We trained and evaluated eleven publicly available PLMs to determine which is most effective for PET-CT reports, and compared multi-task, single task and traditional machine learning approaches.

RESULTS

We find that a multi-task approach with GatorTron as PLM achieves the best performance, with an overall accuracy (all four tasks correct) of 84% and a Hamming loss of 0.05 on the internal test dataset, and 79% and 0.07 on the external test dataset. Performance on the individual TNM tasks approached expert performance with macro average F1 scores of 0.91, 0.95 and 0.90 respectively on external data. For uncertainty an F1 of 0.77 is achieved.

CONCLUSIONS

Our 'TNMu' classifier successfully extracts TNM staging information from internal and external PET-CT reports. We concluded that multi-task approaches result in the best performance, and better computational efficiency over single task PLM approaches. We believe these models can improve PET-CT services by assisting in auditing, creating research cohorts, and developing decision support systems. Our approach to handling uncertainty represents a novel first step but has room for further refinement.

Predictive [18F]-FDG PET/CT-Based Radiogenomics Modelling of Driver Gene Mutations in Non-small Cell Lung Cancer

RATIONALE AND OBJECTIVES

To investigate whether [18F]-FDG PET/CT-derived radiomics may correlate with driver gene mutations in non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

In this IRB-approved retrospective study, 203 patients with surgically treated NSCLC who underwent subsequent genomic analysis of the primary tumour at our institution between December 2004 and January 2014 were identified. Of those, 128 patients (mean age 62.4 ± 10.8 years; range: 35-84) received preoperative [18F]-FDG PET/CT as part of their initial staging and thus were included in the study. PET and CT image segmentation and feature extraction were performed semi-automatically with an open-source software platform (LIFEx, Version 6.30, lifexsoft.org). Molecular profiles using different next-generation sequencing (NGS) panels were collected from a web-based resource (cBioPortal.ca for Cancer genomics). Two statistical models were then built to evaluate the predictive ability of [18F]-FDG PET/CT-derived radiomics features for driver gene mutations in NSCLC.

RESULTS

More than half (68/128, 53%) of all tumour samples harboured three or more gene mutations. Overall, 55% of tumour samples demonstrated a mutation in TP53, 26% of samples had alterations in KRAS and 17% in EGFR. Extensive statistical analysis resulted in moderate to good predictive ability. The highest Youden Index for TP53 was achieved using combined PET/CT features (0.70), for KRAS using PET features only (0.57) and for EGFR using CT features only (0.60).

CONCLUSION

Our study demonstrated a moderate to good correlation between radiomics features and driver gene mutations in NSCLC, indicating increased predictive ability of genomic profiles using combined [18F]-FDG PET/CT-derived radiomics features.

Predicting solitary pulmonary lesions in breast cancer patients using 18fluorodeoxyglucose-positron emission tomography/computed tomography combined with clinicopathological characteristics

BACKGROUND

Solitary pulmonary nodules (SPNs) remain difficult to diagnose for clinical therapeutic purposes in patients with a history of breast cancer. This study try to investigate the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) combined with clinicopathological predictors for the differential diagnosis of SPNs in breast cancer patients.

METHODS

One hundred and twenty breast cancer patients with newly detected SPNs were enrolled in the study and divided into a primary lung cancer (PLC) group and a breast cancer metastasis (BCM) group. The clinicopathological characteristics as well as metabolic and morphological characteristics on 18F-FDG-PET/CT images of 120 patients were retrospectively reviewed. The differences of clinicopathological and 18F-FDG-PET/CT characteristics between the two groups were analyzed, and multivariate analyses for the diagnosis of SPNs were performed.

RESULTS

Clinicopathological terms of carcinoembryonic antigen (CEA) and CA15-3 levels exhibited significant differences between PLC and BCM groups (P = 0.005 and P = 0.001, respectively). Metabolic characteristics of 18F-FDG-PET/CT images included FDG uptake, SUVmax of SPNs, hilar and/or mediastinal lymph node metastasis, SUVmax of hilar and/or mediastinal lymph node, and extrapulmonary metastasis showed significant differences between PLC and BCM groups (P = 0.004, P < 0.001, P = 0.01, P = 0.032 and P = 0.023, respectively). The lobulation sign, spicule sign, and pleural indentation sign were identified as statistically different morphological features of PLC in CT images (all P < 0.001). Among these, the SUVmax of SPNs, lobulation sign, and pleural indentation sign were valuable predictive factors for accurate diagnosis of SPNs in breast cancer patients.

CONCLUSIONS

18F-FDG-PET/CT combined with serum tumor markers are valuable for the diagnosis of SPNs in breast cancer patients.

Comparison of whole-body 18F-FDG-PET/CT with 18F-FDG-PET/CT limited to skull base to upper abdomen for primary staging of lung cancer - a retrospective explorative analysis

The gold standard for ruling out distant metastases as part of primary staging in lung cancer is whole-body 18F-FDG-PET/CT, but this method is resource-intensive. Recent evidence suggests that examining only the thorax and upper abdomen may be sufficient 1 2 3. If a limited 18F-FDG-PET/CT approach proves effective for proper staging, it could lead to quicker examinations and reduced radiation exposure. This study aimed to determine whether limited 18F-FDG-PET/CT is adequate for the primary staging of lung cancer.In this study, a retrospective analysis of 161 patients (87 men, 74 women; age range 31-88 y) with recent or suspected lung cancer who had undergone a whole-body 18F-FDG-PET/CT examination for primary staging at our clinic between 2018 and 2022 was conducted. None of these patients showed evidence of extrathoracic metastases before the 18F-FDG-PET/CT examination. The images were divided into three regions: "head-neck" (HN), "thorax-upper abdomen" (TUA), and "lower abdomen-hip" (LAH). TNM staging based on the HN plus TUA region was compared with TNM staging based on the whole body.Among the 161 subjects, 7 (4%) showed malignancy-suspect lesions in HN, 110 (68%) in TUA and 7 (4%) had suspected distant metastases in LAH. The TNM staging based on HN plus TUA corresponded to TNM staging based on the whole body in 161 (100%) examinations. This finding aligns with similar results in previous literature. 18F-FDG-PET/CT limited to HN and TUA yielded accurate staging in all cases. Adopting this method could facilitate the examination and correct staging of more individuals, reducing exam waiting times and physician reporting time and minimising radiation exposure.

Machine Learning Models to Predict Bone Metastasis Risk in Patients With Lung Cancer

INTRODUCTION

The aim of this study was to find the most appropriate variables to input into machine learning algorithms to identify those patients with primary lung malignancy with high risk for metastasis to the bone.

PATIENT INCLUSION

Patients with either histological or radiological diagnoses of lung cancer were included in this study.

RESULTS

The patient cohort comprised 1864 patients diagnosed from 2016 to 2021. A total of 25 variables were considered as potential risk factors. These variables have been identified in previous studies as independent risk factors for bone metastasis. Treatment methods for lung cancer were taken into account during model development. The outcome variable was binary, (presence or absence of bone metastasis) with follow-up until death or 12-month survival, whichever is the sooner. Results showed that American Joint Committee on Cancer staging, the use of EGFR inhibitor, age, T-staging, and lymphovascular invasion were the five input features contributing the most to the model algorithm. High AJCC staging (OR 1.98; p < 0.05), the use of EGFR inhibitor (OR 6.14; p < 0.05), high T-staging (OR 1.47; p < 0.05), and the presence of lymphovascular invasion (OR 4.92; p < 0.05) increase predicted risk of bone metastasis. Conversely, older age reduces predicted bone metastasis risk (OR 0.98; p < 0.05).

CONCLUSION

The machine learning model developed in this study can be easily incorporated into the hospital's Clinical Management System so that input variables can be immediately utilized to give an accurate prediction of bone metastatic risk, therefore informing clinicians on the best treatment strategy for that individual patient.

Neoadjuvant and Adjuvant Treatments for Early Stage Resectable NSCLC: Consensus Recommendations From the International Association for the Study of Lung Cancer

Advances in the multidisciplinary care of early stage resectable NSCLC (rNSCLC) are emerging at an unprecedented pace. Numerous phase 3 trials produced results that have transformed patient outcomes for the better, yet these findings also require important modifications to the patient treatment journey trajectory and reorganization of care pathways. Perhaps, most notably, the need for multispecialty collaboration for this patient population has never been greater. These rapid advances have inevitably left us with important gaps in knowledge for which definitive answers will only become available in several years. To this end, the International Association for the Study of Lung Cancer commissioned a diverse multidisciplinary international expert panel to evaluate the current landscape and provide diagnostic, staging, and therapeutic recommendations for patients with rNSCLC, with particular emphasis on patients with American Joint Committee on Cancer-Union for International Cancer Control TNM eighth edition stages II and III disease. Using a team-based approach, we generated 19 recommendations, of which all but one achieved greater than 85% consensus among panel members. A public voting process was initiated, which successfully validated and provided qualitative nuance to our recommendations. Highlights include the following: (1) the critical importance of a multidisciplinary approach to the evaluation of patients with rNSCLC driven by shared clinical decision-making of a multispecialty team of expert providers; (2) biomarker testing for rNSCLC; (3) a preference for neoadjuvant chemoimmunotherapy for stage III rNSCLC; (4) equipoise regarding the optimal management of patients with stage II between upfront surgery followed by adjuvant therapy and neoadjuvant or perioperative strategies; and (5) the robust preference for adjuvant targeted therapy for patients with rNSCLC and sensitizing EGFR and ALK tumor alterations. Our primary goals were to provide practical recommendations sensitive to the global differences in biology and resources for patients with rNSCLC and to provide expert consensus guidance tailored to the individualized patient needs, goals, and preferences in their cancer care journey as these are areas where physicians must make daily clinical decisions in the absence of definitive data. These recommendations will continue to evolve as the treatment landscape for rNSCLC expands and more knowledge is acquired on the best therapeutic approach in specific patient and disease subgroups.

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population

BACKGROUND

With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application.

METHODS

Our study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules.

RESULTS

The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001).

CONCLUSIONS

Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

When to Consider Invasive Lymph Node Staging in Non-Small-Cell Lung Cancer? A Novel Scoring System Utilising Metabolic Parameters in 18F-FDG PET/CT

OBJECTIVE

The maximum standardised uptake value (SUVmax) is a widely utilised metric in positron emission tomography/computed tomography for clinically staging non-small-cell lung cancer (NSCLC), yet the reliability of SUVmax remains controversial. We herein aimed to assess the effectiveness of semi-quantitative parameters, encompassing size, SUVmax, metabolic tumour volume (MTV), total lesion glycolysis (TLG) and heterogeneity factor (HF), in evaluating both primary tumours and lymph nodes (LNs) on positron emission tomography/computed tomography. A novel scoring system was devised to appraise the role of semi-quantitative parameters and visually evaluate LNs for nodal staging.

MATERIALS AND METHODS

Patients with pathological NSCLC, diagnosed between 2014 and 2019 and clinically staged I-III, were enrolled in the study. Patient demographics, including age, sex, tumour location, diameter, tumour-node-metastasis stage, as well as SUVmax, MTV, TLG and HF parameters of primary tumours and LNs, were documented.

RESULTS

The analysis comprised 319 patients and 963 LNs. Patients had a mean age of 61.62 years, with 91.5% being male. Adenocarcinoma exhibited a histological association with LN metastasis (P=0.043). The study findings revealed that tumour size, SUVmax, MTV, TLG and HF did not significantly affect the detection of LN metastasis. Conversely, non-squamous cell carcinoma, LNs exhibiting higher FDG levels than the liver, LN size, SUVmax, MTV and TLG were identified as risk factors (P<0.0001). The identified cut-off values were 1.05cm for LN size, 4.055 for SUVmax, 1.805cm3 for MTV and 5.485 for TLG. The scoring system incorporated these parameters, and visual assessment indicated that a score of ≥3 increased the risk of metastasis by 14.33 times.

CONCLUSION

We devised a novel scoring system and demonstrated that LNs with a score of ≥3 in patients with NSCLC have a high likelihood of metastasis. This innovative scoring system can serve as a valuable tool to mitigate excessive and extreme measures in the assessment of invasive pathological staging.

Developing Communication Support Material for Sharing Information with Patients Undergoing an 18F-FDG PET/CT Examination

Our aim was to develop communication support material for information sharing related to an 18F-FDG PET/CT examination. Methods: The study had a qualitative design adapting a multiphase structure. A prototype of communication support material consisting of illustrations and text related to an 18F-FDG PET/CT examination was developed. Interviews were conducted with patients scheduled for an 18F-FDG PET/CT examination for the first time, and questionnaires were collected from health care professionals with experience in 18F-FDG PET/CT. The communication support material was revised until consensus was reached about it. Results: The results are based on interviews with patients (n = 10) and questionnaires collected from health care professionals (n = 9). The overall theme revealed that patient information about an 18F-FDG PET/CT examination is a balancing act between text and illustrations. The analysis showed 2 categories: "illustrations as a complement" and "easy-to-understand layout." Conclusion: The participants strengthened the development of the communication support material by bringing in valuable viewpoints from various perspectives. The results support a person-centered approach in which information about an 18F-FDG PET/CT examination can be adapted to each patient's needs as a balancing act between text and illustrations.

Comparison Between Endobronchial-Guided Transbronchial Biopsy and Computed Tomography-Guided Transthoracic Lung Biopsy for the Diagnosis of Central Pulmonary Lesions

BACKGROUND

Lung cancer is one of the most common malignant tumors at present. This study aimed to compare the diagnostic accuracy, complication rates, and predictive values of computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB) and electronic bronchoscopy-guided transbronchial lung biopsy (TBLB) for patients with central pulmonary lesions (CPLs) with a diameter ≥ 3 cm.

METHODS

We retrospectively included 110 patients with CPLs with a diameter ≥ 3 cm who underwent preoperative PTNB and TBLB examinations and ultimately underwent surgery to remove CPLs and obtained pathological results. Detailed information was collected in order to compare whether there was a difference between two groups. Data were processed using SPSS software (Version 26.0; IBM Corp). Data were compared by t-test or chi-square test. p < 0.05 was considered statistically significant.

RESULTS

All patients underwent surgical treatment at the department of thoracic surgery and obtained a final pathological diagnosis. The rate of positive predictive value (PPV) was comparable between the two methods, and the negative predictive value (NPV) was significantly higher in the PTNB group compared with the TBLB group (p < 0.05). In addition, PTNB was more sensitive and accurate than TBLB (p < 0.05). However, the PTNB group had a higher probability of complications, and TBLB was a relatively safer examination method.

CONCLUSION

PTNB demonstrated a higher accuracy and sensitivity than TBLB in the treatment of CPLs with a diameter ≥ 3 cm, but the complication rates of PTNB are relatively high. These methods exhibited different diagnostic accuracies and therefore should be selected based on different medical conditions.

The Effect of Hounsfield Unit Value on the Differentiation of Malignant/Benign Mediastinal Lymphadenopathy and Masses Diagnosed by Endobronchial Ultrasonography

Aim

In cases where standardized maximum uptake (SUVmax) values in positron emission tomography (PET-CT) were not sufficient to differentiate mediastinal lymphadenopathy and masses from malignant or benign, the contribution of Hounsfield unit (HU) values in thorax computed tomography to the diagnosis was evaluated.

Material Method

The study was conducted by evaluating the data of 182 patients between 2019 and 2023. HU values on non-contrast thorax computed tomography and PET-CT SUVmax values of biopsied masses and lymph nodes were compared with histopathological diagnoses.

Results

Patients, 58 females (31.9%) and 124 males (68.1%), who underwent EBUS were included in the study. Biopsies were taken from 233 stations (199 lymph nodes, 34 masses) from 182 patients. A total of 135 of the biopsies taken from 233 stations were histopathologically malignant and 98 were benign. While PET-CT SUVmax values of cases with benign histopathology were 4.5 ± 3.5, it was 7.6 ± 4.2 in patients with malignant pathology (p<0.05). The HU value on non-contrast thorax tomography in patients with benign histopathology was 43.1 ± 15.7, and in patients with malignant histopathology it was 40.5 ± 13.7 (p>0.05). When HU was compared according to lung cancer type, it was found to be significantly higher in non-small cell lung cancer (p=0.035). A weak (r=0.182) positive and significant relationship (p<0.01) was found between PET-CT values and HU values in thorax computed tomography.

Conclusion

While positron emission tomography maintains its importance in the differentiation of mediastinal lymphadenopathy and masses from malignant to non-malignant, it was concluded that HU values in computed tomography are not sufficient to distinguish malignant/non-malignant.

The Diagnostic Value of Endobronchial Ultrasound-Guided Fine Needle Aspiration (EBUS-FNA) in Diagnosing FDG-PET-Avid Lymph Nodes in Extrapulmonary Malignancies

Background and objective The accurate diagnosis of extrapulmonary malignancies with mediastinal lymphadenopathy is crucial for effective patient management. Endobronchial ultrasound-guided fine-needle aspiration (EBUS-FNA) has emerged as a valuable tool in assessing fluorodeoxyglucose (FDG)-positron emission tomography (PET)-avid lymph nodes (LNs). In this study, we aimed to evaluate the diagnostic value of EBUS-FNA in patients with mediastinal lymphadenopathy in extrapulmonary malignancies and compare its efficacy with PET-CT.  Methodology This retrospective, cross-sectional study was conducted at Shaukat Khanum Memorial Cancer Hospital and Research Center, Lahore, from February 2018 to February 2023. It included patients with extrapulmonary malignancies with mediastinal lymphadenopathy displaying abnormal PET-CT uptake, with LN diameters ≥5 mm, excluding lung cancer cases. Data on demographics, malignancy type, LN involvement, PET-CT findings, and EBUS-FNA histopathology were collected. EBUS-FNA procedures involved a 22-gauge needle, and samples were analyzed cytologically and histologically. SPSS Statistics version 20 (IBM Corp., Armonk, NY) was used to perform the statistical analysis. Results The study analyzed a total of 216 patients. Males comprised 56.3% of the cohort, and females 43.7%. The most common malignancy was lymphoma (33.0%), followed by breast cancer (12.6%). EBUS-FNA exhibited a sensitivity of 90.9% compared to PET-CT's sensitivity of 72.7%. Lymph node morphology on EBUS showed low echogenicity and irregular borders in malignant cases. Subcarinal and right hilar were the most frequently sampled lymph nodes. The study found significant differences in lymph node characteristics between non-malignant and malignant groups, with EBUS-FNA effectively identifying malignancies.  Conclusions EBUS-FNA demonstrates high sensitivity and diagnostic utility in identifying malignant lymph nodes in patients with extrapulmonary malignancies. Its effectiveness in detecting true positive cases highlights its importance as a complementary diagnostic tool to PET-CT in oncological diagnostics.

Omission of staging PET/CT linked to reduced survival in stage III non-small cell lung cancer: insights from the LUCAS project real-world data

Background

Stage III non-small cell lung cancer (NSCLC) is a highly heterogeneous stage due to its subgroups (IIIA-IIIC) comprising both resectable and unresectable tumors. Accurate determination of the extent of the disease is essential for excluding stage IV and choosing the optimal treatment regimen. Whole body positron emission tomography and computed tomography scan (PET/CT) is recommended as an initial staging imaging in locally advanced NSCLC. Despite international guidelines for NSCLC diagnosis and treatment, they are not always adhered to due to various reasons. Even in such a groundbreaking study, the phase 3 trial PACIFIC investigating the efficacy of durvalumab as consolidation therapy in patients with stage III NSCLC PET/CT was not mandatory. With the premise that whole body PET/CT of the trunk is essential for diagnosing stage III NSCLC, we performed a retrospective study evaluating the relationship of the use of PET/CT versus conventional staging with CT of the chest and abdomen, in terms of survival.

Methods

This retrospective study of stage III NSCLC patients used the Czech lung cancer registry LUCAS, which was established in June 2018. As of the data export (up to February 9, 2022), a total of 703 patients were eligible for the analysis. Overall survival (OS) was compared using Kaplan-Meier analysis and a Cox regression model. Continuous variables were tested using the Mann-Whitney test, and categorical variables using the Pearson's Chi-square or Fisher's exact test.

Results

A total of 703 patients were included in the cohort with an average age of 69 years. PET/CT was performed on 354 patients, and conventional staging using chest and abdominal CT on 349 patients. The median OS among patients with PET/CT was 20.9 months [95% confidence interval (CI): 18.1-23.7], and it was statistically significantly higher (P<0.001) than among patients without PET/CT, where the median OS was 9.0 months (95% CI: 7.3-10.6). The observed effect of PET/CT was also statistically significant when comparing individual stages (IIIA, IIIB, IIIC). The multivariate Cox model confirmed the use of PET/CT as an independent prognostic factor. The most common reason for omission of PET/CT was the local or time unavailability of the examination.

Conclusions

Omission of PET/CT can mean a significant decrement in survival for the patients in stage III NSCLC, likely due to poor staging and suboptimal treatment. Routine use of PET/CT is strictly recommended for the optimal management of stage III NSCLC patients even outside the high-income countries.

Prognostic potential of integrated morphologic and metabolic parameters of pre-therapeutic [18F]FDG-PET/CT regarding progression-free survival (PFS) and overall survival (OS) in NSCLC-patients

PURPOSE

This study aimed to evaluate the prognostic potential of pre-therapeutic [18F]FDG-PET/CT variables regarding prediction of progression-free survival (PFS) and overall survival (OS) in NSCLC-patients.

METHOD

NSCLC-patients who underwent pre-therapeutic [18F]FDG-PET/CT were retrospectively analyzed. The following imaging features were collected from the primary tumor: tumor size, tumor density, central necrosis, spicules and SUVmax. For standardization, an indexSUVmax was calculated (SUVmax primary tumor/SUVmax liver). Descriptive statistics and correlations of survival time analyses for PFS and OS were calculated using the Kaplan-Meier method and Cox regression including a hazard ratio (HR). A value of p < 0.05 was set as statistically significant. The 95%-confidence intervals (CI) were calculated. The median follow-up time was 63 (IQR 27-106) months.

RESULTS

This study included a total of 82 patients (25 women, 57 men; mean age: 66 ± 9 years). IndexSUVmax (PFS: HR = 1.0, CI: 1.0-1.1, p = 0.49; OS: HR = 1.0, CI: 0.9-1.2, p = 0.41), tumor size (PFS: HR = 1.0, CI: 0.9-1.0, p = 0.08; OS: HR = 1.0, CI: 0.9-1.0, p = 0.07), tumor density (PFS: HR = 0.9, CI: 0.6-1.4, p = 0.73; OS: HR = 0.3; CI: 0.1-1.1; p = 0.07), central necrosis (PFS: HR = 1.0, CI: 0.6-1.8, p = 0.98; OS: HR = 0.6, CI: 0.2-1.9, p = 0.40) and spicules (PFS: HR = 1.0, CI: 0.6-1.9, p = 0.91; OS: HR = 1.3, CI: 0.4-3.7, p = 0.65) did not significantly affect PFS and OS in the study population. An optimal threshold value for the indexSUVmax was determined by ROC analysis and Youden's index. There was no significant difference in PFS with an indexSUVmax-threshold of 3.8 (13 vs. 27 months; p = 0.45) and in OS with an indexSUVmax-threshold of 4.0 (113 vs. 106 months; p = 0.40).

CONCLUSIONS

SUVmax and morphologic parameters from pre-therapeutic [18F]FDG-PET/CT were not able to predict PFS and OS in NSCLC-patients.

Organ-specific accuracy of [18F]FDG-PET/CT in identifying immune-related adverse events in patients with high-risk melanoma treated with adjuvant immune checkpoint inhibitor

PURPOSE

This study aimed to determine the organ-specific accuracy of [18F]FDG-PET/CT in identifying immune-related adverse events (irAEs) in patients with high-risk (stage III/IV) surgically resected melanoma treated with an adjuvant immune checkpoint inhibitor (ICI) and determine the incidence of irAEs within the first year after starting treatment.

MATERIALS AND METHODS

This registry-based study included individuals who had undergone surgical removal of melanoma and were undergoing adjuvant ICI treatment (either nivolumab or pembrolizumab). The study specifically enrolled patients who had undergone both a baseline and at least one subsequent follow-up [18F]FDG-PET/CT scan. Follow-up scans were performed every third month in the first year after surgery to screen for disease recurrence. We retrospectively compared the follow-up scans with baseline scans to identify irAEs. Clinical information on irAEs was obtained from medical records and served as a reference standard for determining the accuracy of [18F]FDG-PET/CT.

RESULTS

A total of 123 patients with 363 [18F]FDG-PET/CT scans were included, and 65 patients (52.8%) developed irAEs. In decreasing order, the organ-specific incidences of irAEs were: skin 26/65 (40%), muscle and joints 21/65 (32.3%), intestines 13/65 (20%), thyroid gland 12/65 (18.5%), lungs 4/65 (6.2%), and heart 2/65 (3.1%). The sensitivities and specificities of [18F]FDG-PET/CT for diagnosing irAEs were: skin 19% (95% CI: 7-39%) and 95% (88-98%), muscles and joints 71% (48-89%) and 83% (75-90%), intestines 100% (75-100%) and 85% (77-91%); thyroid gland 92% (62-99%) and 95% (89-98%), lungs 75% (19-99%) and 90% (83-95%), and heart 50% (13-99%) and 97% (92-99%), respectively.

CONCLUSION

[18F]FDG-PET/CT generally had moderate to high sensitivities (except for skin and heart) and specificities in diagnosing irAEs in patients receiving adjuvant ICI; this could be suggested to be systematically assessed and reported in scan reports.

Predictive risk score for isolated brain metastasis in non-small cell lung cancer

Background

Brain metastasis is common with non-small cell lung cancer (NSCLC). Patients with some early-stage cancers don't benefit from routine brain imaging. Currently clinical stage alone is used to justify additional brain imaging. Other clinical and demographic characteristics may be associated with isolated brain metastasis (IBM). We aimed to define the most salient clinical features associated with synchronous IBM, hypothesizing that clinical and demographic factors could be used to determine the risk of brain metastasis.

Methods

The National Cancer Database was used to identify patients with NSCLC from 2016-2020. Primary outcome was the presence of IBM relative to patients without evidence of any metastasis. Cohorts were divided into test and validation. The test cohort was used to identify risk factors for IBM using multivariable logistic regression. Using the regression, a scoring system was created to estimate the rate of synchronous IBM. The accuracy of the scoring system was evaluated with receiver operating characteristic (ROC) analysis using the validation cohort.

Results

Study population consisted of 396,113 patients: 25,907 IBM and 370,206 without metastatic disease. IBM was associated with age, clinical T stage, clinical N stage, Charlson/Deyo comorbidity score, histology, and grade. A scoring system using these factors showed excellent accuracy in the test and validation cohort in ROC analysis (0.806 and 0.805, respectively).

Conclusions

Clinical and demographic characteristics can be used to stratify the risk of IBM among patients with NSCLC and provide an evidence-based method to identify patients who require dedicated brain imaging in the absence of other metastatic disease.

Endobronchial ultrasound-guided transbronchial needle aspiration for diagnosing thoracic lesions: a retrospective cohort study

Background

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive technique for biopsy of lung, peri-pulmonary tissue and lymph nodes under real-time ultrasound-guided biopsy. It is used in the diagnosis and/or staging of benign and malignant pulmonary and non-pulmonary diseases. Our study is based on a large sample size, in a diversified population which provides a representative real-world cohort for analysis.

Methods

Patients who underwent EBUS-TBNA procedure between September 2019 and August 2022 were included in this retrospective study. For cases diagnosed as benign and unclassified lesions by EBUS-TBNA, the final diagnosis was determined by further invasive surgery or a combination of therapy and clinical follow-up for at least 6 months.

Results

A total of 618 patients were included in the study, including 182 females (29.4%) and 436 males (70.6%). The mean age of all patients was 61.9 ± 10.5 years. These patients were successfully punctured by EBUS-TBNA to obtain pathological results. The pathological diagnosis results of EBUS-TBNA were compared with the final clinical diagnosis results as follows: 133 cases (21.5%) of benign lesions and 485 cases (78.5%) of malignant lesions were finally diagnosed. Among them, the pathological diagnosis was obtained by EBUS-TBNA in 546 patients (88.3%) (464 malignant lesions and 82 benign conditions), while EBUS-TBNA was unable to define diagnosis in 72 patients (11.6%). 20/72 non-diagnostic EBUS-TBNA were true negative. The overall diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of EBUS-TBNA were 91.3%, 100%, 100%, 27.8%, and 91.6% [95% confidence interval (CI): 89.1-93.6%], respectively. In this study, only one case had active bleeding without serious complications during the EBUS-TBNA procedure.

Conclusion

Given its low invasiveness, high diagnostic accuracy, and safety, EBUS-TBNA is worth promoting in thoracic lesions.

Parotid metastasis of rare lung adenocarcinoma: A case report

BACKGROUND

Lung cancer (LC) is the leading cause of malignancy-related deaths worldwide. The most common sites of metastasis include the nervous system, bone, liver, respiratory system, and adrenal glands. LC metastasis in the parotid gland is very rare, and its diagnosis presents a challenge. Here, we report a case of parotid metastasis in primary LC.

CASE SUMMARY

The patient was a 74-year-old male who was discovered to have bilateral facial asymmetry inadvertently two years ago. The right earlobe was slightly swollen and without pain or numbness. Computed tomography (CT) examination showed bilateral lung space-occupying lesions. Pulmonary biopsy was performed and revealed adenocarcinoma (right-upper-lung nodule tissue). Positron emission tomography-CT examination showed: (1) Two hypermetabolic nodules in the right upper lobe of the lung, enlarged hypermetabolic lymph nodes in the right hilar and mediastinum, and malignant space-occupying lesion in the right upper lobe of the lung and possible metastasis to the right hilar and mediastinal lymph nodes; and (2) multiple hypermetabolic nodules in bilateral parotid glands. Parotid puncture biopsy was performed considering lung adenocarcinoma metastasis. Gene detection of lung biopsy specimens revealed an EGFR gene 21 exon L858R mutation.

CONCLUSION

This case report highlights the challenging diagnosis of parotid metastasis in LC given its rare nature. Such lesions should be differentiated from primary tumors of the parotid gland. Simple radiological imaging is unreliable, and puncture biopsy is needed for final diagnosis of this condition.

FDG PET/CT in Solitary Isolated Renal Metastasis From Squamous Cell Lung Cancer

ABSTRACT

We describe FDG PET/CT findings in a patient with a solitary isolated renal metastasis from squamous cell lung cancer. The renal metastasis appeared as a small focus of activity at the renal cortex on FDG PET/CT at initial staging of the lung tumor, misinterpreted as cortical tracer retention, and was significantly enlarged on the second FDG PET/CT performed 4 months after the first PET/CT. This case demonstrates the usefulness of FDG PET/CT in identifying unexpected extrathoracic metastasis from lung cancer. Focal FDG uptake in the renal cortical region in a cancer patient should be evaluated carefully to avoid misdiagnosis.

Introduction to Special Issue Imaging in Cancer Diagnosis

In the field of oncology, the precision of cancer imaging is the cornerstone of oncological patient care [...].

An Investigation of the Relationship Between 18F-FDG PET/CT Parameters of Primary Tumors and Lymph Node Metastasis in Resectable Non-small Cell Lung Cancer

BACKGROUND

Mediastinal lymph node metastasis is an important prognostic factor in non-small cell lung cancer (NSCLC) patients without distant metastases. 18F-2-fluoro-2-deoxy-Dglucose Positron Emission Tomography/Computed Tomography (18F-FDG PET/CT) is recommended for detecting and staging lymph nodes and distant metastases in NSCLC patients.

OBJECTIVE

This study aims to investigate whether maximum standardized uptake (SUVmax), mean standardized uptake (SUVmean), metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) values of the primary tumor measured by 18F-FDG PET/CT in resectable NSCLC can predict preoperative lymph node metastasis.

METHODS

This retrospective study included eighty NSCLC patients who underwent preoperative Positron Emission Tomography/Computed Tomography (PET/CT) for diagnosis and staging. The patients were stage I-III and had no distant metastases. Tumor metabolic parameters such as SUVmax, SUVmean, MTV, and TLG at PET/CT imaging were measured for preoperative diagnosis and staging, and the postoperative pathology results of the patients were examined. The pathology results divided patients with and without lymph node metastasis into two groups. The groups were compared with the student's t-test and chi-square test regarding 18F-FDG PET/CT tumor metabolic parameters and other parameters.

RESULTS

Fifteen (18.8%) patients were female, and 65 (81.3%) were male. According to the postoperative pathology results, while 30 (37.5%) patients had lymph node metastasis, 50 (62.5%) did not. There was a significant difference between the groups regarding tumor SUVmax and SUVmean values (p = 0.036, p = 0.045). Overall survival in the N0 group was significantly higher than in the N1 + N2 group (p = 0.034); median survival was 30.2 months in N0 cases and 27.3 months in N1 and N2 groups.

CONCLUSION

SUVmax and SUVmean values are significantly higher in patients with lymph node metastases than in patients without lymph node metastases, and this finding may provide useful information for predicting lymph node metastasis in patients with resectable NSCLC.

[Research progress on the identification of central lung cancer and atelectasis using multimodal imaging]

Central lung cancer is a common disease in clinic which usually occurs above the segmental bronchus. It is commonly accompanied by bronchial stenosis or obstruction, which can easily lead to atelectasis. Accurately distinguishing lung cancer from atelectasis is important for tumor staging, delineating the radiotherapy target area, and evaluating treatment efficacy. This article reviews domestic and foreign literatures on how to define the boundary between central lung cancer and atelectasis based on multimodal images, aiming to summarize the experiences and propose the prospects.

PET/CT in treatment response assessment in lung cancer. When should it be recommended?

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Different treatment options are now possible both for surgical candidates and for those NSCLC patients deemed not suitable for surgery. Despite the treatments available, only a limited number of less advanced stages are potentially curable, with many patients suffering local recurrence or distant metastases. FDG-PET/CT is commonly used in many centers for post-treatment evaluation, follow-up, or surveillance; Nonetheless, there is no clear consensus regarding the indications in these cases. Based upon the results of a literature review and local expertise from a large lung cancer unit, we built clinical evidence-based recommendations for the use of FDG-PET/CT in response assessment. We found that in general this is not recommended earlier than 3 months from treatment; however, as described in detail the correct timing will also depend upon the type of treatment used. We also present a structured approach to assessing treatment changes when reporting FDG-PET/CT, using visual or quantitative approaches.

Development and validation of 18F-FDG PET/CT radiomics-based nomogram to predict visceral pleural invasion in solid lung adenocarcinoma

OBJECTIVES

This study aimed to establish a radiomics model based on 18F-FDG PET/CT images to predict visceral pleural invasion (VPI) of solid lung adenocarcinoma preoperatively.

METHODS

We retrospectively enrolled 165 solid lung adenocarcinoma patients confirmed by histopathology with 18F-FDG PET/CT images. Patients were divided into training and validation at a ratio of 0.7. To find significant VPI predictors, we collected clinicopathological information and metabolic parameters measured from PET/CT images. Three-dimensional (3D) radiomics features were extracted from each PET and CT volume of interest (VOI). Receiver operating characteristic (ROC) curve was performed to determine the performance of the model. Accuracy, sensitivity, specificity and area under curve (AUC) were calculated. Finally, their performance was evaluated by concordance index (C-index) and decision curve analysis (DCA) in training and validation cohorts.

RESULTS

165 patients were divided into training cohort (n = 116) and validation cohort (n = 49). Multivariate analysis showed that histology grade, maximum standardized uptake value (SUVmax), distance from the lesion to the pleura (DLP) and the radiomics features had statistically significant differences between patients with and without VPI (P < 0.05). A nomogram was developed based on the logistic regression method. The accuracy of ROC curve analysis of this model was 75.86% in the training cohort (AUC: 0.867; C-index: 0.867; sensitivity: 0.694; specificity: 0.889) and the accuracy rate in validation cohort was 71.55% (AUC: 0.889; C-index: 0.819; sensitivity: 0.654; specificity: 0.739).

CONCLUSIONS

A PET/CT-based radiomics model was developed with SUVmax, histology grade, DLP, and radiomics features. It can be easily used for individualized VPI prediction.

Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions

Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative-intent lung resection, and these individuals require adjuvant platinum-etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum-etoposide chemotherapy. Patients with metastatic (extensive-stage) disease are treated with a combination of platinum-etoposide chemotherapy plus immunotherapy with an anti-programmed death-ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum-based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.

Image Quality and Quantitative PET Parameters of Low-Dose [18F]FDG PET in a Long Axial Field-of-View PET/CT Scanner

PET/CT scanners with a long axial field-of-view (LAFOV) provide increased sensitivity, enabling the adjustment of imaging parameters by reducing the injected activity or shortening the acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectability, and the quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min scan time) were included in this analysis. The PET raw data was rebinned for shorter frame durations to simulate 5 min scans with lower activities in the high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n = 82) were assessed using a 5-point Likert scale. The coefficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Subjective image ratings were generally superior in UHS compared to the HS mode. At 0.5 MBq/kg, lesion detectability decreased to 95% (HS) and to 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7 ± 0.6) and 0.5 MBq/kg in UHS (5.5 ± 0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing the [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a LAFOV PET/CT provides diagnostic image quality without statistically significant changes in the uptake parameters. The UHS mode improves image quality, noise, and lesion detectability compared to the HS mode.

Neuroinflammation and Mitochondrial Dysfunction in Parkinson's Disease: Connecting Neuroimaging with Pathophysiology

There is a pressing need for disease-modifying therapies in patients suffering from neurodegenerative diseases, including Parkinson's disease (PD). However, these disorders face unique challenges in clinical trial designs to assess the neuroprotective properties of potential drug candidates. One of these challenges relates to the often unknown individual disease mechanisms that would, however, be relevant for targeted treatment strategies. Neuroinflammation and mitochondrial dysfunction are two proposed pathophysiological hallmarks and are considered to be highly interconnected in PD. Innovative neuroimaging methods can potentially help to gain deeper insights into one's predominant disease mechanisms, can facilitate patient stratification in clinical trials, and could potentially map treatment responses. This review aims to highlight the role of neuroinflammation and mitochondrial dysfunction in patients with PD (PwPD). We will specifically introduce different neuroimaging modalities, their respective technical hurdles and challenges, and their implementation into clinical practice. We will gather preliminary evidence for their potential use in PD research and discuss opportunities for future clinical trials.

Advances in PET imaging of cancer

Molecular imaging has experienced enormous advancements in the areas of imaging technology, imaging probe and contrast development, and data quality, as well as machine learning-based data analysis. Positron emission tomography (PET) and its combination with computed tomography (CT) or magnetic resonance imaging (MRI) as a multimodality PET-CT or PET-MRI system offer a wealth of molecular, functional and morphological data with a single patient scan. Despite the recent technical advances and the availability of dozens of disease-specific contrast and imaging probes, only a few parameters, such as tumour size or the mean tracer uptake, are used for the evaluation of images in clinical practice. Multiparametric in vivo imaging data not only are highly quantitative but also can provide invaluable information about pathophysiology, receptor expression, metabolism, or morphological and functional features of tumours, such as pH, oxygenation or tissue density, as well as pharmacodynamic properties of drugs, to measure drug response with a contrast agent. It can further quantitatively map and spatially resolve the intertumoural and intratumoural heterogeneity, providing insights into tumour vulnerabilities for target-specific therapeutic interventions. Failure to exploit and integrate the full potential of such powerful imaging data may lead to a lost opportunity in which patients do not receive the best possible care. With the desire to implement personalized medicine in the cancer clinic, the full comprehensive diagnostic power of multiplexed imaging should be utilized.

Radiomics of Tumor Heterogeneity in 18F-FDG-PET-CT for Predicting Response to Immune Checkpoint Inhibition in Therapy-Naïve Patients with Advanced Non-Small-Cell Lung Cancer

We aimed to evaluate the predictive and prognostic value of baseline ¹⁸F-FDG-PET-CT (PET-CT) radiomic features (RFs) for immune checkpoint-inhibitor (CKI)-based first-line therapy in advanced non-small-cell lung cancer (NSCLC) patients. In this retrospective study 44 patients were included. Patients were treated with either CKI-monotherapy or combined CKI-based immunotherapy-chemotherapy as first-line treatment. Treatment response was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST). After a median follow-up of 6.4 months patients were stratified into "responder" (n = 33) and "non-responder" (n = 11). RFs were extracted from baseline PET and CT data after segmenting PET-positive tumor volume of all lesions. A Radiomics-based model was developed based on a Radiomics signature consisting of reliable RFs that allow classification of response and overall progression using multivariate logistic regression. These RF were additionally tested for their prognostic value in all patients by applying a model-derived threshold. Two independent PET-based RFs differentiated well between responders and non-responders. For predicting response, the area under the curve (AUC) was 0.69 for "PET-Skewness" and 0.75 predicting overall progression for "PET-Median". In terms of progression-free survival analysis, patients with a lower value of PET-Skewness (threshold < 0.2014; hazard ratio (HR) 0.17, 95% CI 0.06-0.46; p < 0.001) and higher value of PET-Median (threshold > 0.5233; HR 0.23, 95% CI 0.11-0.49; p < 0.001) had a significantly lower probability of disease progression or death. Our Radiomics-based model might be able to predict response in advanced NSCLC patients treated with CKI-based first-line therapy.

Modified signal-to-noise ratio in the liver using the background-to-lung activity ratio to assess image quality of whole-body 18F-fluorodeoxyglucose positron emission tomography

The signal-to-noise ratio in the liver (SNR liver) is commonly used to assess the quality of positron emission tomography (PET) images; however, it is weakly correlated with visual assessments. Conversely, the noise equivalent count (NEC) density showed a strong correlation with visual assessment but did not consider the effects of image reconstruction conditions. Therefore, we propose a new indicator, the modified SNR liver, and plan to verify its usefulness by comparing it with conventional indicators. We retrospectively analyzed 103 patients who underwent whole-body PET/computed tomography (CT). Approximately 60 min after the intravenous injection of ¹⁸F-fluorodeoxyglucose (FDG), the participants were scanned for 2 min/bed. The SNR liver and NEC density were calculated according to the Japanese guidelines for oncology FDG-PET/CT. The modified SNR live was calculated by multiplying the background-to-lung activity ratio by the SNR liver. Patients were classified into groups based on body mass index (BMI) and visual scores. Subsequently, the relationships between these physical indicators, BMI, and visual scores were evaluated. Although the relationship between the modified SNR liver and BMI was inferior to that of NEC density and BMI, the modified SNR liver distinguished the BMI groups more clearly than the conventional SNR liver. Additionally, the modified SNR liver distinguished low visual scores from high scores more accurately than the conventional SNR liver and NEC density. Whether the modified SNR liver is more suitable than the NEC density remains equivocal; however, the modified SNR liver may be superior to the conventional SNR liver for image-quality assessment.

Fibroblast Activation Protein Inhibitor (FAPI)-Based Theranostics-Where We Are at and Where We Are Heading: A Systematic Review

Cancer is the leading cause of death around the globe, followed by heart disease and stroke, with the highest mortality to this day. We have reached great levels of understanding of how these various types of cancer operate at a cellular level and this has brought us to what we call "precision medicine" where every diagnostic examination and the therapeutic procedure is tailored to the patient. FAPI is among the new tracers that can be used to assess and treat many types of cancer. The aim of this review was to gather all the known literature on FAPI theranostics. A MEDLINE search was conducted on four web libraries, PUBMED, Cochrane, Scopus, and Web of Sciences. All of the available articles that included both diagnoses and therapy with FAPI tracers were collected and put through the CASP (Critical Appraisal Skills Programme) questionnaire for systematic reviewing. A total of 8 records were deemed suitable for CASP review, ranging from 2018 to November 2022. These studies were put through the CASP diagnostic checklist, in order to assess the goal of the study, diagnostic and reference tests, results, descriptions of the patient sample, and future applications. Sample sizes were heterogeneous, both for size as well as for tumor type. Only one author studied a single type of cancer with FAPI tracers. Progression of disease was the most common outcome, and no relevant collateral effects were noted. Although FAPI theranostics is still in its infancy and lacks solid grounds to be brought into clinical practice, it does not show any collateral effects that prohibit administration to patients, thus far, and has good tolerability profiles.

First-, Second-, and Third-Generation Radiolabeled Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Positron Emission Tomography: State of the Art, a Systematic Review

Introduction: Lung cancer (LC) is a leading cause of death among men and women, with non-small cell LC (NSCLC) accounting for a substantial portion of the histopathological spectrum and epidermal growth factor receptor (EGFR) mutations being correlated with its manifestation and evolution. Positron emission tomography (PET)/computed tomography has been the most widely used instrument to assess and monitor LC in a noninvasive way, including EGFR-mutated NSCLC, and its course during therapy, indicating to the referring physician the response to ongoing treatment or the lack of it. This systematic review aims to evaluate the feasibility and safety of radiolabeled EGFR tyrosine kinase inhibitors (TKis) in PET in clinical practice. Materials and Methods: From 1999 to April 2022 a Medline search was conducted on four different databases such as PubMed, Cochrane Library, Scopus, and Web of Sciences. Clinical studies were assessed by Quality Assessment of Diagnostic accuracy Studies-2 (QUADAS-2) and preclinical studies were also reported in this review. Results: Nine clinical studies were QUADAS-2 assessed and risk-of-bias assessment, and it turned out acceptable as two out of eight studies had low risk of bias in all four domains for risk-of-bias assessment, and the other four studies had three low-risk domains. The overall assessment for applicability risks was low. Conclusions: Radiolabeled EGFR-TKis in PET are a valid tool in identifying patients who may benefit from TKi therapy and who may not as a means to start an effective treatment. Although the number of clinical studies conducted so far is meager, these new PET tracers are already proving to be very useful in clinical settings as patient prognosis can be better assessed.

Positron emission tomography imaging of lung cancer: An overview of alternative positron emission tomography tracers beyond F18 fluorodeoxyglucose

Lung cancer has been the leading cause of cancer-related mortality in China in recent decades. Positron emission tomography-computer tomography (PET/CT) has been established in the diagnosis of lung cancer. ¹⁸F-FDG is the most widely used PET tracer in foci diagnosis, tumor staging, treatment planning, and prognosis assessment by monitoring abnormally exuberant glucose metabolism in tumors. However, with the increasing knowledge on tumor heterogeneity and biological characteristics in lung cancer, a variety of novel radiotracers beyond ¹⁸F-FDG for PET imaging have been developed. For example, PET tracers that target cellular proliferation, amino acid metabolism and transportation, tumor hypoxia, angiogenesis, pulmonary NETs and other targets, such as tyrosine kinases and cancer-associated fibroblasts, have been reported, evaluated in animal models or under clinical investigations in recent years and play increasing roles in lung cancer diagnosis. Thus, we perform a comprehensive literature review of the radiopharmaceuticals and recent progress in PET tracers for the study of lung cancer biological characteristics beyond glucose metabolism.

Application of diffusion kurtosis imaging and 18F-FDG PET in evaluating the subtype, stage and proliferation status of non-small cell lung cancer

Background

Lung cancer has become one of the deadliest tumors in the world. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for approximately 80%-85% of all lung cancer cases. This study aimed to investigate the value of diffusion kurtosis imaging (DKI), diffusion-weighted imaging (DWI) and 2-[¹⁸F]-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸F-FDG PET) in differentiating squamous cell carcinoma (SCC) and adenocarcinoma (AC) and to evaluate the correlation of each parameter with stage and proliferative status Ki-67.

Methods

Seventy-seven patients with lung lesions were prospectively scanned by hybrid 3.0-T chest ¹⁸F-FDG PET/MR. Mean kurtosis (MK), mean diffusivity (MD), apparent diffusion coefficient (ADC), maximum standard uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. The independent samples t test or Mann–Whitney U test was used to compare and analyze the differences in each parameter of SCC and AC. The diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve analysis and compared with the DeLong test. A logistic regression analysis was used for the evaluation of independent predictors. Bootstrapping (1000 samples) was performed to establish a control model, and calibration curves and ROC curves were used to validate its performance. Pearson’s correlation coefficient and Spearman’s correlation coefficient were calculated for correlation analysis.

Results

The MK and ADC values of the AC group were significantly higher than those of the SCC group (all P< 0.05), and the SUVmax, MTV, and TLG values of the SCC group were significantly higher than those of the AC group (all P<0.05). There was no significant difference in the MD value between the two groups. Moreover, MK, SUVmax, TLG and MTV were independent predictors of the NSCLC subtype, and the combination of these parameters had an optimal diagnostic efficacy (AUC, 0.876; sensitivity, 86.27%; specificity, 80.77%), which was significantly better than that of MK (AUC = 0.758, z = 2.554, P = 0.011), ADC (AUC = 0.679, z = 2.322, P = 0.020), SUVmax (AUC = 0.740, z = 2.584, P = 0.010), MTV (AUC = 0.715, z = 2.530, P = 0.011) or TLG (AUC = 0.716, z = 2.799, P = 0.005). The ROC curve showed that the validation model had high accuracy in identifying AC and SCC (AUC, 0.844; 95% CI, 0.785-0.885);. The SUVmax value was weakly positively correlated with the Ki-67 index (r = 0.340, P< 0.05), the ADC and MD values were weakly negatively correlated with the Ki-67 index (r = -0.256, -0.282, P< 0.05), and the MTV and TLG values were weakly positively correlated with NSCLC stage (r = 0.342, 0.337, P< 0.05).

Conclusion

DKI, DWI and ¹⁸F-FDG PET are all effective methods for assessing the NSCLC subtype, and some parameters are correlated with stage and proliferation status.

The combined role of PET/CT metabolic parameters and inflammatory markers in detecting extensive disease in small cell lung cancer

The combined role of inflammatory markers [including neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), and systemic immune-inflammation index (SII)] and PET/CT metabolic parameters [including maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and TLG (total lesion glycolysis)] at baseline in evaluating the binary stage [extensive-stage disease (ED) and limited-stage disease (LD)] of small cell lung cancer (SCLC) is unclear. In this study, we verified that high metabolic parameters and inflammatory markers were related to the binary stage of SCLC patients, respectively (p &lt; 0.05). High inflammatory markers were also associated with high MTV and TLG in patients with SCLC (p &lt; 0.005). Moreover, the incidences of co-high metabolic parameters and inflammatory markers were higher in ED-SCLC (p &lt; 0.05) than those in LD-SCLC. Univariate logistic regression analysis demonstrated that Co-high MTV/NLR, Co-high MTV/MLR, Co-high MTV/SII, Co-high TLG/NLR, Co-high TLG/MLR, and Co-high TLG/SII were significantly related to the binary stage of SCLC patients (p = 0.00). However, only Co-high MTV/MLR was identified as an independent predictor for ED-SCLC (odds ratio: 8.67, 95% confidence interval CI: 3.51–21.42, p = 0.000). Our results suggest that co-high metabolic parameters and inflammatory markers could be of help for predicting ED-SCLC at baseline. Together, these preliminary findings may provide new ideas for more accurate staging of SCLC.

Cryo-Biopsy versus 19G needle versus 22G needle with EBUS-TBNA endoscopy

Introduction: We have been using cryo-biopsy for endobronchial lesions for lung cancer diagnosis and debulking. Cryo-biopsy is also known to be an excellent tool for diagnosis of lung interstitial disease. Recently cryo-biopsy with the 1.1mm probe was used for lymphnode biopsy.

Patients and Methods: 311 patients participated with lymphadenopathy and at least one lung lesion. The following tools were used for diagnosis; 22G Mediglobe Sonotip, 22G Medigolbe, 21G Olympus, 19G Olympus and 1.1mm cryo probe ERBE CRYO 2 system (3 seconds froze). A PENTAX Convex-probe EBUS was used for biopsy guidance.

Results: Cell-blocks slices had a higher number in the 19G needle group (19G> Cryo Probe>22G Mediglobe Sonotip >21G Olympus >22G Mediglobe).

Conclusion: Cryo biopsy of the lymphnodes is safe with the 1.1mm cryo probe. Further studies are needed in order to evaluate new probes and the technique specifications.

Deep Learning-Based Chest CT Image Features in Diagnosis of Lung Cancer

This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed with lung cancer by surgery or puncture in hospital were selected as the research subjects. The Mask Region Convolutional Neural Network (Mask-RCNN) model was a typical end-to-end image segmentation model, and Dual Path Network (DPN) was used in nodule detection. The results showed that the accuracy of DPN algorithm model in detecting lung lesions in lung cancer patients was 88.74%, the accuracy of CT diagnosis of lung cancer was 88.37%, the sensitivity was 82.91%, and the specificity was 87.43%. Deep learning-based CT examination combined with serum tumor detection, factoring into Neurospecific enolase (N S E), cytokeratin 19 fragment (CYFRA21), Carcinoembryonic antigen (CEA), and squamous cell carcinoma (SCC) antigen, improved the accuracy to 97.94%, the sensitivity to 98.12%, and the specificity to 100%, all showing significant differences (P < 0.05). In conclusion, this study provides a scientific basis for improving the diagnostic efficiency of CT imaging in lung cancer and theoretical support for subsequent lung cancer diagnosis and treatment.

Evaluation of PD-L1 Expression Level in Patients With Non-Small Cell Lung Cancer by 18F-FDG PET/CT Radiomics and Clinicopathological Characteristics

PURPOSE

In the present study, we aimed to evaluate the expression of programmed death-ligand 1 (PD-L1) in patients with non-small cell lung cancer (NSCLC) by radiomic features of 18F-FDG PET/CT and clinicopathological characteristics.

METHODS

A total 255 NSCLC patients (training cohort: n = 170; validation cohort: n = 85) were retrospectively enrolled in the present study. A total of 80 radiomic features were extracted from pretreatment 18F-FDG PET/CT images. Clinicopathologic features were compared between the two cohorts. The least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful prognostic features in the training cohort. Radiomics signature and clinicopathologic risk factors were incorporated to develop a prediction model by using multivariable logistic regression analysis. The receiver operating characteristic (ROC) curve was used to assess the prognostic factors.

RESULTS

A total of 80 radiomic features were extracted in the training dataset. In the univariate analysis, the expression of PD-L1 in lung tumors was significantly correlated with the radiomic signature, histologic type, Ki-67, SUVmax, MTV, and TLG (p< 0.05, respectively). However, the expression of PD-L1 was not correlated with age, TNM stage, and history of smoking (p> 0.05). Moreover, the prediction model for PD-L1 expression level over 1% and 50% that combined the radiomic signature and clinicopathologic features resulted in an area under the curve (AUC) of 0.762 and 0.814, respectively.

CONCLUSIONS

A prediction model based on PET/CT images and clinicopathological characteristics provided a novel strategy for clinicians to screen the NSCLC patients who could benefit from the anti-PD-L1 immunotherapy.