Role of PET/CT for precision medicine in lung cancer: perspective of the Society of Nuclear Medicine and Molecular Imaging

Modern era systemic therapies: Expanding concepts of cure in early and locally advanced non-small cell lung cancer

Cure of cancer is a sensitive and multidimensional concept that is challenging to define, difficult to assert at the individual patient level, and often surrounded by controversy. The notion of cure in non-small cell lung cancer (NSCLC) has changed and continues to evolve with improvements in diagnosis and treatment. Targeted and immune therapies have recently entered the treatment landscape of stage I-III NSCLC. While some initial pivotal trials of such agents failed to improve survival, recently approved epidermal growth factor receptor (EGFR) inhibitors (in EGFR-mutated NSCLC) and immune checkpoint inhibitors have shown delays in disease recurrence or progression and unprecedented survival gains compared to previous standards of care. Additional data is now emerging supporting the benefit of treatment strategies based on alternation-matched targeting (anaplastic lymphoma kinase [ALK] inhibition in ALK-altered disease) and immune checkpoint inhibition in stage I-III NSCLC. Similar to previous developments in the treatment of early and locally advanced NSCLC, it is expected that statistically significant and clinically meaningful trial-level benefits will translate into real-world benefits, including improvements in cure measures. Parallel advances in molecular testing (e.g., circulating tumor DNA analyses) are also allowing for a deeper and more comprehensive characterization of disease status and treatment response. Given the impact that curative-intent treatments have on survival, it is critical that various stakeholders, including clinicians and patients, are aware of new opportunities to pursue cure in stage I-III NSCLC.

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.

CYFRA 21-1, CA 125 and CEA provide additional prognostic value in NSCLC patients with stable disease at first CT scan

BACKGROUND

Serum tumor markers (STM) may complement imaging and provide additional clinical information for patients with non-small cell lung cancer (NSCLC).

OBJECTIVE

To determine whether STMs can predict outcomes in patients with stable disease (SD) after initial treatment.

METHODS

This single-center, prospective, observational trial enrolled 395 patients with stage III/IV treatment-naïve NSCLC; of which 263 patients were included in this analysis. Computed Tomography (CT) scans were performed and STMs measured before and after initial treatment (two cycles of chemotherapy and/or an immune checkpoint inhibitor or tyrosine kinase inhibitor); analyses were based on CT and STM measurements obtained at first CT performed after cycle 2 only PFS and OS were analyzed by Kaplan-Meier curves and Cox-proportional hazard models.

RESULTS

When patients with SD (n = 100) were split into high- and low-risk groups based on CYFRA 21-1, CEA and CA 125 measurements using an optimized cut-off, a 4-fold increase risk of progression or death was estimated for high- vs low-risk SD patients (PFS, HR 4.17; OS, 3.99; both p < 0.0001). Outcomes were similar between patients with high-risk SD or progressive disease (n = 35) (OS, HR 1.17) and between patients with low-risk SD or partial response (n = 128) (PFS, HR 0.98; OS, 1.14).

CONCLUSIONS

STMs can provide further guidance in patients with indeterminate CT responses by separating them into high- and low-risk groups for future PFS and OS events.

Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment

Non-small cell lung cancer (NSCLC) is a significant public health concern with high mortality rates. Recent advancements in genomic data, bioinformatics tools, and the utilization of biomarkers have improved the possibilities for early diagnosis, effective treatment, and follow-up in NSCLC. Biomarkers play a crucial role in precision medicine by providing measurable indicators of disease characteristics, enabling tailored treatment strategies. The integration of big data and artificial intelligence (AI) further enhances the potential for personalized medicine through advanced biomarker analysis. However, challenges remain in the impact of new biomarkers on mortality and treatment efficacy due to limited evidence. Data analysis, interpretation, and the adoption of precision medicine approaches in clinical practice pose additional challenges and emphasize the integration of biomarkers with advanced technologies such as genomic data analysis and artificial intelligence (AI), which enhance the potential of precision medicine in NSCLC. Despite these obstacles, the integration of biomarkers into precision medicine has shown promising results in NSCLC, improving patient outcomes and enabling targeted therapies. Continued research and advancements in biomarker discovery, utilization, and evidence generation are necessary to overcome these challenges and further enhance the efficacy of precision medicine. Addressing these obstacles will contribute to the continued improvement of patient outcomes in non-small cell lung cancer.

False Positive Positron Emission Tomography/Computed Tomography (PET/CT) Requiring Biopsy for Proper Staging of Lung Cancer

Lung cancer is the leading cause of cancer death in women in developed countries. Staging is crucial in determining the treatment modality. Different treatment modalities for lung cancer include surgery, radiation therapy, and chemotherapy. PET/CT is the most sensitive and accurate modality for detecting hilar, mediastinal, and metastatic disease except in the brain. PET/CT scan often upstages the disease. PET/CT has also been shown to have false positive results. We present the case of a 72-year-old female who had a false positive finding on PET/CT, which would have changed the management process and outcome of her disease.

Endoscopic Technologies for Peripheral Pulmonary Lesions: From Diagnosis to Therapy

Peripheral pulmonary lesions (PPLs) are frequent incidental findings in subjects when performing chest radiographs or chest computed tomography (CT) scans. When a PPL is identified, it is necessary to proceed with a risk stratification based on the patient profile and the characteristics found on chest CT. In order to proceed with a diagnostic procedure, the first-line examination is often a bronchoscopy with tissue sampling. Many guidance technologies have recently been developed to facilitate PPLs sampling. Through bronchoscopy, it is currently possible to ascertain the PPL's benign or malignant nature, delaying the therapy's second phase with radical, supportive, or palliative intent. In this review, we describe all the new tools available: from the innovation of bronchoscopic instrumentation (e.g., ultrathin bronchoscopy and robotic bronchoscopy) to the advances in navigation technology (e.g., radial-probe endobronchial ultrasound, virtual navigation, electromagnetic navigation, shape-sensing navigation, cone-beam computed tomography). In addition, we summarize all the PPLs ablation techniques currently under experimentation. Interventional pulmonology may be a discipline aiming at adopting increasingly innovative and disruptive technologies.

Glycolytic Plasticity of Metastatic Lung Cancer Captured by Noninvasive 18F-FDG PET/CT and Serum 1H-NMR Analysis: An Orthotopic Murine Model Study

We aim to establish a noninvasive diagnostic platform to capture early phenotypic transformation for metastasis using 18F-FDG PET and 1H-NMR-based serum metabolomics. Mice with implantation of NCI-H460 cells grew only primary lung tumors in the localized group and had both primary and metastatic lung tumors in the metastatic group. The serum metabolites were analyzed using 1H-NMR at the time of PET/CT scan. The glycolysis status and cell proliferation were validated by Western blotting and staining. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of SUVmean and serum metabolites in metastasis. In the metastatic mice, the SUVmean of metastatic tumors was significantly higher than that of primary lung tumors in PET images, which was supported by elevated glycolytic protein expression of HK2 and PKM2. The serum pyruvate level in the metastatic group was significantly lower than that in the localized group, corresponding to increased pyruvate-catalyzed enzyme and proliferation rates in metastatic tumors. In diagnosing localized or metastatic tumors, the areas under the ROC curves of SUVmean and pyruvate were 0.92 and 0.91, respectively, with p < 0.05. In conclusion, the combination of 18F-FDG PET and 1H-NMR-based serum metabolomics demonstrated the feasibility of a glycolytic platform for diagnosing metastatic lung cancers.

FDG PET and CT radiomics in diagnosis and prognosis of non-small-cell lung cancer

BACKGROUND

18F-FDG PET and CT radiomics has been the object of a wide research for over 20 years but its contribution to clinical practice remains not yet well established. We have investigated its impact versus that of only histo-clinical data, for the routine management of non-small-cell lung cancer (NSCLC).

METHODS

Our patients were retrospectively considered. They all had a FDG PET-CT and immuno-histo-chemistry (IHC) to assess PD-L1 expression at the beginning of the disease. A prognosis univariate and multivariate Cox survival analyses was performed for overall survival (OS) and progression free survival (PFS) prediction, including a training/testing procedure. Two sets of 47 PET and 47 CT radiomics features (RFs) were extracted. Difference between RFs according to PD-L1 expression, the histology status and the stage level were tested using suited non parametric statistical tests and the receiver operating characteristics (ROC) curve and the area under curve (AUC).

RESULTS

From 2017 to 2019, 212 NSCLC patients treated in our institution were included. The main conventional prognostic variables were stage and gender with a low added prognostic value in the models including PET and CT RFs. Neither PET nor CT RFs were significant to separate the different levels of PD-L1 expression. Several RFs differ between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) tumours and a large number of PET and CT RFs are significantly linked to patient stage.

CONCLUSIONS

In our population, PET and CT RFs show their intrinsic power to predict survival but do not significantly improve OS and PFS prediction in the different multivariate models, in comparison to conventional data. It would seem necessary to carry out one's own survival analysis before determining a radiomics signature.

Primary Extra-Pleura Leiomyoma: A Case Report and Literature Review

Leiomyomas are a common type of benign soft tissue tumor arising from smooth muscle, most often occurring within females’ genitourinary and gastrointestinal tract. However, primary leiomyomas of the chest wall residing in the extra-pleural space are an extremely rare subset of leiomyomatous lesion presentation. We present a case of a fifty-two-year-old male who initially presented complaining of dyspnea worsening with exertion. Computed tomography imaging was performed showing an extra-pleural mass residing under the left sixth rib. Subsequent core needle biopsy and immunohistochemical staining were performed, and the definitive diagnosis of primary leiomyoma of the posterior mediastinal chest wall. Although extremely rare, this neoplastic condition should be included in your differential diagnosis when diagnostic imaging reveals a benign mass residing in the extra-pleural space, and subsequent biopsy specimens consist of smooth muscle fibers.

A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging

Over the past few years, positron emission tomography/computed tomography (PET/CT) imaging for computer-aided diagnosis has received increasing attention. Supervised deep learning architectures are usually employed for the detection of abnormalities, with anatomical localization, especially in the case of CT scans. However, the main limitations of the supervised learning paradigm include (i) large amounts of data required for model training, and (ii) the assumption of fixed network weights upon training completion, implying that the performance of the model cannot be further improved after training. In order to overcome these limitations, we apply a few-shot learning (FSL) scheme. Contrary to traditional deep learning practices, in FSL the model is provided with less data during training. The model then utilizes end-user feedback after training to constantly improve its performance. We integrate FSL in a U-Net architecture for lung cancer lesion segmentation on PET/CT scans, allowing for dynamic model weight fine-tuning and resulting in an online supervised learning scheme. Constant online readjustments of the model weights according to the user's feedback, increase the detection and classification accuracy, especially in cases where low detection performance is encountered. Our proposed method is validated on the Lung-PET-CT-DX TCIA database. PET/CT scans from 87 patients were included in the dataset and were acquired 60 minutes after intravenous¹⁸F-FDG injection. Experimental results indicate the superiority of our approach compared to other state of the art methods.

Tumor angiogenesis at baseline identified by 18F-Alfatide II PET/CT may predict survival among patients with locally advanced non-small cell lung cancer treated with concurrent chemoradiotherapy

Background

The study investigated the predictive value of tumor angiogenesis observed by ¹⁸F-ALF-NOTA-PRGD2 II (denoted as ¹⁸F-Alfatide II) positron emission tomography (PET)/computed tomography (CT) before concurrent chemoradiotherapy (CCRT) for treatment response and survival among patients with locally advanced non-small cell lung cancer (LA-NSCLC).

Methods

Patients with unresectable stage IIIA or IIIB NSCLC (AJCC Cancer Staging 7th Edition) who received CCRT were included in this prospective study. All patients had undergone ¹⁸F-Alfatide PET/CT scanning before CCRT, and analyzed parameters included maximum uptake values (SUV_max) of primary tumor (SUV_P) and metastatic lymph nodes (SUV_LN) and mean uptake value of blood pool (SUV_blood). Tumor-to-background ratios (TBRs) and changes in tumor diameter before and after CCRT (ΔD) were calculated. The ratios of SUV_P to SUV_blood, SUV_LN to SUV_blood, and SUV_P to SUV_LN were denoted as TBR_P, TBR_LN, and T/LN. Short-term treatment response, progression-free survival (PFS), and overall survival (OS) were evaluated.

Results

Of 38 enrolled patients, 28 completed CCRT. SUV_P, SUV_LN, TBR_P, TBR_LN and T/LN showed significant correlation with PFS (all P < 0.05). SUV_P was negatively correlated with OS (P = 0.005). SUV_P and TBR_P were higher in non-responders than in responders (6.55 ± 2.74 vs. 4.61 ± 1.94, P = 0.039; 10.49 ± 7.58 vs. 7.73 ± 6.09, P = 0.023). ΔD was significantly greater in responders (2.78 ± 1.37) than in non-responders (-0.16 ± 1.33, P < 0.001). Exploratory receiver operating characteristic curve analysis identified TBR_P (area under the curve [AUC] = 0.764, P = 0.018), with a cutoff value of 6.52, as the only parameter significantly predictive of the response to CCRT, with sensitivity, specificity, and accuracy values of 71.43%, 78.57%, and 75.00%, respectively. ROC curve analysis also identified SUV_P (AUC = 0.942, P < 0.001, cutoff value 4.64) and TBR_P (AUC = 0.895, P = 0.001, cutoff value 4.95) as predictive of OS with high sensitivity (84.21%, 93.75%), specificity (100.00%, 66.67%), and accuracy (89.29%, 82.14%).

Conclusions

Evaluation of tumor angiogenesis by ¹⁸F-Alfatide II at baseline may be useful in predicting the short-term response to CCRT as well as PFS and OS in patients with LA-NSCLC.

PET Use in Cancer Diagnosis, Treatment, and Prognosis

Tumorigenesis is a multistep process marked by variations in numerous metabolic pathways that affect cellular architectures and functions. Cancer cells reprogram their energy metabolism to enable several basic molecular functions, including membrane biosynthesis, receptor regulations, bioenergetics, and redox stress. In recent years, cancer diagnosis and treatment strategies have targeted these specific metabolic changes and the tumor's interactions with its microenvironment. Positron emission tomography (PET) captures all molecular alterations leading to abnormal function and cancer progression. As a result, the development of PET radiotracers increasingly focuses on irregular biological pathways or cells that overexpress receptors that have the potential to function as biomarkers for early diagnosis and treatment measurements as well as research. This chapter reviews both established and evolving PET radiotracers used to image tumor biology. We have also included a few advantages and disadvantages of the routinely used PET radiotracers in cancer imaging.

Habitat Imaging-Based 18F-FDG PET/CT Radiomics for the Preoperative Discrimination of Non-small Cell Lung Cancer and Benign Inflammatory Diseases

Purpose

To propose and evaluate habitat imaging-based ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) radiomics for preoperatively discriminating non-small cell lung cancer (NSCLC) and benign inflammatory diseases (BIDs).

Methods

Three hundred seventeen ¹⁸F-FDG PET/CT scans were acquired from patients who underwent aspiration biopsy or surgical resection. All volumes of interest (VOIs) were semiautomatically segmented. Each VOI was separated into variant subregions, namely, habitat imaging, based on our adapted clustering-based habitat generation method. Radiomics features were extracted from these subregions. Three feature selection methods and six classifiers were applied to construct the habitat imaging-based radiomics models for fivefold cross-validation. The radiomics models whose features extracted by conventional habitat-based methods and nonhabitat method were also constructed. For comparison, the performances were evaluated in the validation set in terms of the area under the receiver operating characteristic curve (AUC). Pairwise t-test was applied to test the significant improvement between the adapted habitat-based method and the conventional methods.

Results

A total of 1,858 radiomics features were extracted. After feature selection, habitat imaging-based ¹⁸F-FDG PET/CT radiomics models were constructed. The AUC of the adapted clustering-based habitat radiomics was 0.7270 ± 0.0147, which showed significantly improved discrimination performance compared to the conventional methods (p <.001). Furthermore, the combination of features extracted by our adaptive habitat imaging-based method and non-habitat method showed the best performance than the other combinations.

Conclusion

Habitat imaging-based ¹⁸F-FDG PET/CT radiomics shows potential as a biomarker for discriminating NSCLC and BIDs, which indicates that the microenvironmental variations in NSCLC and BID can be captured by PET/CT.

Development of Dual Receptor Enhanced Pre-Targeting Strategy-A Novel Promising Technology for Immuno-Positron Emission Tomography Imaging

PET imaging has become an important diagnostic tool in the era of precise medicine. Various pre-targeting systems have been reported to address limitations associated with traditional immuno-PET. However, the application of these mono-receptor based pre-targeting (MRPT) strategies is limited to non-internalizable antibodies, and the tumor uptake is usually much lower than that in the corresponding immuno-PET. To circumvent these limitations, we develop the first Dual-Receptor Pre-Targeting (DRPT) system through entrapping the tumor-receptor-specific radioligand by the pre-administered antibody. Besides the similar ligation pathway happens in MRPT, incorporation of a tumor-receptor-specific peptide into the radioligand in DRPT enhances both concentration and retention of the radioligand on tumor, promoting its ligation with pre-administered mAb on cell-surface and/or internalized into tumor-cells. In this study, 64Cu based DRPT shows superior performance over corresponding MRPT and immuno-PET using internalizable antibodies. Besides, the compatibility of DRPT with short-lived and generator-produced 68Ga is demonstrated, leveraging its advantage in reducing radio-dose exposure. Furthermore, the feasibility of reducing the amount of the pre-administered antibody is confirmed, indicating the cost saving potential of DRPT. In summary, synergizing advantages of dual-receptor targeting and pre-targeting, we expect that this DRPT strategy can become a breakthrough technology in the field of antibody-based molecular imaging.

The expression of miRNA-216b is negatively correlated with 18F-FDG uptake in non-small cell lung cancer

Background

This study aimed to investigate the correlation between miRNA-216b expression in patients with non-small cell lung cancer (NSCLC) and ¹⁸F-fluorodeoxyglucose (FDG) uptake by PET/CT and to explore the clinical application value of 18F-FDG PET/CT in miRNA-216b based on therapy for NSCLC.

Methods

Eighty patients with NSCLC and 40 healthy subjects were enrolled in our study. The SUVmax of the lesion area by PET/CT imaging was calculated. SUVmax represented the highest concentration of 18F-FDG in the lesion. The expression of miRNA-216b in the plasma and fiber bronchoscopic puncture of NSCLC patients was detected by RT qPCR. Then Pearson correlation analysis was used to analyze the correlation between miRNA-216b expression and 18F-FDG uptake in patients with different types of NSCLC.

Results

Compared with healthy subjects, SUVmax of early adenocarcinoma and advanced adenocarcinoma were increased. Compared with healthy subjects, SUVmax of early squamous and advanced squamous were increased. And the SUVmax content of advanced adenocarcinoma and squamous cell carcinoma was higher than that of early adenocarcinoma and squamous cell carcinoma. Compared with healthy subjects, the expression of miRNA-216b in the plasma of patients with early and advanced adenocarcinoma was reduced, and the expression of miRNA-216b in the plasma of patients with early and advanced squamous cell carcinoma was reduced. Compared with adjacent tissues, the expression of miRNA-216b in early adenocarcinoma tissues and advanced adenocarcinoma tissues was reduced, and the expression in early squamous cell carcinoma and advanced squamous cell carcinoma was reduced. Pearson correlation analysis showed a negative correlation between SUVmax and miRNA-216b (plasma and tissue) in patients with four types of NSCLC.

Conclusion

miRNA-216b expression was negatively correlated with ¹⁸F-FDG uptake in NSCLC. miRNA-216b could be used for the classification and staging of non-small cell lung cancer. ¹⁸F-FDG PET/CT may be used to evaluate the therapeutic response in application of miRNA-216b-based cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02376-2.

PET/CT-Guided Biopsy of Suspected Lung Lesions Requires Less Rebiopsy Than CT-Guided Biopsy Due to Inconclusive Results

The purpose of this study was to compare 18F-FDG PET/CT and CT performance in guiding percutaneous biopsies with histologic confirmation of lung lesions. Methods: We prospectively evaluated 341 patients, of whom 216 underwent 18F-FDG PET/CT-guided biopsy and 125 underwent CT-guided biopsy. The pathology results, lesion size, complications, and rebiopsy rate in the 2 groups were evaluated. Results: Of the 216 biopsies with PET/CT guidance, histology demonstrated 170 lesions (78.7%) to be malignant and 46 (21.3%) to be benign. In the CT-guided group, of 125 lesions, 77 (61.6%) were malignant and 48 (38.4%) were benign (P = 0.001). Inconclusive results prompted the need for a second biopsy in 18 patients: 13 of 125 (10.4%) in the CT group and 5 of 216 (2.3%) in PET group (P = 0.001). Complications were pneumothorax (13.2%), hemothorax (0.8%), and hemoptysis (0.6%). No life-threatening adverse events or fatalities were reported. The difference in complication rates between the 2 groups was not significant (P = 0.6). Malignant lesions showed a greater mean size than benign lesions regardless of the group (P = 0.015). Conclusion: PET/CT-guided biopsy of lung lesions led to fewer inconclusive biopsies than CT-guided biopsy, with similar complication rates.

The predictive power of artificial intelligence on mediastinal lymphnode metastasis

OBJECTIVE

The aim of this study was to create the preoperative predictive model on mediastinal lymph-node metastasis based on artificial intelligence in surgically resected lung adenocarcinoma.

METHODS

We enrolled 301 surgical resections of patients with clinical stage N0-1 lung adenocarcinoma, who received positron emission tomography preoperatively between 2015 and 2019. We randomly assigned the patients into two groups: the training (n = 201) and validation groups (n = 100). The training group was used to obtain basic data for learning by artificial intelligence, whereas the validation group was used to verify the constructed algorithm. We used an automatic machine learning platform, to create artificial intelligence model. For comparison, multivariate analysis was performed in the training group, whereas for calculating and verifying the prediction accuracy rate, significant predicting factors were applied to the validation group.

RESULTS

Of the 301 patients, 41 patients were diagnosed as mediastinal lymph node metastasis. In multivariate analysis, the maximum standardized uptake value was an individual predictive factor. The accuracy rate of artificial intelligence model was 84%, and the specificity was 98% which were higher than those of the maximum standardized uptake value (61% and 57%). However, in terms of sensitivity, artificial intelligence model remarked low at 12%.

CONCLUSIONS

An artificial intelligence-based diagnostic algorithm showed remarkable specificity compared with the maximum standardized uptake value. Although this model is not ready to practical use and the result was preliminary because of poor sensitivity, artificial intelligence could be able to complement the shortcomings of existing diagnostic modalities.

"PET/CT Variants and Pitfalls in Lung Cancer and Mesothelioma"

2-deoxy-2-[¹⁸F]fluoro-D-glucose [¹⁸F]FDG-PET/CT represents the metabolic imaging of choice in various cancer types. Used either at diagnosis or during treatment response assessment, the modality allows for a more accurate definition of tumor extent compared to morphological imaging and is able to predict the therapeutic benefit earlier in time. Due to the aspecific uptake property of [¹⁸F]FDG there is an overlap of its distribution in normal and pathological conditions, which can make the interpretation of the imaging challenging. Lung and pleural neoplasia are no exception to this, thus acknowledging of possible pitfalls and artifacts are mandatory for image interpretation. While most pitfalls and artifacts are common for all indications with metabolic imaging with [¹⁸F]FDG-PET/CT, there are specific variants and pitfalls in lung cancer and malignant pleural mesothelioma. The aim of the present article is to shed light on the most frequent and relevant variants and pitfalls in [¹⁸F]FDG-PET/CT imaging in lung cancer and malignant pleural mesothelioma.

miRNAs in lung cancer. A systematic review identifies predictive and prognostic miRNA candidates for precision medicine in lung cancer

Lung cancer (LC) is the leading cause of cancer-related death worldwide and miRNAs play a key role in LC development. To better diagnose LC and to predict drug treatment responses we evaluated 228 articles encompassing 16,697 patients and 12,582 healthy controls. Based on the criteria of ≥3 independent studies and a sensitivity and specificity of >0.8 we found blood-borne miR-20a, miR-10b, miR-150, and miR-223 to be excellent diagnostic biomarkers for non-small cell LC whereas miR-205 is specific for squamous cell carcinoma. The systematic review also revealed 38 commonly regulated miRNAs in tumor tissue and the circulation, thus enabling the prediction of histological subtypes of LC. Moreover, theranostic biomarker candidates with proven responsiveness to checkpoint inhibitor treatments were identified, notably miR-34a, miR-93, miR-106b, miR-181a, miR-193a-3p, and miR-375. Conversely, miR-103a-3p, miR-152, miR-152-3p, miR-15b, miR-16, miR-194, miR-34b, and miR-506 influence programmed cell death-ligand 1 and programmed cell death-1 receptor expression, therefore providing a rationale for the development of molecularly targeted therapies. Furthermore, miR-21, miR-25, miR-27b, miR-19b, miR-125b, miR-146a, and miR-210 predicted response to platinum-based treatments. We also highlight controversial reports on specific miRNAs. In conclusion, we report diagnostic miRNA biomarkers for in-depth clinical evaluation. Furthermore, in an effort to avoid unnecessary toxicity we propose predictive biomarkers. The biomarker candidates support personalized treatment decisions of LC patients and await their confirmation in randomized clinical trials.

FDG-Avid Lung Nodule Formation by the Use of Hemostatic Powder: A Potential Cause of False-Positive FDG PET/CT

ABSTRACT

FDG PET/CT is used in the diagnosis and follow-up of various malignant tumors and changes patient management in routine clinical practice. However, inflammatory, infectious, physiological, and technical causes and benign pathological conditions may lead to false-positive FDG uptake. We report a case of a 59-year-old man who was considered having a false-positive FDG-PET pulmonary nodular lesion in favor of metastasis, which was formed by the use of hemostatic powder.

PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients

Despite the recent advances in lung cancer biology, molecular pathology, and treatment, this malignancy remains the leading cause of cancer-related death worldwide and non-small cell lung cancer (NSCLC) is the most common form found at diagnosis. Accurate staging of the disease is a fundamental prognostic factor that correctly predicts progression-free (PFS) and overall survival (OS) of NSCLC patients. However, outcome of patients within each TNM staging group can change widely highlighting the need to identify additional prognostic biomarkers to better stratify patients on the basis of risk. 18F-FDG PET/CT plays an essential role in staging, evaluation of treatment response, and tumoral target delineation in NSCLC patients. Moreover, a number of studies showed the prognostic role of imaging parameters derived from PET images, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). These parameters represent three-dimensional PET-based measurements providing information on both tumor volume and metabolic activity and previous studies reported their ability to predict OS and PFS of NSCLC patients. This review will primarily focus on the studies that showed the prognostic and predictive role of MTV and TLG in NSCLC patients, addressing also their potential utility in the new era of immunotherapy of NSCLC.

Recent and Current Advances in FDG-PET Imaging within the Field of Clinical Oncology in NSCLC: A Review of the Literature

Lung cancer is the leading cause of cancer-related deaths around the world, the most common type of which is non-small-cell lung cancer (NSCLC). Computed tomography (CT) is required for patients with NSCLC, but often involves diagnostic issues and large intra- and interobserver variability. The anatomic data obtained using CT can be supplemented by the metabolic data obtained using fluorodeoxyglucose F 18 (FDG) positron emission tomography (PET); therefore, the use of FDG-PET/CT for staging NSCLC is recommended, as it provides more accuracy than either modality alone. Furthermore, FDG-PET/magnetic resonance imaging (MRI) provides useful information on metabolic activity and tumor cellularity, and has become increasingly popular. A number of studies have described FDG-PET/MRI as having a high diagnostic performance in NSCLC staging. Therefore, multidimensional functional imaging using FDG-PET/MRI is promising for evaluating the activity of the intratumoral environment. Radiomics is the quantitative extraction of imaging features from medical scans. The chief advantages of FDG-PET/CT radiomics are the ability to capture information beyond the capabilities of the human eye, non-invasiveness, the (virtually) real-time response, and full-field analysis of the lesion. This review summarizes the recent advances in FDG-PET imaging within the field of clinical oncology in NSCLC, with a focus on surgery and prognostication, and investigates the site-specific strengths and limitations of FDG-PET/CT. Overall, the goal of treatment for NSCLC is to provide the best opportunity for long-term survival; therefore, FDG-PET/CT is expected to play an increasingly important role in deciding the appropriate treatment for such patients.

Current Applications for Nuclear Medicine Imaging in Pulmonary Disease

Purpose of Review

The main goal of the article is to familiarize the reader with commonly and uncommonly used nuclear medicine procedures that can significantly contribute to improved patient care. The article presents examples of specific modality utilization in the chest including assessment of lung ventilation and perfusion, imaging options for broad range of infectious and inflammatory processes, and selected aspects of oncologic imaging. In addition, rapidly developing new techniques utilizing molecular imaging are discussed.

Recent Findings

The article describes nuclear medicine imaging modalities including gamma camera, SPECT, PET, and hybrid imaging (SPECT/CT, PET/CT, and PET/MR) in the context of established and emerging clinical applications. Areas of potential future development in nuclear medicine are discussed with emphasis on molecular imaging and implementation of new targeted tracers used in diagnostics and therapeutics (theranostics).

Summary

Nuclear medicine and molecular imaging provide many unique and novel options for the diagnosis and treatment of pulmonary diseases. This article reviews current applications for nuclear medicine and molecular imaging and selected future applications for radiopharmaceuticals and targeted molecular imaging techniques.

Tumour functional imaging by PET

Carcinogenesis is a complex multistep process, characterized by changes at different levels, both genetic and epigenetic, which alter cell metabolism. Positron emission tomography (PET) is a very sensitive image modality that allows to evaluate oncometabolism. PET functionalities are immense, since by labelling a molecule that specifically intervenes in a biochemical regulatory pathway of interest with a positron-emitting radionuclide, we can easily image that pathway. Thus, PET makes possible imaging several metabolic processes and assessing risk prediction, screening, diagnosis, response to therapy, metastization and recurrence. In this paper, we provide an overview of different radiopharmaceuticals developed for PET use in oncology, with a focus on brain tumours, breast cancer, hepatocellular carcinoma, neuroendocrine tumours, bladder cancer and prostate cancer because for these cancer types PET has been shown to be valuable. Most of the described tracers are just used in the research environment, with the aim to assess if these tracers could be able to offer an improvement concerning staging/restaging, characterization and stratification of different types of cancer, as well as therapeutic response assessment. In pursuit of personalized therapy, we briefly discuss the more established metabolic tracers and describe recent work on the development of new radiopharmaceuticals, aware that there will continue to exist diagnostic challenges to face modern cancer medicine.

Quantitative PET/MR imaging of lung cancer in the presence of artifacts in the MR-based attenuation correction maps

Background

Positron emission tomography (PET)/magnetic resonance (MR) imaging may become increasingly important for assessing tumor therapy response. A prerequisite for quantitative PET/MR imaging is reliable and repeatable MR-based attenuation correction (AC).

Purpose

To investigate the frequency and test–retest reproducibility of artifacts in MR-AC maps in a lung cancer patient cohort and to study the impact of artifact corrections on PET-based tumor quantification.

Material and Methods

Twenty-five lung cancer patients underwent single-day, test–retest, 18F-fluorodeoxyglucose (FDG) PET/MR imaging. The acquired MR-AC maps were inspected for truncation, susceptibility, and tissue inversion artifacts. An anatomy-based bone template and a PET-based estimation of truncated arms were employed, while susceptibility artifacts were corrected manually. We report the frequencies of artifacts and the relative difference (RD) on standardized uptake value (SUV) based quantification in PET images reconstructed with the corrected AC maps.

Results

Truncation artifacts were found in all 50 acquisitions (100%), while susceptibility and tissue inversion artifacts were observed in six (12%) and 26 (52%) of the scans, respectively. The RD in lung tumor SUV was < 5% from bone and truncation corrections, while up to 20% RD was introduced after susceptibility artifact correction, with large inconsistencies between test–retest scans.

Conclusion

The absence of bone and truncation artifacts have limited effect on the PET quantification of lung lesions. In contrast, susceptibility artifacts caused significant and inconsistent underestimations of the lung tumor SUVs, between test–retest scans. This may have clinical implications for patients undergoing serial imaging for tumor therapy response assessment.

Role of FDG PET/CT in the Eighth Edition of TNM Staging of Non-Small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related mortality in the United States, and accurate staging plays a vital role in determining prognosis and treatment. The recently revised eighth edition of the TNM staging system for lung cancer defines new T and M descriptors and updates stage groupings on the basis of substantial differences in survival. There are new T descriptors that are based on the findings at histopathologic examination, and T descriptors are reassigned on the basis of tumor size and extent. No changes were made to the N descriptors in the eighth edition of the TNM staging of lung cancer, because the four N categories that are based on the location of the diseased nodes can be used to consistently predict prognosis. The eighth edition includes a new M1b descriptor for patients with a single extrathoracic metastatic lesion in a single organ (M1b), because they have better survival and different treatment options, compared with those with multiple extrathoracic lesions (M1c). Examination with fluorine 18 fluorodeoxyglucose (FDG) PET/CT is the standard of care and is an integral part of the clinical staging of patients with lung cancer. To provide the treating physicians with accurate staging information, radiologists and nuclear medicine physicians should be aware of the updated classification system and should be cognizant of the site-specific strengths and limitations of FDG PET/CT. In this article, the eighth edition of the TNM staging system is reviewed, as well as the role of FDG PET/CT in the staging of non-small cell lung carcinoma. ^©RSNA, 2018.

Machine learning for radiomics-based multimodality and multiparametric modeling

Due to the recent developments of both hardware and software technologies, multimodality medical imaging techniques have been increasingly applied in clinical practice and research studies. Previously, the application of multimodality imaging in oncology has been mainly related to combining anatomical and functional imaging to improve diagnostic specificity and/or target definition, such as positron emission tomography/computed tomography (PET/CT) and single-photon emission CT (SPECT)/CT. More recently, the fusion of various images, such as multiparametric magnetic resonance imaging (MRI) sequences, different PET tracer images, PET/MRI, has become more prevalent, which has enabled more comprehensive characterization of the tumor phenotype. In order to take advantage of these valuable multimodal data for clinical decision making using radiomics, we present two ways to implement the multimodal image analysis, namely radiomic (handcrafted feature) based and deep learning (machine learned feature) based methods. Applying advanced machine (deep) learning algorithms across multimodality images have shown better results compared with single modality modeling for prognostic and/or prediction of clinical outcomes. This holds great potentials for providing more personalized treatment for patients and achieve better outcomes.

Transcription factors in SOX family: Potent regulators for cancer initiation and development in the human body

Transcription factors (TFs) have a key role in controlling the gene regulatory network that sustains explicit cell states in humans. However, an uncontrolled regulation of these genes potentially results in a wide range of diseases, including cancer. Genes of the SOX family are indeed crucial as deregulation of SOX family TFs can potentially lead to changes in cell fate as well as irregular cell growth. SOX TFs are a conserved group of transcriptional regulators that mediate DNA binding through a highly conserved high-mobility group (HMG) domain. Accumulating evidence demonstrates that cell fate and differentiation in major developmental processes are controlled by SOX TFs. Besides; numerous reports indicate that both up- and down-regulation of SOX TFs may induce cancer progression. In this review, we discuss the involvement of key TFs of SOX family in human cancers.