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

Maximum standardized uptake value-to-tumor size ratio in fluorodeoxyglucose F18 positron emission tomography/computed tomography: a simple prognostic parameter for non-small cell lung cancer

PURPOSE

By correcting the effect of tumor size on metabolic activity, the maximum standardized uptake value-to-tumor size (SUVmax:tumor size) ratio on fluorodeoxyglucose F18 positron emission tomography (18F-FDG PET)/computed tomography (CT) scans can be a prognostic parameter of non-small cell lung cancer (NSCLC). The current study evaluates the prognostic value of SUVmax:tumor size ratio on pretreatment 18F-FDG PET/CT scans in patients with NSCLC. Furthermore, the SUVmax:tumor size ratio is compared with other established PET parameters.

METHODS

This study included 108 patients with NSCLC who underwent pretreatment 18F-FDG PET/CT scans and curative lung surgery. The associations between the SUVmax:tumor size ratio and other conventional PET parameters were investigated. The recurrence-free survival according to the SUVmax:tumor size ratio was also analyzed. In addition, the SUVmax:tumor size ratio was compared according to postoperative pathologic findings.

RESULTS

In total, 72 (66.7%) of the 108 participants presented with adenocarcinoma (ADC). Nineteen (17.6%) patients experienced recurrence during a median follow-up period of 32.3 months. The median SUV max:tumor size ratio was 2.37 (1.23 for ADCs and 3.90 for other histologic types). The SUVmax:tumor size ratio was associated with SUVmax and mean SUV, as well as metabolic tumor volume and total lesion glycolysis. Patients with an SUVmax:tumor size ratio higher than the median had a worse recurrence outcome than those with an SUVmax:tumor size ratio lower than the median. Participants with ADC who presented with lymphovascular invasion had a higher SUVmax:tumor size ratio than those without. The presence of lymph node metastasis and advanced histologic grade were associated with a high SUVmax:tumor size ratio in patients with ADC.

CONCLUSION

The SUVmax:tumor size ratio on pretreatment 18F-FDG PET/CT scans was associated with aggressive tumor behavior and poor outcome in NSCLCs, particularly ADC.

CLINICAL SIGNIFICANCE

The SUVmax:tumor size ratio on pretreatment 18F-FDG PET/CT scans has a prognostic value in patients with NSCLCs, especially ADC.

Multiparametric 18F-FDG PET/MRI based on restrictive spectrum imaging and amide proton transfer-weighted imaging facilitates the assessment of lymph node metastases in non-small cell lung cancer

BACKGROUND

To investigate the value of multiparametric 18F-FDG PET/MRI based on tri-compartmental restrictive spectrum imaging (RSI), amide proton transfer-weighted imaging (APTWI), and diffusion-weighted imaging (DWI) in the assessment of lymph node metastasis (LNM) of non-small cell lung cancer (NSCLC).

METHODS

A total of 152 patients (LNM-positive, 86 cases; LNM-negative, 66 cases) with NSCLC underwent chest multiparametric 18F-FDG PET/MRI were enrolled. 18F-FDG PET- derived parameter (SUVmax), RSI-derived parameters (f1, f2, and f3), APTWI-derived parameter (MTRasym(3.5 ppm)), DWI-derived parameter (ADC), and were calculated and compared. Logistic regression analysis was used to identify independent predictors, and combined diagnostics. Area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA) were employed to assess the performance of the combined diagnostics.

RESULTS

MTRasym(3.5 ppm), SUVmax, f2, and f3 were higher and ADC and f1 were lower in LNM-positive group than in LNM-negative group (all P < 0.05). Maximum lesion diameter, f1, MTRasym(3.5 ppm), SUVmax, and ADC were independent predictors of LNM status in NSCLC patients, and the combination of them had an optimal diagnostic efficacy (AUC = 0.978; sensitivity = 95.35%; specificity = 90.91%), which was significantly higher than maximum lesion diameter, f1, MTRasym(3.5 ppm), SUVmax, and ADC (AUC = 0.774, 0.810, 0.832, 0.834, and 0.783, respectively, and all P < 0.01). The combined diagnosis showed a good performance (AUC = 0.968) in the bootstrap (1000 samples)-based internal validation. Calibration curves and DCA demonstrated that the combined diagnosis not only provided better stability, but also resulted in a higher net benefit for the patients involved.

CONCLUSION

Multiparametric 18F-FDG PET/MRI based on RSI, APTWI, and DWI is beneficial for the non-invasive assessment of LNM status in NSCLC.

Head-to-head comparison of 18F-FDG PET/CT and 18F-FDG PET/MRI for lymph node metastasis staging in non-small cell lung cancer: a meta-analysis

PURPOSE

The current meta-analysis aimed to compare the diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) with 18F-FDG PET/magnetic resonance imaging (MRI) in non-small cell lung cancer (NSCLC) lymph node metastasis staging.

METHODS

We searched the PubMed, Web of Science, and Embase databases for relevant articles between November 1992 and September 2022. Studies evaluating the head-to-head comparison of 18F-FDG PET/CT and 18F-FDG PET/MRI for lymph node metastasis in patients with NSCLC were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 tool.

RESULTS

The analysis includes six studies with a total of 434 patients. The pooled sensitivity of 18F-FDG PET/CT and 18F-FDG PET/MRI was 0.78 [95% confidence interval (CI): 0.59-0.90] and 0.84 (95% CI: 0.68-0.93), and the pooled specificity was 0.87 (95% CI: 0.72-0.94) and 0.87 (95% CI: 0.80-0.92), respectively. The accuracy of 18F-FDG PET/CT and 18F-FDG PET/MRI was 0.81 (95% CI: 0.71-0.90) and 0.84 (95% CI: 0.75-0.92), respectively. When the pre-test probability was set at 50%, the post-test probability for 18F-FDG PET/CT could increase to 85%, and the post-test probability for 18F-FDG PET/MRI could increase to 87%.

CONCLUSION

18F-FDG PET/CT and 18F-FDG PET/MRI have similar diagnostic performance in detecting lymph node metastasis in NSCLC. However, the results of this study were from a small sample study, and further studies with larger sample sizes are needed.

Diagnostic potential of [18F]FDG PET/MRI in non-small cell lung cancer lymph node metastasis: a meta-analysis

PURPOSE

This meta-analysis evaluated the diagnostic accuracy and diagnostic value of [18F]FDG PET/MRI for mediastinal lymph node staging of NSCLC.

METHODS

Relevant articles in PubMed, Embase, Web of Science, and the Cochrane Library were searched until January 2023. Research evaluating [18F]FDG PET/MRI for mediastinal lymph node staging of NSCLC was included. Pooled estimates of sensitivity, specificity, PLR, and NLR were calculated by the "Stata" software.

RESULTS

Nine researches were included, containing 618 patients. The pooled sensitivity of [18F]FDG PET/MRI for detecting mediastinal lymph node staging of NSCLC was 0.82 (0.70-0.90), and the pooled specificity was 0.88 (0.82-0.93). PLR and NLR were 7.38 (4.73-11.52) and 0.20 (0.11-0.36), respectively. The AUC value of this imaging modality was 0.92 (0.90-0.94). The post-test probability for [18F]FDG PET/MRI might rise to 88% when the pre-test probability was set at 50%.

CONCLUSIONS

We considered [18F]FDG PET/MRI as an effective imaging tool with relatively high specificity and sensitivity. It has great potential to be used in the clinical management of patients in NSCLC who are amenable to early surgery. More studies with large sample sizes in the same direction are needed in future to obtain more reliable evidence-based support.

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.

Recent Advances in Cardiovascular Diseases Research Using Animal Models and PET Radioisotope Tracers

Cardiovascular diseases (CVD) is a collective term describing a range of conditions that affect the heart and blood vessels. Due to the varied nature of the disorders, distinguishing between their causes and monitoring their progress is crucial for finding an effective treatment. Molecular imaging enables non-invasive visualisation and quantification of biological pathways, even at the molecular and subcellular levels, what is essential for understanding the causes and development of CVD. Positron emission tomography imaging is so far recognized as the best method for in vivo studies of the CVD related phenomena. The imaging is based on the use of radioisotope-labelled markers, which have been successfully used in both pre-clinical research and clinical studies. Current research on CVD with the use of such radioconjugates constantly increases our knowledge and understanding of the causes, and brings us closer to effective monitoring and treatment. This review outlines recent advances in the use of the so-far available radioisotope markers in the research on cardiovascular diseases in rodent models, points out the problems and provides a perspective for future applications of PET imaging in CVD studies.

Metabolic targeting, immunotherapy and radiation in locally advanced non-small cell lung cancer: Where do we go from here?

In the US, there are ~250,000 new lung cancer diagnoses and ~130,000 deaths per year, and worldwide there are an estimated 1.6 million deaths per year from this deadly disease. Lung cancer is the most common cause of cancer death worldwide, and it accounts for roughly a quarter of all cancer deaths in the US. Non-small cell lung cancer (NSCLC) represents 80-85% of these cases. Due to an enormous tobacco cessation effort, NSCLC rates in the US are decreasing, and the implementation of lung cancer screening guidelines and other programs have resulted in a higher percentage of patients presenting with potentially curable locoregional disease, instead of distant disease. Exciting developments in molecular targeted therapy and immunotherapy have resulted in dramatic improvement in patients' survival, in combination with new surgical, pathological, radiographical, and radiation techniques. Concurrent platinum-based doublet chemoradiation therapy followed by immunotherapy has set the benchmark for survival in these patients. However, despite these advances, ~50% of patients diagnosed with locally advanced NSCLC (LA-NSCLC) survive long-term. In patients with local and/or locoregional disease, chemoradiation is a critical component of curative therapy. However, there remains a significant clinical gap in improving the efficacy of this combined therapy, and the development of non-overlapping treatment approaches to improve treatment outcomes is needed. One potential promising avenue of research is targeting cancer metabolism. In this review, we will initially provide a brief general overview of tumor metabolism as it relates to therapeutic targeting. We will then focus on the intersection of metabolism on both oxidative stress and anti-tumor immunity. This will be followed by discussion of both tumor- and patient-specific opportunities for metabolic targeting in NSCLC. We will then conclude with a discussion of additional agents currently in development that may be advantageous to combine with chemo-immuno-radiation in NSCLC.

Form Factors as Potential Imaging Biomarkers to Differentiate Benign vs. Malignant Lung Lesions on CT Scans

Indeterminate lung nodules detected on CT scans are common findings in clinical practice. Their correct assessment is critical, as early diagnosis of malignancy is crucial to maximise the treatment outcome. In this work, we evaluated the role of form factors as imaging biomarkers to differentiate benign vs. malignant lung lesions on CT scans. We tested a total of three conventional imaging features, six form factors, and two shape features for significant differences between benign and malignant lung lesions on CT scans. The study population consisted of 192 lung nodules from two independent datasets, containing 109 (38 benign, 71 malignant) and 83 (42 benign, 41 malignant) lung lesions, respectively. The standard of reference was either histological evaluation or stability on radiological followup. The statistical significance was determined via the Mann-Whitney U nonparametric test, and the ability of the form factors to discriminate a benign vs. a malignant lesion was assessed through multivariate prediction models based on Support Vector Machines. The univariate analysis returned four form factors (Angelidakis compactness and flatness, Kong flatness, and maximum projection sphericity) that were significantly different between the benign and malignant group in both datasets. In particular, we found that the benign lesions were on average flatter than the malignant ones; conversely, the malignant ones were on average more compact (isotropic) than the benign ones. The multivariate prediction models showed that adding form factors to conventional imaging features improved the prediction accuracy by up to 14.5 pp. We conclude that form factors evaluated on lung nodules on CT scans can improve the differential diagnosis between benign and malignant lesions.

Tumorous tissue characterization using integrated 18F-FDG PET/dual-energy CT in lung cancer: Combining iodine enhancement and glycolytic activity

Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has become the method of choice for tumor staging in lung cancer patients with improved diagnostic accuracy for the evaluation of lymph node involvement and distant metastasis. Due to its spectral capabilities, dual-energy CT (DECT) employs a material decomposition algorithm enabling precise quantification of iodine concentrations in distinct tissues. This technique enhances the characterization of tumor blood supply and has demonstrated promising results for the assessment of therapy response in patients with lung cancer. Several studies have demonstrated that DECT provides additional value to the PET-based evaluation of glycolytic activity, especially for the evaluation of therapy response and follow-up of patients with lung cancer. The combination of PET and DECT in a single scanner system enables the simultaneous assessment of glycolytic activity and iodine enhancement, offering further insight to the characterization of tumorous tissues. Recently a new approach of a novel integrated PET/DECT was investigated in a pilot study on patients with non-small cell lung cancer (NSCLC). The study showed a moderate correlation between PET-based standard uptake values (SUV) and DECT-based iodine densities in the evaluation of lung tumorous tissue but with limited assessment of lymph nodes. The following review on tumorous tissue characterization using PET and DECT imaging describes the strengths and limitations of this novel technique.

A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management

Radiomics analysis quantifies the interpolation of multiple and invisible molecular features present in diagnostic and therapeutic images. Implementation of 18-fluorine-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) radiomics captures various disorders in non-invasive and high-throughput manner. ¹⁸F-FDG PET/CT accurately identifies the metabolic and anatomical changes during cancer progression. Therefore, the application of ¹⁸F-FDG PET/CT in the field of oncology is well established. Clinical application of ¹⁸F-FDG PET/CT radiomics in lung infection and inflammation is also an emerging field. Combination of bioinformatics approaches or textual analysis allows radiomics to extract additional information to predict cell biology at the micro-level. However, radiomics texture analysis is affected by several factors associated with image acquisition and processing. At present, researchers are working on mitigating these interrupters and developing standardised workflow for texture biomarker establishment. This review article focuses on the application of ¹⁸F-FDG PET/CT in detecting lung diseases specifically on cancer, infection and inflammation. An overview of different approaches and challenges encountered on standardisation of ¹⁸F-FDG PET/CT technique has also been highlighted. The review article provides insights about radiomics standardisation and application of ¹⁸F-FDG PET/CT in lung disease management.

Application of dual-stream 3D convolutional neural network based on 18F-FDG PET/CT in distinguishing benign and invasive adenocarcinoma in ground-glass lung nodules

Purpose

This work aims to train, validate, and test a dual-stream three-dimensional convolutional neural network (3D-CNN) based on fluorine 18 (¹⁸F)-fluorodeoxyglucose (FDG) PET/CT to distinguish benign lesions and invasive adenocarcinoma (IAC) in ground-glass nodules (GGNs).

Methods

We retrospectively analyzed patients with suspicious GGNs who underwent ¹⁸F-FDG PET/CT in our hospital from November 2011 to November 2020. The patients with benign lesions or IAC were selected for this study. According to the ratio of 7:3, the data were randomly divided into training data and testing data. Partial image feature extraction software was used to segment PET and CT images, and the training data after using the data augmentation were used for the training and validation (fivefold cross-validation) of the three CNNs (PET, CT, and PET/CT networks).

Results

A total of 23 benign nodules and 92 IAC nodules from 106 patients were included in this study. In the training set, the performance of PET network (accuracy, sensitivity, and specificity of 0.92 ± 0.02, 0.97 ± 0.03, and 0.76 ± 0.15) was better than the CT network (accuracy, sensitivity, and specificity of 0.84 ± 0.03, 0.90 ± 0.07, and 0.62 ± 0.16) (especially accuracy was significant, P-value was 0.001); in the testing set, the performance of both networks declined. However, the accuracy and sensitivity of PET network were still higher than that of CT network (0.76 vs. 0.67; 0.85 vs. 0.70). For dual-stream PET/CT network, its performance was almost the same as PET network in the training set (P-value was 0.372–1.000), while in the testing set, although its performance decreased, the accuracy and sensitivity (0.85 and 0.96) were still higher than both CT and PET networks. Moreover, the accuracy of PET/CT network was higher than two nuclear medicine physicians [physician 1 (3-year experience): 0.70 and physician 2 (10-year experience): 0.73].

Conclusion

The 3D-CNN based on ¹⁸F-FDG PET/CT can be used to distinguish benign lesions and IAC in GGNs, and the performance is better when both CT and PET images are used together.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-021-00423-1.

Influencing Factors and Prognostic Value of 18F-FDG PET/CT Metabolic and Volumetric Parameters in Non-Small Cell Lung Cancer

Objective

This study aims to explore factors influencing metabolic and volumetric parameters of [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging in non-small cell lung cancer (NSCLC) and the predictive value for prognosis of NSCLC.

Methods

Retrospective analysis was performed on 133 NSCLC patients who received ¹⁸F-FDG PET/CT imaging. After ¹⁸F-FDG injection at 3.7 MBq/kg, 1 h early imaging and 2 h delayed imaging were performed. The metabolic and volumetric parameters such as SUVmax, SUVpeak, SULmax, SULpeak, MTV and TLG were measured. The tumor markers including CFYRA21-1, NSE, SCC-ag and the immunohistochemical biomarkers including Ki-67, P53 and CK-7 were examined. All patients were followed up for 24 months, and the 1-year and 2-year overall survival rate (OS) were recorded.

Results

There were significant differences in metabolic and volumetric parameters (SUVmax, SUVpeak, SULmax, SULpeak and TLG) between adenocarcinoma and squamous cell carcinoma of NSCLC. SUVmax, SUVpeak, SULmax, SULpeak, MTV and TLG were correlated with tumor marker NSE and TNM stage. MTV and TLG were related to CYFRA21-1, and only MTV was associated with SCC-ag. SUVpeak and SULmax were related to P53. In addition, early SULpeak and delayed MTV were significant prognostic factors of 1-year OS, while early SUVpeak, delayed TLG and delayed MTV were predictive factors of 2-year OS in NSCLC.

Conclusion

The metabolic and volumetric parameters of ¹⁸F-FDG PET/CT were related to a variety of factors such as NSE, CFYRA21-1, SCC-ag, P53 and TNM stage, and have a predictive value in prognosis of NSCLC.

"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.

Quantitative FDG PET Assessment for Oncology Therapy

Simple Summary

PET enables quantitative assessment of tumour biology in vivo. Accumulation of F-18 fluorodeoxyglucose (FDG) may reflect tumour metabolic activity. Quantitative assessment of FDG uptake can be applied for treatment monitoring. Numerous studies indicated biochemical change assessed by FDG-PET as a more sensitive marker than morphological change. Those with complete metabolic response after therapy may show better prognosis. Assessment of metabolic change may be performed using absolute FDG uptake or metabolic tumour volume. More recently, radiomics approaches have been applied to FDG PET. Texture analysis quantifies intratumoral heterogeneity in a voxel-by-voxel basis. Combined with various machine learning techniques, these new quantitative parameters hold a promise for assessing tissue characterization and predicting treatment effect, and could also be used for future prognosis of various tumours.

Abstract

Positron emission tomography (PET) has unique characteristics for quantitative assessment of tumour biology in vivo. Accumulation of F-18 fluorodeoxyglucose (FDG) may reflect tumour characteristics based on its metabolic activity. Quantitative assessment of FDG uptake can often be applied for treatment monitoring after chemotherapy or chemoradiotherapy. Numerous studies indicated biochemical change assessed by FDG PET as a more sensitive marker than morphological change estimated by CT or MRI. In addition, those with complete metabolic response after therapy may show better disease-free survival and overall survival than those with other responses. Assessment of metabolic change may be performed using absolute FDG uptake in the tumour (standardized uptake value: SUV). In addition, volumetric parameters such as metabolic tumour volume (MTV) have been introduced for quantitative assessment of FDG uptake in tumour. More recently, radiomics approaches that focus on image-based precision medicine have been applied to FDG PET, as well as other radiological imaging. Among these, texture analysis extracts intratumoral heterogeneity on a voxel-by-voxel basis. Combined with various machine learning techniques, these new quantitative parameters hold a promise for assessing tissue characterization and predicting treatment effect, and could also be used for future prognosis of various tumours, although multicentre clinical trials are needed before application in clinical settings.

Effect of Wenxia Changfu Formula Combined With Cisplatin Reversing Non-Small Cell Lung Cancer Cell Adhesion-Mediated Drug Resistance

Non-small cell lung cancer (NSCLC), the major form of primary lung cancer, is a common cause of cancer-related death worldwide. Cell adhesion-mediated drug resistance (CAM-DR), a form of chemotherapy resistance, has been reported to confer resistance to various chemotherapeutic agents. Integrin β1 signaling plays an important role in CAM-DR and has been proposed as a potential target for NSCLC. Wenxia Changfu Formula (WCF) is a Traditional Chinese Compound Prescription for the intervention treatment of NSCLC combined with cisplatin (DDP). This study aims to investigate the effect and mechanism of WCF combined with DDP in reversing CAM-DR. Firstly, the chemical profile of WCF was characterized by UPLC/Q-TOF-MS analysis. A total of 237 compounds with mzCloud Best Match of greater than 70 were identified by using the online database mzCloud. Secondly, we established A549 three-dimensional(3D) cells cultured in vitro and nude mice xenografts models of the A549 cell line with Integrin β1 overexpression. In vitro, the cell viability, migration and adhesion were measured though MTT Assay, Wound Healing Assay and Cell Adhesion Assay, the Integrin β1 expression of the A549 cells was assessed through immunocytochemistry; in vitro, the transplanted tumor morphology and the colocalization of Integrin β1 and its ligands were tested by HE staining and immunofluorescence. As a result, we found that the combination effectively reduced cell viability, suppressed migration and adhesion, and downregulated the protein level of Integrin β1 in three-dimensional cultured A549 cells. And the combination of WCF with DDP significantly inhibited tumor growth, increased organelle vacuolations and decreased colocalization of Integrin β1 and its ligands including fibulin-2 and laminin. Taken together, our results confirm that the combination of WCF with DDP could reverse the lung cancer CAM-DR through the Integrin β1 signaling pathway.

Value of Shape and Texture Features from 18F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation

In this paper, we investigate the role of shape and texture features from 18F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11.0) all with histologically confirmed benign (n=39) or malignant (n=72) solitary pulmonary nodules. Eighteen three-dimensional imaging features, including conventional, texture, and shape features from PET and CT were tested for significant differences (Wilcoxon-Mann-Withney) between the benign and malignant groups. Prediction models based on different feature sets and three classification strategies (Classification Tree, k-Nearest Neighbours, and Naïve Bayes) were also evaluated to assess the potential benefit of shape and texture features compared with conventional imaging features alone. Eight features from CT and 15 from PET were significantly different between the benign and malignant groups. Adding shape and texture features increased the performance of both the CT-based and PET-based prediction models with overall accuracy gain being 3.4-11.2 pp and 2.2-10.2 pp, respectively. In conclusion, we found that shape and texture features from 18F-FDG PET/CT can lead to a better discrimination between benign and malignant lung nodules by increasing the accuracy of the prediction models by an appreciable margin.