Prognostic value of whole-body total lesion glycolysis at pretreatment FDG PET/CT in non-small cell lung cancer

[18F]fluorodeoxyglucose positron emission tomography/computed tomography in combination with clinical data in predicting overall survival in non-small-cell lung cancer patients: A retrospective study

INTRODUCTION

Positron emission tomography/computed tomography (PET/CT) has an established role in evaluating patients with lung cancer. The aim of this work was to assess the predictive capability of [18F]Fluorodeoxyglucose ([18F]FDG) PET/CT parameters on overall survival (OS) in lung cancer patients using an artificial neural network (ANN) in parallel with conventional statistical analysis.

METHODS

Retrospective analysis was performed on a group of 165 lung cancer patients (98M, 67F). PET features associated with the primary tumor: maximum and mean standardized uptake value (SUVmax, SUVmean), total lesion glycolysis (TLG) metabolic tumor volume (MTV) and area under the curve-cumulative SUV histogram (AUC-CSH) and metastatic lesions (SUVmaxtotal, SUVmeantotal, TLGtotal, and MTVtotal) were evaluated. In parallel with conventional statistical analysis (Chi-Square analysis for nominal data, Student's t test for continuous data), the data was evaluated using an ANN. There were 97 input variables in 165 patients using a binary classification of either below, or greater than/equal to median survival post primary diagnosis. Additionally, phantom study was performed to assess the most optimal contouring method.

RESULTS

Males had statistically higher SUVmax (mean: 10.7 vs 8.9; p = 0.020), MTV (mean: 66.5 cm3 vs. 21.5 cm3; p = 0.001), TLG (mean 404.7 vs. 115.0; p = 0.003), TLGtotal (mean: 946.7 vs. 433.3; p = 0.014) and MTVtotal (mean: 242.0 cm3 vs. 103.7 cm3; p = 0.027) than females. The ANN after training and validation was optimised with a final architecture of 4 scaling layer inputs (TLGtotal, SUVmaxtotal, SUVmeantotal and disease stage) and receiving operator characteristic (ROC) analysis demonstrated an AUC of 0.764 (sensitivity of 92.3%, specificity of 57.1%).

CONCLUSION

Conventional statistical analysis and the ANN provided concordant findings in relation to variables that predict decreased survival. The ANN provided a weighted algorithm of the 4 key features to predict decreased survival.

IMPLICATION FOR PRACTICE

Identification of parameters which can predict survival in lung cancer patients might be helpful in choosing the group of patients who require closer look during the follow-up.

Need for Objective Task-Based Evaluation of Image Segmentation Algorithms for Quantitative PET: A Study with ACRIN 6668/RTOG 0235 Multicenter Clinical Trial Data

Reliable performance of PET segmentation algorithms on clinically relevant tasks is required for their clinical translation. However, these algorithms are typically evaluated using figures of merit (FoMs) that are not explicitly designed to correlate with clinical task performance. Such FoMs include the Dice similarity coefficient (DSC), the Jaccard similarity coefficient (JSC), and the Hausdorff distance (HD). The objective of this study was to investigate whether evaluating PET segmentation algorithms using these task-agnostic FoMs yields interpretations consistent with evaluation on clinically relevant quantitative tasks. Methods: We conducted a retrospective study to assess the concordance in the evaluation of segmentation algorithms using the DSC, JSC, and HD and on the tasks of estimating the metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of primary tumors from PET images of patients with non-small cell lung cancer. The PET images were collected from the American College of Radiology Imaging Network 6668/Radiation Therapy Oncology Group 0235 multicenter clinical trial data. The study was conducted in 2 contexts: (1) evaluating conventional segmentation algorithms, namely those based on thresholding (SUVmax40% and SUVmax50%), boundary detection (Snakes), and stochastic modeling (Markov random field-Gaussian mixture model); (2) evaluating the impact of network depth and loss function on the performance of a state-of-the-art U-net-based segmentation algorithm. Results: Evaluation of conventional segmentation algorithms based on the DSC, JSC, and HD showed that SUVmax40% significantly outperformed SUVmax50%. However, SUVmax40% yielded lower accuracy on the tasks of estimating MTV and TLG, with a 51% and 54% increase, respectively, in the ensemble normalized bias. Similarly, the Markov random field-Gaussian mixture model significantly outperformed Snakes on the basis of the task-agnostic FoMs but yielded a 24% increased bias in estimated MTV. For the U-net-based algorithm, our evaluation showed that although the network depth did not significantly alter the DSC, JSC, and HD values, a deeper network yielded substantially higher accuracy in the estimated MTV and TLG, with a decreased bias of 91% and 87%, respectively. Additionally, whereas there was no significant difference in the DSC, JSC, and HD values for different loss functions, up to a 73% and 58% difference in the bias of the estimated MTV and TLG, respectively, existed. Conclusion: Evaluation of PET segmentation algorithms using task-agnostic FoMs could yield findings discordant with evaluation on clinically relevant quantitative tasks. This study emphasizes the need for objective task-based evaluation of image segmentation algorithms for quantitative PET.

Prognostic significance of integrating total metabolic tumor volume and EGFR mutation status in patients with lung adenocarcinoma

Background

The objective of this study was to investigate the prognostic significance of total metabolic tumor volume (TMTV) derived from baseline 18F-2-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), in conjunction with epidermal growth factor receptor (EGFR) mutation status, among patients with lung adenocarcinoma (LUAD).

Methods

We performed a retrospective analysis on 141 patients with LUAD (74 males, 67 females, median age 67 (range 34-86)) who underwent 18F-FDG PET/CT and had their EGFR mutation status determined. Optimal cutoff points for TMTV were determined using time-dependent receiver operating characteristic curve analysis. The survival difference was compared using Cox regression analysis and Kaplan‒Meier curves.

Results

The EGFR mutant patients (n = 79, 56.0%) exhibited significantly higher 2-year progression-free survival (PFS) and overall survival (OS) rates compared to those with EGFR wild-type (n = 62, 44.0%), with rates of 74.2% vs 69.2% (P = 0.029) and 86.1% vs 67.7% (P = 0.009), respectively. The optimal cutoff values of TMTV were 36.42 cm3 for PFS and 37.51 cm3 for OS. Patients with high TMTV exhibited significantly inferior 2-year PFS and OS, with rates of 22.4% and 38.1%, respectively, compared to those with low TMTV, who had rates of 85.8% and 95.0% (both P < 0.001). In both the EGFR mutant and wild-type groups, patients exhibiting high TMTV demonstrated significantly inferior 2-year PFS and OS compared to those with low TMTV. In multivariate analysis, EGFR mutation status (hazard ratio, HR, 0.41, 95% confidence interval, CI [0.18-0.94], P = 0.034) and TMTV (HR 8.08, 95% CI [2.34-28.0], P < 0.001) were independent prognostic factors of OS, whereas TMTV was also an independent prognosticator of PFS (HR 2.59, 95% CI [1.30-5.13], P = 0.007).

Conclusion

Our study demonstrates that the integration of TMTV on baseline 18F-FDG PET/CT with EGFR mutation status improves the accuracy of prognostic evaluation for patients with LUAD.

Are MTV and TLG Accurate for Quantifying the Intensity of Brown Adipose Tissue Activation?

Recent research has suggested that one novel mechanism of action for anti-obesity medications is to stimulate the activation of brown adipose tissue (BAT). 18FDG PET/CT remains the gold standard for defining and quantifying BAT. SUVmax is the most often used quantification tool in clinical practice. However, this parameter does not reflect the entire BAT volume. As a potential method for precisely evaluating BAT, we have utilised metabolic tumour volume (MTV) and total lesion glycolysis (TLG) to answer the question: Are MTV and TLG accurate in quantifying the intensity of BAT activation? After analysing the total number of oncological 18F-FDG PET/CT scans between 2021-2023, we selected patients with active BAT. Based on the BAT SUVmax, the patients were divided into BAT-moderate activation (MA) vs. BAT-high activation (HA). Furthermore, we statistically analysed the accuracy of TLG and MTV in assessing BAT activation intensity. The results showed that both parameters increased their predictive value regarding BAT activation, and presented a significantly high sensitivity and specificity for the correct classification of BAT activation intensity. To conclude, these parameters could be important indicators with increased accuracy for classifying BAT expression, and could bring additional information about the volume of BAT to complement the limitations of the SUVmax.

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study

PURPOSE

No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pulmonary adenocarcinomas. This study aims to develop a deep learning grading signature (DLGS) based on positron emission tomography/computed tomography (PET/CT) to personalize surgical treatments for clinical stage I invasive lung adenocarcinoma and explore the biologic basis under its prediction.

METHODS

A total of 2638 patients with clinical stage I invasive lung adenocarcinoma from 4 medical centers were retrospectively included to construct and validate the DLGS. The predictive performance of the DLGS was evaluated by the area under the receiver operating characteristic curve (AUC), its potential to optimize surgical treatments was investigated via survival analyses in risk groups defined by the DLGS, and its biological basis was explored by comparing histologic patterns, genotypic alternations, genetic pathways, and infiltration of immune cells in microenvironments between risk groups.

RESULTS

The DLGS to predict grade 3 achieved AUCs of 0.862, 0.844, and 0.851 in the validation set (n = 497), external cohort (n = 382), and prospective cohort (n = 600), respectively, which were significantly better than 0.814, 0.810, and 0.806 of the PET model, 0.813, 0.795, and 0.824 of the CT model, and 0.762, 0.734, and 0.751 of the clinical model. Additionally, for DLGS-defined high-risk population, lobectomy yielded an improved prognosis compared to sublobectomy p = 0.085 for overall survival [OS] and p = 0.038 for recurrence-free survival [RFS]) and systematic nodal dissection conferred a superior prognosis to limited nodal dissection (p = 0.001 for OS and p = 0.041 for RFS).

CONCLUSION

The DLGS harbors the potential to predict the histologic grade and personalize the surgical treatments for clinical stage I invasive lung adenocarcinoma. Its applicability to other territories should be further validated by a larger international study.

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer

Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a deep learning signature based on positron emission tomography/computed tomography to predict ONM of clinical stage N0 NSCLC. An internal cohort (n = 1911) is included to construct the deep learning nodal metastasis signature (DLNMS). Subsequently, an external cohort (n = 355) and a prospective cohort (n = 999) are utilized to fully validate the predictive performances of the DLNMS. Here, we show areas under the receiver operating characteristic curve of the DLNMS for occult N1 prediction are 0.958, 0.879 and 0.914 in the validation set, external cohort and prospective cohort, respectively, and for occult N2 prediction are 0.942, 0.875 and 0.919, respectively, which are significantly better than the single-modal deep learning models, clinical model and physicians. This study demonstrates that the DLNMS harbors the potential to predict ONM of clinical stage N0 NSCLC.

PET-CT for characterising TB infection (TBI) in immunocompetent subjects: a systematic review

Introduction. There is emerging evidence of a potential role for PET-CT scan as an imaging biomarker to characterise the spectrum of tuberculosis infection (TBI) in humans and animal models.Gap Statement. Synthesis of available evidence from current literature is needed to understand the utility of PET-CT for characterising TBI and how this may inform application of PET-CT in future TBI research.Aim. The aims of this review are to summarise the evidence of PET-CT scan use in immunocompetent hosts with TBI, and compare PET-CT features observed in humans and animal models.Methodology. MEDLINE, Embase and PubMed Central were searched to identify relevant publications. Studies were selected if they reported PET-CT features in human or animals with TBI. Studies were excluded if immune deficiency was present at the time of the initial PET-CT scan.Results. Six studies - four in humans and two in non-human primates (NHP) were included for analysis. All six studies used 2-deoxy-2-[18F]fluoro-d-glucose (2-[18F]FDG) PET-CT. Features of TBI were comparable between NHP and humans, with 2-[18F]FDG avid intrathoracic lymph nodes observed during early infection. Progressive TBI was characterised in NHP by increasing 2-[18F]FDG avidity and size of lesions. Two human studies suggested that PET-CT can discriminate between active TB and inactive TBI. However, data synthesis was generally limited by human studies including inconsistent and poorly characterised cohorts and the small number of eligible studies for review.Conclusion. Our review provides some evidence, limited primarily to non-human primate models, of PET-CT utility as a highly sensitive imaging modality to reveal and characterise meaningful metabolic and structural change in early TBI. The few human studies identified exhibit considerable heterogeneity. Larger prospective studies are needed recruiting well characterised cohorts with TBI and adopting a standardized PET-CT protocol, to better understand utility of this imaging biomarker to support future research.

Prognostic Significance of Volumetric Parameters Based on FDG PET/CT in Patients with Lung Adenocarcinoma Undergoing Curative Surgery

INTRODUCTION

FDG PET/CT is a robust imaging modality to diagnose and stratify prognoses for non-small cell lung carcinoma. However, the role of FDG PET/CT in operable lung adenocarcinoma patients has not been previously investigated in a large cohort with varying pathological stages. The prognostic value of volumetric parameters based on FDG PET/CT was investigated in patients with stage I-III lung adenocarcinoma receiving curative surgery.

METHODS

This retrospective study included 432 patients with lung adenocarcinoma undergoing preoperative FDG PET/CT between January 2016 and December 2017. Clinicopathologic variables, conventional image parameters, such as the maximum standardized uptake value (SUVmax) and mean SUV (SUVmean) of the primary tumor, and volumetric parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), were included in Cox regression analysis. Subgroup analysis was conducted to compare hazard ratios (HRs) based on MTV in each pathological stage. A new staging system including volumetric parameters was suggested.

RESULTS

A total of 432 patients (median age: 62 years; interquartile range: 56-70 years; 225 males) were evaluated. Sex, age, presence of EGFR mutation, pathological stage, MTV, and TLG of the primary tumor were selected as statistically significant prognostic factors for overall survival irrespective of other variables (OS; p < 0.05 for all). Pathological stage, MTV, and TLG of the primary tumor were selected as statistically significant prognostic factors for disease-free survival irrespective of other variables (p < 0.05 for all). The suggested new staging system including MTV as an additional criterion showed better discrimination and prediction for OS than the conventional pathological staging system despite statistical insignificance (concordance index: 0.698 vs. 0.673).

CONCLUSIONS

The volumetric parameters of the primary tumor based on preoperative FDG PET/CT were independent prognostic factors in addition to pathological stage in patients with operable lung adenocarcinoma. The suggested new staging system considering MTV predicted the prognoses better than the conventional pathological staging system.

Metabolic Oscillations and Glycolytic Phenotypes of Cancer Cells

Cancer cells show several metabolic phenotypes depending on the cancer types and the microenvironments in tumor tissues. The glycolytic phenotype is one of the hallmarks of cancer cells and is considered to be one of the crucial features of malignant cancers. Here, we show glycolytic oscillations in the concentrations of metabolites in the glycolytic pathway in two types of cancer cells, HeLa cervical cancer cells and DU145 prostate cancer cells, and in two types of cellular morphologies, spheroids and monolayers. Autofluorescence from nicotinamide adenine dinucleotide (NADH) in cells was used for monitoring the glycolytic oscillations at the single-cell level. The frequencies of NADH oscillations were different among the cellular types and morphologies, indicating that more glycolytic cancer cells tended to exhibit oscillations with higher frequencies than less glycolytic cells. A mathematical model for glycolytic oscillations in cancer cells reproduced the experimental results quantitatively, confirming that the higher frequencies of oscillations were due to the higher activities of glycolytic enzymes. Thus, glycolytic oscillations are expected as a medical indicator to evaluate the malignancy of cancer cells with glycolytic phenotypes.

Lesion Analysis in PERCIST 1.0: Clinical Ease versus Research Requisite-Where Does the Balance Exist?

Background  Semiqualitative parameter SUVmax has been the most frequently used semiquantitative positron emission tomography (PET) parameter for response evaluation, but only metabolic activity of a single (most metabolic) lesion is predicted. Newer response parameters such as tumor lesion glycolysis (TLG) incorporating lesions' metabolic volume or whole-body metabolic tumor burden (MTBwb) are being explored for response evaluation. Evaluation and comparison of response with different semiquantitative PET parameters such as SUVmax and TLG in most metabolic lesion, multiple lesions (max of five), and MTBwb in advanced non-small cell lung cancer (NSCLC) patients were made. The different PET parameters were analyzed for response evaluation, overall survival (OS), and progression-free survival (PFS). Methods   ¹⁸ F-FDG-PET/CT (18-fluorine-fluorodeoxyglucose positron emission tomography/computed tomography) imaging was performed in 23 patients (M = 14, F = 9, mean age = 57.6 years) with stage IIIB-IV advanced NSCLC before initiation of therapy with oral estimated glomerular filtration rate-tyrosine kinase inhibitor for early and late response evaluation. The quantitative PET parameters such as SUVmax and TLG were measured in single (most metabolic) lesion, multiple lesions, and MTBwb. The parameters SUVmax, TLG, and MTBwb were compared for early and late response evaluation and analyzed for OS and PFS Results  No significant difference in change in response evaluation was seen in patients evaluated with most metabolic lesion, multiple lesions, or MTBwb. Difference in early (DC 22, NDC 1) and late (DC 20, NDC 3) response evaluation was seen that remained unchanged when lesions were measured in terms of number of lesions or the MTBwb. The early imaging was seen to be statistically significant to the OS compared with late imaging. Conclusions  Single (most metabolic) lesion shows similar disease response and OS to multiple lesions and MTBwb. Response evaluation by late imaging offered no significant advantage compared with early imaging. Thus, early response evaluation with SUVmax parameter offers a good balance between clinical ease and research requisition.

Can Baseline [18F]FDG PET/CT Predict Response to Immunotherapy After 6 Months and Overall Survival in Patients with Lung Cancer or Malignant Melanoma? A Multicenter Retrospective Study

Aim: To assess the role of baseline 18F-fluorodeoxyglucose ([18F]FDG)-positron emission tomography/computed tomography (PET/CT) in predicting response to immunotherapy after 6 months and overall survival (OS) in patients with lung cancer (LC) or malignant melanoma (MM). Methods: Data from a multicenter, retrospective study conducted between March and November 2021 were analyzed. Patients >18 years old with a confirmed diagnosis of LC or MM, who underwent a baseline [18F]FDG-PET/CT within 1-2 months before starting immunotherapy and had a follow-up of at least 12 months were included. PET scans were examined visually and semiquantitatively by physicians at peripheral centers. The metabolic tumor burden (number of lesions with [18F]FDG-uptake) and other parameters were recorded. Clinical response was assessed at 3 and 6 months after starting immunotherapy, and OS was calculated as the time elapsing between the PET scan and death or latest follow-up. Results: The study concerned 177 patients with LC and 101 with MM. Baseline PET/CT was positive in primary or local recurrent lesions in 78.5% and 9.9% of cases, in local/distant lymph nodes in 71.8% and 36.6%, in distant metastases in 58.8% and 84%, respectively, in LC and in MM patients. Among patients with LC, [18F]FDG-uptake in primary/recurrent lung lesions was more often associated with no clinical response to immunotherapy after 6 months than in cases without any tracer uptake. After a mean 21 months, 46.5% of patients with LC and 37.1% with MM had died. A significant correlation emerged between the site/number of [18F]FDG foci and death among patients with LC, but not among those with MM. Conclusions: In patients with LC who are candidates for immunotherapy, baseline [18F]FDG-PET/CT can help to predict response to this therapy after 6 months, and to identify those with a poor prognosis based on their metabolic parameters. For patients with MM, there was only a weak correlation between baseline PET/CT parameters, response to therapy, and survival.

Usefulness of 18 F-FDG PET/computed tomography metabolic parameters in predicting sarcopenia and prognosis of treatment-naive patients with non-small cell lung cancer

PURPOSE

Sarcopenia tremendously impacts the quality of life but remains debatable in prognostication in treatment-naive patients with non-small cell lung cancer (NSCLC). Hence, this study aimed to find a clinically feasible approach using 18 F-FDG PET/computed tomography (CT) imaging parameters and clinical characteristics to predict sarcopenia and determine independent prognostic factors.

METHODS

Clinical characteristics and 18 F-FDG PET/CT metabolic parameters, including maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis of primary tumor (SUVmax_P, MTV_P, and TLG_P) and combination of whole-body lesions (MTV_C and TLG_C) were collected in 344 treatment-naive patients with NSCLC. Skeletal muscle index at the third lumbar vertebra was calculated to determine sarcopenia. SUVmax of the psoas major muscle (SUVmax_M) was measured at the third lumbar vertebra as well. The diagnostic endpoint is the probability of sarcopenia, and the survival endpoints include progression-free survival (PFS) and overall survival (OS).

RESULTS

Among 344 patients with NSCLC there were 271 patients with adenocarcinoma and 73 with squamous cell carcinoma (SCC). One hundred forty-seven patients (42.7%) were diagnosed with sarcopenia. Higher age, male, lower BMI, SCC, and lower SUVmax_M were correlated with a higher incidence of sarcopenia ( P  < 0.05), while age, sex and SUVmax_M were independently predictive of sarcopenia. Multivariate Cox-regression analysis revealed that BMI, advanced stage and TLG_C were independent predictors of PFS and OS, while sex was independently predictive of OS.

CONCLUSIONS

The incidence of sarcopenia increased with declining SUVmax of muscle. BMI, tumor stage, and TLG_C, but not sarcopenia, were found independently predictive of both PFS and OS.

Radiomics Analysis of 18F-FDG PET/CT for Prognosis Prediction in Patients with Stage III Non-Small Cell Lung Cancer Undergoing Neoadjuvant Chemoradiation Therapy Followed by Surgery

We investigated the prognostic significance of radiomic features from 18F-FDG PET/CT to predict overall survival (OS) in patients with stage III NSCLC undergoing neoadjuvant chemoradiation therapy followed by surgery. We enrolled 300 patients with stage III NSCLC who underwent PET/CT at the initial work-up (PET1) and after neoadjuvant concurrent chemoradiotherapy (PET2). Radiomic primary tumor features were subjected to LASSO regression to select the most useful prognostic features of OS. The prognostic significance of the LASSO score and conventional PET parameters was assessed by Cox proportional hazards regression analysis. In conventional PET parameters, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of each PET1 and PET2 were significantly associated with OS. In addition, both the PET1-LASSO score and the PET2-LASSO score were significantly associated with OS. In multivariate Cox regression analysis, only the PET2-LASSO score was an independently significant factor for OS. The LASSO score showed better predictive performance for OS regarding the time-dependent receiver operating characteristic curve and decision curve analysis than conventional PET parameters. Radiomic features from PET/CT were an independent prognostic factor for the estimation of OS in stage III NSCLC. The newly developed LASSO score using radiomic features showed better prognostic results for individualized OS estimation than conventional PET parameters.

Four-dimensional quantitative analysis using FDG-PET in clinical oncology

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) has been commonly used in many oncological areas. High-resolution PET permits a three-dimensional analysis of FDG distributions on various lesions in vivo, which can be applied for tissue characterization, risk analysis, and treatment monitoring after chemoradiotherapy and immunotherapy. Metabolic changes can be assessed using the tumor absolute FDG uptake as standardized uptake value (SUV) and metabolic tumor volume (MTV). In addition, tumor heterogeneity assessment can potentially estimate tumor aggressiveness and resistance to chemoradiotherapy. Attempts have been made to quantify intratumoral heterogeneity using radiomics. Recent reports have indicated the clinical feasibility of a dynamic FDG PET-computed tomography (CT) in pilot cohort studies of oncological cases. Dynamic imaging permits the assessment of temporal changes in FDG uptake after administration, which is particularly useful for differentiating pathological from physiological uptakes with high diagnostic accuracy. In addition, several new parameters have been introduced for the in vivo quantitative analysis of FDG metabolic processes. Thus, a four-dimensional FDG PET-CT is available for precise tissue characterization of various lesions. This review introduces various new techniques for the quantitative analysis of FDG distribution and glucose metabolism using a four-dimensional FDG analysis with PET-CT. This elegant study reveals the important role of tissue characterization and treatment strategies in oncology.

Risk stratification of oesophageal squamous cell carcinoma using change in total lesion glycolysis and number of PET-positive lymph nodes

BACKGROUND

The efficacy of neoadjuvant chemotherapy (NACT) correlates with patient survival in oesophageal squamous cell carcinoma (OSCC), but optimal evaluation of the treatment response based on PET-CT parameters has not been established.

METHODS

We analysed 226 OSCC patients who underwent PET-CT before and after NACT followed by surgery. We assessed SUVmax, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) for the primary tumour and the number of PET-positive lymph nodes before and after NACT to predict patient survival.

RESULTS

In a stepwise analysis, we defined 60%, 80%, and 80% as the optimal cut-off values for SUVmax, MTV, and TLG reduction, respectively, to distinguish responders and non-responders to NACT. In the ROC analysis, the TLG reduction rate was the best predictor of recurrence among PET-CT parameters. The TLG responders achieved significantly more favourable prognoses than non-responders (2-year progression-free survival [PFS] rate: 64.1% vs. 38.5%; P = 0.0001). TLG reduction rate (HR 2.58; 95% CI 1.16-5.73) and the number of PET-positive lymph nodes after NACT (HR 1.79; 95% CI 1.04-3.08) were significant independent prognostic factors.

CONCLUSIONS

TLG reduction is the best predictor of prognosis. Preoperative PET-CT evaluation of both the primary tumour and lymph nodes could accurately stratify risk in OSCC patients.

Metabolic Tumor Volume Measured by 18F-FDG PET/CT is Associated with the Survival of Unresectable Hepatocellular Carcinoma Treated with PD-1/PD-L1 Inhibitors Plus Molecular Targeted Agents

Purpose

The combination of PD-1/PD-L1 inhibitors and molecular targeted agents showed promising efficacy for unresectable hepatocellular carcinoma (uHCC). This study aimed to investigate the prognostic value of metabolic parameters from ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) in patients with uHCC underwent the combined therapies.

Patients and Methods

Patients with uHCC treated with a combination of immunotherapy and targeted therapy who underwent baseline ¹⁸F-FDG PET/CT between July 2018 and December 2021 were recruited retrospectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake values (SUV_max), and clinical and biological parameters were recorded. A multivariate prediction model was developed for overall survival (OS) using these parameters together with clinical prognostic factors.

Results

Seventy-seven patients were finally included. The median OS was 16.8 months. We found that a high MTV (≥39.65 cm³ as the median value) was significantly associated with OS (P<0.05). In multivariate analyses for OS, a high MTV, high Eastern Cooperative Oncology Group performance status (ECOG-PS, ≥1), Child-Pugh (B-C) grade, and the presence of bone metastasis were significantly associated with poor OS (HR 1.371, HR 3.73, HR 15.384, and HR 2.994, all P<0.05, respectively). A multivariate prognostic model including MTV and prognostic factors, such as ECOG-PS, Child-Pugh grade, and bone metastasis, further improved the identification of different OS subgroups.

Conclusion

High MTV is an adverse prognostic factor in patients with uHCC treated with a combination of immunotherapy and molecular targeted agents. Integrating PET/CT parameters with clinical prognostic factors could help to personalize immunotherapy.

Role of 18F-FDG PET/CT and sarcopenia in untreated non-small cell lung cancer with advanced stage

BACKGROUND

Sarcopenia is essential in managing advanced stage (III-IV) non-small cell lung cancer (NSCLC) but is laborious to diagnose using currently available method. This study aimed to establish a simple approach to predict sarcopenia using ¹⁸F-FDG PET/CT parameters and clinical characteristics and determine their roles in prognostication in advanced stage NSCLC.

METHODS

Untreated 202 NSCLC patients with stage III-IV were retrospectively reviewed. Sarcopenia was defined using the skeletal muscle index (SMI) measured at the third lumbar vertebra (L3). ¹⁸F-FDG PET/CT metabolic parameters of maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis of the primary tumor (SUVmax_T, MTV_T, and TLG_T) and of whole-body lesions (MTV_WB and TLG_WB) were measured. Besides, SUVmax of the psoas major muscle (SUVmax_Muscle) was measured at the L3 level. The diagnostic endpoint was the probability of sarcopenia, and the survival endpoints included progression-free survival (PFS) and overall survival (OS).

RESULTS

Among the enrolled 202 patients, 82 (40.6%) were diagnosed with sarcopenia. Higher age, male, lower BMI, and lower SUVmax_Muscle were correlated with a higher incidence of sarcopenia (P < 0.05), while age, sex, BMI, and SUVmax_Muscle were independently predictive of sarcopenia, and thus were utilized to construct a nomogram model. Multivariate Cox regression analysis revealed that sarcopenia score derived from the nomogram model, sarcopenia, stage, and TLG_WB were independently predictive of both PFS and OS.

CONCLUSION

The incidence of sarcopenia increased with declining SUVmax_Muscle in advanced stage NSCLC. Our model using age, sex, BMI, and SUVmax_Muscle might be substituted for the complicated measurement of SMI. After adjustment by stage and TLG_WB, both sarcopenia score and sarcopenia were found to be independently predictive of PFS and OS.

Tumor glycolytic profiling through 18F-FDG PET/CT predicts immune checkpoint inhibitor efficacy in advanced NSCLC

Background

A significant proportion of patients with non-small-cell lung cancer (NSCLC) do not respond to immune checkpoint inhibitors (ICIs). Since metabolic reprogramming with increased glycolysis is a hallmark of cancer and is involved in immune evasion, we used ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) to evaluate the baseline glycolytic parameters of patients with advanced NSCLC submitted to ICIs, and assessed their predictive value.

Methods

¹⁸F-FDG PET/CT results in the 3 months before ICIs treatment were included. Maximum standardized uptake values, whole metabolic tumor volume (wMTV), and whole-body total lesion glycolysis (wTLG) were evaluated. Cutoff values for high or low glycolytic categories were determined using receiver-operating characteristic curves. Progression-free survival (PFS) and overall survival (OS) were evaluated. Patients with a complete response and a matching group with resistance to ICIs underwent immunohistochemistry analysis. An unsupervised k-means clustering model integrating programmed cell death ligand 1 (PD-L1) expression, glycolytic parameters, and ICIs therapy was performed.

Results

In all, 98 patients were included. Lower baseline ¹⁸F-FDG PET/CT parameters were associated with responses to ICIs. Patients with low wMTV or wTLG had improved PFS and OS. High wTLG, strong tumor expression of glucose transporter-1, and lack of responses were significantly associated. Patients with low glycolytic parameters benefited from ICIs, regardless of chemotherapy. Conversely, those with high parameters benefited from the addition of chemotherapy. Patients with higher wTLG and lower PD-L1 were associated with progression and worse survival to ICIs monotherapy.

Conclusions

Glycolytic metabolic profiles established through baseline ¹⁸F-FDG PET/CT are useful biomarkers for evaluating ICI therapy in advanced NSCLC.

The prognostic relationship of 18F-FDG PET/CT metabolic and volumetric parameters in metastatic ALK + NSCLC

OBJECTIVE

The aim of this study is to determine the role of metabolic and volumetric parameters obtained from 18Fluorine-Fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) imaging on progression-free survival (PFS) and overall survival (OS) in patients with advanced nonsquamous cell lung carcinoma (NSCLC) with anaplastic lymphoma kinase (ALK) rearrangement.

METHODS

Pre and post-treatment PET/CT images of the ALK + NSCLC patients between January 2015 and July 2020 were evaluated. The highest standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) values were obtained from pre-tyrosine kinase inhibitor (TKI) basal PET/CT (PETpre) and post-TKI PET/CT (PETpost) images. Total MTV (tMTV) and total TLG (tTLG) values were calculated by summing MTV and TLG values in all tumor foci. The change (Δ) in pSUVmax, pMTV, pTLG, tMTV and tTLG before and after treatment was calculated.The relationship of these parameters with OS and PFS was analyzed.

RESULTS

tTLGpre, tMTVpre, pTLGpre, pMTVpre, ∆SUVmax, ∆tMTV and ∆tTLG values were found to be associated with OS; ∆tMTV, ∆tTLG, tTLGpre, tMTVpre, pTLGpre and pMTVpre were associated with PFS. The cutoff values in both predicting OS and PFS were calculated as -31.6 and 391.1 for ∆tMTV and tTLGpre, respectively. In Cox regression analysis, ∆tMTV and stage for OS and ∆tMTV and tTLGpre for PFS were obtained as prognostic factors.

CONCLUSIONS

Metabolic and volumetric parameters, especially TLG values in the whole body before treatment and change in whole body MTV value, obtained from PET/CT may be useful in predicting prognosis and determining treatment strategies for patients with advanced ALK + NSCLC.

Targeting glycolysis in non-small cell lung cancer: Promises and challenges

Metabolic disturbance, particularly of glucose metabolism, is a hallmark of tumors such as non-small cell lung cancer (NSCLC). Cancer cells tend to reprogram a majority of glucose metabolism reactions into glycolysis, even in oxygen-rich environments. Although glycolysis is not an efficient means of ATP production compared to oxidative phosphorylation, the inhibition of tumor glycolysis directly impedes cell survival and growth. This review focuses on research advances in glycolysis in NSCLC and systematically provides an overview of the key enzymes, biomarkers, non-coding RNAs, and signaling pathways that modulate the glycolysis process and, consequently, tumor growth and metastasis in NSCLC. Current medications, therapeutic approaches, and natural products that affect glycolysis in NSCLC are also summarized. We found that the identification of appropriate targets and biomarkers in glycolysis, specifically for NSCLC treatment, is still a challenge at present. However, LDHB, PDK1, MCT2, GLUT1, and PFKM might be promising targets in the treatment of NSCLC or its specific subtypes, and DPPA4, NQO1, GAPDH/MT-CO1, PGC-1α, OTUB2, ISLR, Barx2, OTUB2, and RFP180 might be prognostic predictors of NSCLC. In addition, natural products may serve as promising therapeutic approaches targeting multiple steps in glycolysis metabolism, since natural products always present multi-target properties. The development of metabolic intervention that targets glycolysis, alone or in combination with current therapy, is a potential therapeutic approach in NSCLC treatment. The aim of this review is to describe research patterns and interests concerning the metabolic treatment of NSCLC.

Therapeutic effects of in-vivo radiodynamic therapy (RDT) for lung cancer treatment: a combination of 15MV photons and 5-aminolevulinic acid (5-ALA)

Objective.Radiodynamic therapy (RDT) uses high-energy photon beams instead of visible/near-infrared light to treat deep-seated tumors that photodynamic therapy cannot achieve due to the low penetration depth of laser beams. The purpose of this study is to investigate the therapeutic effect of RDT with 15 MV photon beams combined with 5-aminolevulinic acid (5-ALA) using a mouse model.Approach.A subcutaneous C57BL/6 mouse model of KP1 small-cell lung cancer cell line was used. The tumors (N = 120) were randomized into four groups to observe individual and synergistic effects of 5-ALA and radiation treatment: control (untreated, N = 42), radiation treatment (RT) only (N = 20), 5-ALA only (N = 20), and RDT (N = 38). For the RT only and RDT groups, 4 Gy in a single fraction was delivered to the tumors using 15 MV photons. For the 5-ALA only and RDT groups, 5-ALA was injected at a dose of 100 mg kg^-1by tail-vein 4 h prior to RT. The tumor response was assessed by monitoring tumor growth using 1.5 T MR, maximum standardized uptake value (SUV_max) and total lesion glycolysis (TLG) using [¹⁸F]FDG PET/CT, and animal survival.Main results.RDT achieved a statistically significant delay in tumor growth by 52.1%, 48.1%, and 57.9% 7 days post-treatment compared to 5-ALA only, RT only, and control group (P < 0.001), respectively. There were no significant differences in tumor growth between 5-ALA only and RT only groups. An additional 38.5%-40.9% decrease in tumor growth was observed, showing a synergistic effect with RDT. Furthermore, RDT significantly decreased [¹⁸F]FDG uptakes in SUV_maxand TLG 7 days post-treatment by 47.4% and 66.5% (P < 0.001), respectively. RDT mice survived the longest of all treatment groups.Significance.RDT with 15 MV photons and 5-ALA resulted in greater tumor control compared to the control and other treatment groups. A significant synergistic effect was also observed with RDT. These preliminary results demonstrate an effective cancer treatment modality.

Full automation of total metabolic tumor volume from FDG-PET/CT in DLBCL for baseline risk assessments

Background

Current radiological assessments of ¹⁸fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging data in diffuse large B-cell lymphoma (DLBCL) can be time consuming, do not yield real-time information regarding disease burden and organ involvement, and hinder the use of FDG-PET to potentially limit the reliance on invasive procedures (e.g. bone marrow biopsy) for risk assessment.

Methods

Our aim is to enable real-time assessment of imaging-based risk factors at a large scale and we propose a fully automatic artificial intelligence (AI)-based tool to rapidly extract FDG-PET imaging metrics in DLBCL. On availability of a scan, in combination with clinical data, our approach generates clinically informative risk scores with minimal resource requirements. Overall, 1268 patients with previously untreated DLBCL from the phase III GOYA trial (NCT01287741) were included in the analysis (training: n = 846; hold-out: n = 422).

Results

Our AI-based model comprising imaging and clinical variables yielded a tangible prognostic improvement compared to clinical models without imaging metrics. We observed a risk increase for progression-free survival (PFS) with hazard ratios [HR] of 1.87 (95% CI: 1.31–2.67) vs 1.38 (95% CI: 0.98–1.96) (C-index: 0.59 vs 0.55), and a risk increase for overall survival (OS) (HR: 2.16 (95% CI: 1.37–3.40) vs 1.40 (95% CI: 0.90–2.17); C-index: 0.59 vs 0.55). The combined model defined a high-risk population with 35% and 42% increased odds of a 4-year PFS and OS event, respectively, versus the International Prognostic Index components alone. The method also identified a subpopulation with a 2-year Central Nervous System (CNS)-relapse probability of 17.1%.

Conclusion

Our tool enables an enhanced risk stratification compared with IPI, and the results indicate that imaging can be used to improve the prediction of central nervous system relapse in DLBCL. These findings support integration of clinically informative AI-generated imaging metrics into clinical workflows to improve identification of high-risk DLBCL patients.

Trial Registration

Registered clinicaltrials.gov number: NCT01287741.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-022-00476-0.

Combination of 18F-FDG PET/CT and convex probe endobronchial ultrasound elastography for intrathoracic malignant and benign lymph nodes prediction

Background

Positron emission tomography–computed tomography (PET/CT) and convex probe endobronchial ultrasound (CP-EBUS) elastography are important diagnostic methods in predicting intrathoracic lymph nodes (LNs) metastasis, but a joint analysis of the two examinations is still lacking. This study aimed to compare the diagnostic efficiency of the two methods and explore whether the combination can improve the diagnostic efficiency in differentiating intrathoracic benign LNs from malignant LNs.

Materials and Methods

LNs examined by EBUS-guided transbronchial needle aspiration (EBUS-TBNA) and PET/CT from March 2018 to June 2019 in Shanghai Chest Hospital were retrospectively analyzed as the model group. Four PET/CT parameters, namely, maximal standardized uptake value mean standardized uptake value (SUVmean), SUVmean, metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG); four quantitative elastography indicators (stiff area ratio, mean hue value, RGB, and mean gray value); and the elastography grading score of targeted LNs were analyzed. A prediction model was constructed subsequently and the dataset from July to November 2019 was used to validate the diagnostic capability of the model.

Results

A total of 154 LNs from 135 patients and 53 LNs from 47 patients were enrolled in the model and validation groups, respectively. Mean hue value and grading score were independent malignancy predictors of elastography, as well as SUVmax and TLG of PET/CT. In model and validation groups, the combination of PET/CT and elastography demonstrated sensitivity, specificity, positive and negative predictive values, and accuracy for malignant LNs diagnosis of 85.87%, 88.71%, 91.86%, 80.88%, and 87.01%, and 94.44%, 76.47%, 89.47%, 86.67%, and 88.68%, respectively. Moreover, elastography had better diagnostic accuracies than PET/CT in both model and validation groups (85.71% vs. 79.22%, 86.79% vs. 75.47%).

Conclusion

EBUS elastography demonstrated better efficiency than PET/CT and the combination of the two methods had the best diagnostic efficacy in differentiating intrathoracic benign from malignant LNs, which may be helpful for clinical application.

The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer

The diagnosis, staging and therapeutic monitoring of lung cancer were amongst the first applications for which the utility of FDG PET was documented and FDG PET/CT is now a routine diagnostic tool for clinical decision-making. As well as having high sensitivity for detection of disease sites, which provides critical information about stage, the intensity of uptake provides deeper biological characterization, while the burden of disease also has potential clinical significance. These disease characteristics can easily be quantified on delayed whole-body imaging as the maximum standardized uptake value (SUV_max) and metabolic tumor volume (MTV), respectively. There have been significant efforts to harmonize the measurement of these features, particularly within the context of clinical trials. Nevertheless, however calculated, in general, a high SUV_max and large MTV have been shown to have an adverse prognostic significance. Nevertheless, the use of these parameters in the interpretation and reporting of clinical scans remains inconsistent and somewhat controversial. This review details the current status of semi-quantitative FDG PET/CT in the evaluation of lung cancer.

Detection of clinical progression through plasma ctDNA in metastatic melanoma patients: a comparison to radiological progression

BACKGROUND

The validity of circulating tumour DNA (ctDNA) as an indicator of disease progression compared to medical imaging in patients with metastatic melanoma requires detailed evaluation.

METHODS

Here, we carried out a retrospective ctDNA analysis of 108 plasma samples collected at the time of disease progression. We also analysed a validation cohort of 66 metastatic melanoma patients monitored prospectively after response to systemic therapy.

RESULTS

ctDNA was detected in 62% of patients at the time of disease progression. For 67 patients that responded to treatment, the mean ctDNA level at progressive disease was significantly higher than at the time of response (P < 0.0001). However, only 30 of these 67 (45%) patients had a statistically significant increase in ctDNA by Poisson test. A validation cohort of 66 metastatic melanoma patients monitored prospectively indicated a 56% detection rate of ctDNA at progression, with only two cases showing increased ctDNA prior to radiological progression. Finally, a correlation between ctDNA levels and metabolic tumour burden was only observed in treatment naïve patients but not at the time of progression in a subgroup of patients failing BRAF inhibition (N = 15).

CONCLUSIONS

These results highlight the low efficacy of ctDNA to detect disease progression in melanoma when compared mainly to standard positron emission tomography imaging.

Relationship between 18F-FDG PET/CT Semi-Quantitative Parameters and International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society Classification in Lung Adenocarcinomas

Objective

To investigate the relationship between ¹⁸F-FDG PET/CT semi-quantitative parameters and the International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) histopathologic classification, including histological subtypes, proliferation activity, and somatic mutations.

Materials and Methods

This retrospective study included 419 patients (150 males, 269 females; median age, 59.0 years; age range, 23.0–84.0 years) who had undergone surgical removal of stage IA–IIIA lung adenocarcinoma and had preoperative PET/CT data of lung tumors. The maximum standardized uptake values (SUVmax), background-subtracted volume (BSV), and background-subtracted lesion activity (BSL) derived from PET/CT were measured. The IASLC/ATS/ERS subtypes, Ki67 score, and epidermal growth factor/anaplastic lymphoma kinase (EGFR/ALK) mutation status were evaluated. The PET/CT semi-quantitative parameters were compared between the tumor subtypes using the Mann–Whitney U test or the Kruskal–Wallis test. The optimum cutoff values of the PET/CT semi-quantitative parameters for distinguishing the IASLC/ATS/ERS subtypes were calculated using receiver operating characteristic curve analysis. The correlation between the PET/CT semi-quantitative parameters and pathological parameters was analyzed using Spearman’s correlation. Statistical significance was set at p < 0.05.

Results

SUVmax, BSV, and BSL values were significantly higher in invasive adenocarcinoma (IA) than in minimally IA (MIA), and the values were higher in MIA than in adenocarcinoma in situ (AIS) (all p < 0.05). Remarkably, an SUVmax of 0.90 and a BSL of 3.62 were shown to be the optimal cutoff values for differentiating MIA from AIS, manifesting as pure ground-glass nodules with 100% sensitivity and specificity. Metabolic-volumetric parameters (BSV and BSL) were better potential independent factors than metabolic parameters (SUVmax) in differentiating growth patterns. SUVmax and BSL, rather than BSV, were strongly or moderately correlated with Ki67 in most subtypes, except for the micropapillary and solid predominant groups. PET/CT parameters were not correlated with EGFR/ALK mutation status.

Conclusion

As noninvasive surrogates, preoperative PET/CT semi-quantitative parameters could imply IASLC/ATS/ERS subtypes and Ki67 index and thus may contribute to improved management of precise surgery and postoperative adjuvant therapy.

First-Line Pembrolizumab Mono- or Combination Therapy of Non-Small Cell Lung Cancer: Baseline Metabolic Biomarkers Predict Outcomes

Simple Summary

Positron-emission tomography/computed tomography (PET/CT) is used for staging of non-small cell lung cancer (NSCLC) and can help to estimate prognosis in patients treated with immune checkpoint inhibitor (ICI) therapy. Most available data in that field were derived from cohorts treated in higher therapy lines using ICI monotherapy with different drugs. Currently, however, most advanced NSCLC patients receive first-line ICI treatment, often in combination with cytotoxic chemotherapy. We evaluated prognostic PET/CT biomarkers in 85 patients receiving first-line ICI, 70 (82%) of them as a chemotherapy–ICI combination. We found that patients with a higher metabolically active tumor volume (MTV) had a significantly poorer survival and lower radiological response rate. In patients with high MTV, a concomitantly low bone marrow to liver ratio indicated a better prognosis. Our results demonstrate that PET/CT-derived biomarkers can aid therapeutic decision-making in ICI-treated NSCLC.

Abstract

Quantitative biomarkers derived from positron-emission tomography/computed tomography (PET/CT) have been suggested as prognostic variables in immune-checkpoint inhibitor (ICI) treated non-small cell lung cancer (NSCLC). As such, data for first-line ICI therapy and especially for chemotherapy–ICI combinations are still scarce, we retrospectively evaluated baseline ¹⁸F-FDG-PET/CT of 85 consecutive patients receiving first-line pembrolizumab with chemotherapy (n = 70) or as monotherapy (n = 15). Maximum and mean standardized uptake value, total metabolic tumor volume (MTV), total lesion glycolysis, bone marrow-/and spleen to liver ratio (BLR/SLR) were calculated. Kaplan–Meier analyses and Cox regression models were used to assess progression-free/overall survival (PFS/OS) and their determinant variables. Median follow-up was 12 months (M; 95% confidence interval 10–14). Multivariate selection for PFS/OS revealed MTV as most relevant PET/CT biomarker (p < 0.001). Median PFS/OS were significantly longer in patients with MTV ≤ 70 mL vs. >70 mL (PFS: 10 M (4–16) vs. 4 M (3–5), p = 0.001; OS: not reached vs. 10 M (5–15), p = 0.004). Disease control rate was 81% vs. 53% for MTV ≤/> 70 mL (p = 0.007). BLR ≤ 1.06 vs. >1.06 was associated with better outcomes (PFS: 8 M (4–13) vs. 4 M (3–6), p = 0.034; OS: 19 M (12-/) vs. 6 M (4–12), p = 0.005). In patients with MTV > 70 mL, concomitant BLR ≤ 1.06 indicated a better prognosis. Higher MTV is associated with inferior PFS/OS in first-line ICI-treated NSCLC, with BLR allowing additional risk stratification.

Prognostication Based on Texture Analysis of Baseline 18F Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Nonsmall-Cell Lung Carcinoma Patients Who Underwent Platinum-Based Chemotherapy as First-Line Treatment

Objective:

Our study aims to establish the potential for tumor heterogeneity evaluated using ¹⁸F fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) texture analysis in nonsmall-cell lung carcinoma (NSCLC) patients who underwent platinum-based chemotherapy to provide an independent marker for overall survival (OS) of more than 1-year.

Materials and Methods:

A total of 42 patients (34 male and 8 female) with biopsy-proven NSCLC and mean age 55.33 ± 10.71 years who underwent a baseline F-18 FDG PET/CT and received platinum-based chemotherapy as first-line treatment were retrospectively included in the study. Ten first order, 21 s order texture parameters and 7 SUV and metabolic tumor volume (MTV) based metabolic parameters were calculated. All these parameters were compared between the two survival groups based on OS ≥1 year and OS <1 year. Cut-offs of significant parameters were determined using receiver operating characteristic curve analysis. Survival patterns were compared by log-rank test and presented using Kaplan-Meier curves. Cox proportion hazard model was used to determine the independent prognostic marker for 1 year OS.

Results:

In univariate survival analysis, 3 first order texture parameters (i.e. mean, median, root mean square with hazard ratios [HRs] 2.509 [P = 0.034], 2.590 [P = 0.05], 2.509 [P = 0.034], respectively) and 6 s order texture parameters (i.e. mean, auto correlation, cluster prominence, cluster shade, sum average and sum variance with HRs 2.509 [P = 0.034], 2.509 [P = 0.034], 3.929 [0.007], 2.903 [0.018], 2.954 [0.016] and 2.906 [0.014], respectively) were significantly associated with 1 year OS in these patients. Among the metabolic parameters, only metabolic tumor volume whole-body was significantly associated with 1 year OS. In multivariate survival analysis, cluster prominence came out as the independent predictor of 1 year OS.

Conclusion:

Texture analysis based on F-18 FDG PET/CT is potentially beneficial in the prediction of OS ≥1 year in NSCLC patients undergoing platinum-based chemotherapy as first-line treatment. Thus, can be used to stratify the patients which will not be benefitted with platinum-based chemotherapy and essentially needs to undergo some other therapy option.

The ratio between the whole-body and primary tumor burden, measured on 18F-FDG PET/CT studies, as a prognostic indicator in advanced non-small cell lung cancer

Objective

To determine whether the whole-body tumor burden, as quantified by ¹⁸F-fluorodeoxyglucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT), is a prognostic indicator in advanced (stage III or IV) non-small cell lung cancer (NSCLC).

Materials and Methods

This was a prospective study in which we evaluated ¹⁸F-FDG PET/CT staging parameters to quantify tumor burdens in patients with stage III or IV NSCLC. The following parameters were evaluated for the whole body (including the primary tumor) and for the primary tumor alone, respectively: maximum standardized uptake volume (wbSUV_max and tuSUV_max); metabolic tumor volume (wbMTV and tuMTV); and total lesion glycolysis (wbTLG and tuTLG). To determine whether the ¹⁸F-FDG PET/CT parameters were associated with overall survival (OS) and progression-free survival (PFS), we evaluated the wbSUV_max/tuSUV_max, wbMTV/tuMTV, and wbTLG/tuTLG ratios.

Results

¹⁸F-FDG PET/CT was performed for staging in 52 patients who were followed for a median of 11.0 months (mean, 11.7 months). The estimated median PFS and OS were 9.6 months and 11.6 months, respectively. In the univariate analysis, OS was found to correlate significantly with wbTLG (hazard ratio [HR] = 1.001; 95% confidence interval [95 CI]: 1.000-1.001; p = 0.0361) and with the wbTLG/tuTLG ratio (HR = 1.705; 95% CI: 1.232-2.362; p = 0.0013). In the multivariate analysis, only the wbTLG/tuTLG ratio was independently associated with OS (HR = 1.660; 95% CI: 1.193-2.310; p = 0.0027).

Conclusion

The wbTLG/tuTLG ratio is an independent prognostic indicator of OS in advanced-stage NSCLC.

Metabolic active tumour volume quantified on [18F]FDG PET/CT further stratifies TNM stage IV non-small cell lung cancer patients

PURPOSE

This study aimed to assess whether the whole body metabolic active tumour volume (MTV_WB), quantified on staging [¹⁸F]FDG PET/CT, could further stratify stage IV non-small cell lung cancer (NSCLC) patients.

METHODS

A group of 160 stage IV NSCLC patients, submitted to staging [¹⁸F]FDG PET/CT between July 2010 and May 2020, were retrospectively evaluated. MTV_WB was quantified. Univariate and multivariate Cox regressions were carried out to assess correlation with overall survival (OS). C-statistic was used to test predictive power. Kaplan-Meier survival curves with Log-Rank tests were performed to compute statistical differences between strata from dichotomized variables and to calculate the estimated mean survival times (EMST). Survival rates at 1 and 5 years were calculated.

RESULTS

MTV_WB was a statistically significant predictor of OS on univariate (p < 0.0001) and multivariate analyses (p < 0.0001). The multivariate model with MTV_WB (Cindex ± SE = 0.657 ± 0.024) worked significantly better as an OS predictor than the cTNM model (Cindex ± SE = 0.544 ± 0.028) (p = 0.003). An EMST of 29.207 ± 3.627(95% CI 22.099-36.316) months and an EMST of 10.904 ± 1.171(95% CI 8.609-13.199) months (Log-Rank p < 0.0001) were determined for patients with MTV_WB < 104.3 and MTV_WB ≥ 104.3, respectively. In subsamples of stage IVA (cut-off point = 114.5) and IVB patients (cut-off point = 191.1), statistically significant differences between EMST were also reported, with p-values of 0.0001 and 0.0002, respectively. In both substages and in the entire cohort, patients with MTV_WB ≥ cut-off points had lower EMST and survival rates.

CONCLUSION

Baseline MTV_WB, measured on staging [¹⁸F]FDG PET/CT, further stratifies stage IV NSCLC patients. This parameter is an independent predictor of OS and provides valuable prognostic information over the 8th edition of cTNM staging.

Prognostic significance of volume-based 18F-FDG PET/CT parameters and correlation with PD-L1 expression in patients with surgically resected lung adenocarcinoma

The aim of this study was to retrospectively analyze 18F-FDG positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic variables, programmed death-ligand 1 (PD-L1) and phosphorylated signal transducer and activator of transcription 3 (p-STAT3) tumor expression, and other factors as predictors of disease-free survival (DFS) in patients with lung adenocarcinoma (LUAD) (stage IA-IIIA) who underwent surgical resection. We still lack predictor of immune checkpoint (programmed cell death-1 [PD-1]/PD-L1) inhibitors. Herein, we investigated the correlation between metabolic parameters from 18F-FDG PET/CT and PD-L1 expression in patients with surgically resected LUAD.Seventy-four patients who underwent 18F-FDG PET/CT prior to treatment were consecutively enrolled. The main 18F-FDG PET/CT-derived variables were primary tumor maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Surgical tumor specimens were analyzed for PD-L1 and p-STAT3 expression using immunohistochemistry. Correlations between immunohistochemistry results and 18F-FDG PET/CT-derived variables were compared. Associations of PD-L1 and p-STAT3 tumor expression, 18F-FDG PET/CT-derived variables, and other factors with DFS in resected LUAD were evaluated.All tumors were FDG-avid. The cutoff values of low and high SUVmax, MTV, and TLG were 12.60, 14.87, and 90.85, respectively. The results indicated that TNM stage, PD-L1 positivity, and high 18F-FDG PET/CT metabolic volume parameters (TLG ≥90.85 or MTV ≥14.87) were independent predictors of worse DFS in resected LUAD. No 18F-FDG metabolic parameters associated with PD-L1 expression were observed (chi-square test), but we found that patients with positive PD-L1 expression have significantly higher SUVmax (P = .01), MTV (P = .00), and TLG (P = .00) than patients with negative PD-L1 expression.18F-FDG PET/CT metabolic volume parameters (TLG ≥90.85 or MTV ≥14.87) were more helpful in prognostication than the conventional parameter (SUVmax), PD-L1 expression was an independent predictor of DFS in patients with resected LUAD. Metabolic parameters on 18F-FDG PET/CT have a potential role for 18F-FDG PET/CT in selecting candidate LUAD for treatment with checkpoint inhibitors.

Prognostic Value of Metabolic Tumor Parameters in Pretreatment 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography Scan in Advanced Non-Small Cell Lung Cancer

Objective:

This retrospective study aimed to investigate whether metabolic parameters of primary tumour i.e. maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) predict overall survival (OS) in patients with advanced stage non-small cell lung cancer (NSCLC).

Materials and Methods:

SUVmax, MTV and TLG of the primary tumors were measured in staging ¹⁸F-Fluorodeoxyglucose Positron emission tomography- Computed tomography (¹⁸F-FDG PET/CT) scan of 97 NSCLC patients by gradient based tumour segmentation method. Prognostic ability was assessed for overall survival (OS) of the patients.

Result:

The median follow-up period of the study was 15.84 months (range 1.3 to 47.97 months).The estimated median OS was 11.29 months (range 1.37 to 38.63 months). Total of 40 (41.24%) patients had progressive disease and 21 (21.65%) patients died during the follow up period. Receiver Operating Characteristic (ROC) analysis showed that the area under the curve (AUC) for MTV was significant (area = 0.652 ± 0.065; 95% CI = 0.548 – 0.746; P = 0.020). Kaplan-Meier survival curves showed that the OS differences between the groups of patients who were dichotomized by the median value of MTV (38.76 ml, P = 0.0150) and TLG (301.69 ml, P = 0.0046) were significant. MTV (hazard ratio = 4.524; 95% CI = 1.244 – 16.451; P = 0.022) was found to be an independent prognostic factor for OS in multivariate analysis.

Conclusion:

MTV of the primary tumor is a potential prognostic parameter for OS in our population of advanced NSCLC patients independent of other risk factors.

Prognostic value of metabolic parameters on 18F-fluorodeoxyglucose positron tomography/computed tomography in classical rectal adenocarcinoma

We aimed to investigate the prognostic value of the metabolic parameters of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in classical rectal adenocarcinoma (CRAC). We retrospectively reviewed 149 patients with CRAC who underwent preoperative ¹⁸F-FDG PET/CT at initial diagnosis followed by curative surgical resection. ¹⁸F-FDG PET/CT metabolic parameters including maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) for disease-free survival (DFS) and overall survival (OS) were evaluated for prognostic significance by univariate and multivariate analyses, along with conventional risk factors including pathologic T (pT) stage, lymph node (LN) metastasis, lymphovascular invasion (LVI), perineural invasion (PNI), and preoperative carcinoembryonic antigen (CEA) level. On univariate analysis, high pT stage, positive LN metastasis, LVI, PNI, MTV, and TLG were significant prognostic factors affecting DFS (all P < 0.05), while CEA level, high pT stage, positive LN metastasis, LVI, PNI, MTV, and TLG affected OS (all P < 0.05). On multivariate analysis, positive LN metastasis, LVI, MTV, and TLG were independent prognostic factors affecting DFS (all P < 0.05), while CEA level, positive LN metastasis, and MTV affected OS (all P < 0.05). Thus, the volume-based metabolic parameters from preoperative ¹⁸F-FDG PET/CT scans are independent prognostic factors in patients with CRAC.

A Bayesian approach to tissue-fraction estimation for oncological PET segmentation

Tumor segmentation in oncological PET is challenging, a major reason being the partial-volume effects (PVEs) that arise due to low system resolution and finite voxel size. The latter results in tissue-fraction effects (TFEs), i.e. voxels contain a mixture of tissue classes. Conventional segmentation methods are typically designed to assign each image voxel as belonging to a certain tissue class. Thus, these methods are inherently limited in modeling TFEs. To address the challenge of accounting for PVEs, and in particular, TFEs, we propose a Bayesian approach to tissue-fraction estimation for oncological PET segmentation. Specifically, this Bayesian approach estimates the posterior mean of the fractional volume that the tumor occupies within each image voxel. The proposed method, implemented using a deep-learning-based technique, was first evaluated using clinically realistic 2D simulation studies with known ground truth, in the context of segmenting the primary tumor in PET images of patients with lung cancer. The evaluation studies demonstrated that the method accurately estimated the tumor-fraction areas and significantly outperformed widely used conventional PET segmentation methods, including a U-net-based method, on the task of segmenting the tumor. In addition, the proposed method was relatively insensitive to PVEs and yielded reliable tumor segmentation for different clinical-scanner configurations. The method was then evaluated using clinical images of patients with stage IIB/III non-small cell lung cancer from ACRIN 6668/RTOG 0235 multi-center clinical trial. Here, the results showed that the proposed method significantly outperformed all other considered methods and yielded accurate tumor segmentation on patient images with Dice similarity coefficient (DSC) of 0.82 (95% CI: 0.78, 0.86). In particular, the method accurately segmented relatively small tumors, yielding a high DSC of 0.77 for the smallest segmented cross-section of 1.30 cm². Overall, this study demonstrates the efficacy of the proposed method to accurately segment tumors in PET images.

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic-Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

We investigated whether the combination of primary tumor and nodal ¹⁸F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment ¹⁸F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell’s concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group.

Emerging role of artificial intelligence in nuclear medicine

The role of artificial intelligence is increasing in all branches of medicine. The emerging role of artificial intelligence applications in nuclear medicine is going to improve the nuclear medicine clinical workflow in the coming years. Initial research outcomes are suggestive of increasing role of artificial intelligence in nuclear medicine workflow, particularly where selective automation tasks are of concern. Artificial intelligence-assisted planning, dosimetry and procedure execution appear to be areas for rapid and significant development. The role of artificial intelligence in more directly imaging-related tasks, such as dose optimization, image corrections and image reconstruction, have been particularly strong points of artificial intelligence research in nuclear medicine. Natural Language Processing (NLP)-based text processing task is another area of interest of artificial intelligence implementation in nuclear medicine.

Guidance on Imaging for Invasive Pulmonary Aspergillosis and Mucormycosis: From the Imaging Working Group for the Revision and Update of the Consensus Definitions of Fungal Disease from the EORTC/MSGERC

BACKGROUND

Clinical imaging in suspected invasive fungal disease (IFD) has a significant role in early detection of disease and helps direct further testing and treatment. Revised definitions of IFD from the EORTC/MSGERC were recently published and provide clarity on the role of imaging for the definition of IFD. Here, we provide evidence to support these revised diagnostic guidelines.

METHODS

We reviewed data on imaging modalities and techniques used to characterize IFDs.

RESULTS

Volumetric high-resolution computed tomography (CT) is the method of choice for lung imaging. Although no CT radiologic pattern is pathognomonic of IFD, the halo sign, in the appropriate clinical setting, is highly suggestive of invasive pulmonary aspergillosis (IPA) and associated with specific stages of the disease. The ACS is not specific for IFD and occurs in the later stages of infection. By contrast, the reversed halo sign and the hypodense sign are typical of pulmonary mucormycosis but occur less frequently. In noncancer populations, both invasive pulmonary aspergillosis and mucormycosis are associated with "atypical" nonnodular presentations, including consolidation and ground-glass opacities.

CONCLUSIONS

A uniform definition of IFD could improve the quality of clinical studies and aid in differentiating IFD from other pathology in clinical practice. Radiologic assessment of the lung is an important component of the diagnostic work-up and management of IFD. Periodic review of imaging studies that characterize findings in patients with IFD will inform future diagnostic guidelines.

One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer

Purpose

The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST).

Methods

Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass (SUL_peak) of up-to-5 hottest target lesions was measured at each time point. The percent changes of SUL_peak of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of SUL_peak values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in SUL_peak; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics.

Results

A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with ¹⁸F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson's r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89).

Conclusion

Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13139-021-00697-4.

Prone position [18F]FDG PET/CT to reduce respiratory motion artefacts in the evaluation of lung nodules

OBJECTIVES

2-Deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron-emission tomography/computed tomography (PET/CT) is widely used to evaluate lung nodules, although respiratory motion artefacts may occur. We investigated the value of prone position PET/CT (pPET/CT) in lung nodule evaluation compared with standard supine position PET/CT (sPET/CT).

METHODS

We retrospectively reviewed 28 consecutive patients (20 men; age, 65.6 ± 12.1 years) with a lung nodule (size, 16.8 ± 5.5 mm) located below the sub-carinal level who underwent [¹⁸F]FDG PET/CT in a standard supine position and additional prone position. The maximum standardised uptake value (SUV_max), metabolic tumour volume (MTV), difference of diaphragm position between PET and CT (DDP), Dice's similarity coefficient (DSC) and occurrence of mis-registration were analysed. The [¹⁸F]FDG uptake of 20 biopsy-confirmed (15 malignant) nodules was evaluated visually.

RESULTS

pPET/CT yielded a significantly higher SUV_max, lower MTV and shorter DDP than with sPET/CT (p = 0.043, 0.007 and 0.021, respectively). Mis-registration occurred in 53.6% of cases in sPET/CT and in 28.6% of cases in pPET/CT (p = 0.092). Among the 15 patients with mis-registration in sPET/CT, 10 patients (66.7%) did not show mis-registration in pPET/CT. DSC was higher in pPET/CT than in sPET/CT in 18 out of 28 patients (64.3%). In visual analysis, malignant nodules exhibited a higher [¹⁸F]FDG uptake positivity than benign nodules in pPET/CT (93.3% vs. 40.0%, p = 0.032) but not in sPET/CT (80.0% vs. 40.0%, p = 0.131).

CONCLUSIONS

pPET/CT reduces respiratory motion artefact and enables more-precise measurements of PET parameters.

KEY POINTS

• In prone position PET/CT, the decrease in the blurring effect caused by reduced respiratory motion resulted in a higher SUV_max and lower MTV in lung nodules than that with supine position PET/CT. • Prone position PET/CT was useful to interpret correctly malignant lung nodules as being positive in individual cases that had a negative result in supine position PET/CT.

Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience

Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pembrolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume-wMTV, total lesion glycolysis-wTLG, higher standardized uptake volume maximum and mean-SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respectively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.

Assessing tumor angiogenesis using dynamic contrast-enhanced integrated magnetic resonance-positron emission tomography in patients with non-small-cell lung cancer

Background

Angiogenesis assessment is important for personalized therapeutic intervention in patients with non-small-cell lung cancer (NSCLC). This study investigated whether radiologic parameters obtained by dynamic contrast-enhanced (DCE)-integrated magnetic resonance-positron emission tomography (MR-PET) could be used to quantitatively assess tumor angiogenesis in NSCLC.

Methods

This prospective cohort study included 75 patients with NSCLC who underwent DCE-integrated MR-PET at diagnosis. The following parameters were analyzed: metabolic tumor volume (MTV), maximum standardized uptake value (SUV_max), reverse reflux rate constant (k_ep), volume transfer constant (K^trans), blood plasma volume fraction (v_p), extracellular extravascular volume fraction (v_e), apparent diffusion coefficient (ADC), and initial area under the time-to-signal intensity curve at 60 s post enhancement (iAUC₆₀). Serum biomarkers of tumor angiogenesis, including vascular endothelial growth factor-A (VEGF-A), angiogenin, and angiopoietin-1, were measured by enzyme-linked immunosorbent assays simultaneously.

Results

Serum VEGF-A (p = 0.002), angiogenin (p = 0.023), and Ang-1 (p <  0.001) concentrations were significantly elevated in NSCLC patients compared with healthy individuals. MR-PET parameters, including MTV, K^trans, and k_ep, showed strong linear correlations (p <  0.001) with serum angiogenesis-related biomarkers. Serum VEGF-A concentrations (p = 0.004), MTV values (p <  0.001), and k_ep values (p = 0.029) were significantly higher in patients with advanced-stage disease (stage III or IV) than in those with early-stage disease (stage I or II). Patients with initial higher values of angiogenesis-related MR-PET parameters, including MTV > 30 cm³ (p = 0.046), K^trans > 200 10^− 3/min (p = 0.069), and k_ep > 900 10^− 3/min (p = 0.048), may have benefited from angiogenesis inhibitor therapy, which thus led to significantly longer overall survival.

Conclusions

The present findings suggest that DCE-integrated MR-PET provides a reliable, non-invasive, quantitative assessment of tumor angiogenesis; can guide the use of angiogenesis inhibitors toward longer survival; and will play an important role in the personalized treatment of NSCLC.

18F-FDG PET/CT and circulating tumor cells in treatment-naive patients with non-small-cell lung cancer

PURPOSE

This study retrospectively investigated the clinical utility of 2-deoxy-18F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) and circulating tumor cells (CTCs) in the diagnosis and prognosis of treatment-naive patients with non-small-cell lung cancer (NSCLC).

METHODS

The blood samples of treatment-naive patients with NSCLC were collected for CTCs detection, and the tumor metabolic parameters of ¹⁸F-FDG PET/CT, including maximum standard uptake value (SUVmax), metabolic tumor volume of primary lesion (MTV-P) and combination of primary lesion and metastases (MTV-C), and total lesion glycolysis of primary lesion (TLG-P) and combination of primary lesion and metastases (TLG-C), were analyzed. Age, sex, smoking, serum tumor markers, tumor size, location, TNM stage, and genetic mutations were also reviewed. Moreover, progression-free survival (PFS) and overall survival (OS) of these patients were analyzed.

RESULTS

A total of 309 patients with NSCLC (200 men, 109 women; mean age: 61 ± 9 years) were enrolled in this study, including 217 patients with adenocarcinoma and 92 with squamous cell carcinoma. Of the 309 cases, 11 were misdiagnosed with benign diseases by ¹⁸F-FDG PET/CT. CTCs positivity was detected in 234 cases. The sensitivity of ¹⁸F-FDG PET/CT and CTCs in NSCLC were 96.4% and 75.7%, respectively. SUVmax, MTV-P, TLG-P, MTV-C, TLG-C, tumor size, and serum CYFRA211 levels were significantly higher in CTCs positive group than negative group; and advanced TNM stage, squamous cell carcinoma, and EGFR wild type presented higher CTCs positivity. Multivariate logistic regression analysis revealed that SUVmax was significantly associated with CTCs positivity. Multivariate cox regression analysis showed that TLG-P, TLG-C, and CTCs were independent predictors of PFS in patients with NSCLC, and TLG-C and CTCs were independent predictors of OS.

CONCLUSIONS

¹⁸F-FDG PET/CT was superior to CTCs in the diagnosis of treatment-naive patients with NSCLC. The levels of CTCs in the peripheral blood were associated with tumor glucose metabolism in NSCLC. Metabolic parameters of ¹⁸F-FDG PET/CT and CTCs could separately predict the outcomes of treatment-naive patients with NSCLC.

Prognostic Significance of Metabolic Parameters by 18F-FDG PET/CT in Thymic Epithelial Tumors

Simple Summary

Thymic epithelial tumors have variable prognoses that depend on histological subtype, and ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) currently plays an important part in oncology images. Thus, we prosecuted a retrospective review of data from 83 patients with thymic epithelial tumors who underwent pretreatment ¹⁸F-FDG PET/CT and investigated the prognostic significance along with WHO classification, Masaoka stage, and volumetric ¹⁸F-PET parameters. Masaoka stage, histologic type, treatment modality, maximum standardized uptake values (SUV_max), average standardized uptake values (SUV_avg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were significant prognostic factors for time-to-progression on univariate survival analysis. On multivariate analysis, SUV_avg and Masaoka stage were important independent prognostic factors for progression-free survival in thymic epithelial tumors.

Abstract

Background: Imaging tumor FDG avidity could complement prognostic implication in thymic epithelial tumors. We thus investigated the prognostic value of volume-based ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/CT parameters in thymic epithelial tumors with other clinical prognostic factors. Methods: This is a retrospective study that included 83 patients who were diagnosed with thymic epithelial tumors and underwent pretreatment ¹⁸F-FDG PET/CT. PET parameters, including maximum and average standardized uptake values (SUV_max, SUV_avg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), were measured with a threshold of SUV 2.5. Univariate and multivariate analysis of PET parameters and clinicopathologic variables for time-to-progression was performed by using a Cox proportional hazard regression model. Results: There were 21 low-risk thymomas (25.3%), 27 high-risk thymomas (32.5%), and 35 thymic carcinomas (42.2%). Recurrence or disease progression occurred in 24 patients (28.9%). On univariate analysis, Masaoka stage (p < 0.001); histologic types (p = 0.009); treatment modality (p = 0.001); and SUV_max, SUV_avg, MTV, and TLG (all p < 0.001) were significant prognostic factors. SUV_avg (p < 0.001) and Masaoka stage (p = 0.001) were independent prognostic factors on multivariate analysis. Conclusion: SUV_avg and Masaoka stage are independent prognostic factors in thymic epithelial tumors.

Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers

Human cancers are biologically and morphologically heterogeneous. A variety of clonal populations emerge within these neoplasms and their interaction leads to complex spatiotemporal dynamics during tumor growth. We studied the reshaping of metabolic activity in human cancers by means of continuous and discrete mathematical models and matched the results to positron emission tomography (PET) imaging data. Our models revealed that the location of increasingly active proliferative cellular spots progressively drifted from the center of the tumor to the periphery, as a result of the competition between gradually more aggressive phenotypes. This computational finding led to the development of a metric, normalized distance from 18F-fluorodeoxyglucose (18F-FDG) hotspot to centroid (NHOC), based on the separation from the location of the activity (proliferation) hotspot to the tumor centroid. The NHOC metric can be computed for patients using 18F-FDG PET-computed tomography (PET/CT) images where the voxel of maximum uptake (standardized uptake value [SUV]max) is taken as the activity hotspot. Two datasets of 18F-FDG PET/CT images were collected, one from 61 breast cancer patients and another from 161 non-small-cell lung cancer patients. In both cohorts, survival analyses were carried out for the NHOC and for other classical PET/CT-based biomarkers, finding that the former had a high prognostic value, outperforming the latter. In summary, our work offers additional insights into the evolutionary mechanisms behind tumor progression, provides a different PET/CT-based biomarker, and reveals that an activity hotspot closer to the tumor periphery is associated to a worst patient outcome.

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.

Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG-PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis

Positron emission tomography (PET) imaging with 2-deoxy-2-[¹⁸F]-fluorodeoxyglucose (FDG) was proposed as prognostic marker in radiotherapy. Various uptake metrics and cut points were used, potentially leading to inflated effect estimates. Here, we performed a meta-analysis and systematic review of the prognostic value of pretreatment FDG–PET in head and neck squamous cell carcinoma (HNSCC) and non-small cell lung cancer (NSCLC), with tests for publication bias. Hazard ratio (HR) for overall survival (OS), disease free survival (DFS), and local control was extracted or derived from the 57 studies included. Test for publication bias was performed, and the number of statistical tests and cut-point optimizations were registered. Eggers regression related to correlation of SUVmax with OS/DFS yielded p = 0.08/p = 0.02 for HNSCC and p < 0.001/p = 0.014 for NSCLC. No outcomes showed significant correlation with SUVmax, when adjusting for publication bias effect, whereas all four showed a correlation in the conventional meta-analysis. The number of statistical tests and cut points were high with no indication of improvement over time. Our analysis showed significant evidence of publication bias leading to inflated estimates of the prognostic value of SUVmax. We suggest that improved management of these complexities, including predefined statistical analysis plans, are critical for a reliable assessment of FDG–PET.

Semi-automatic evaluation of baseline whole-body tumor burden as an imaging biomarker of 68Ga-PSMA-11 PET/CT in newly diagnosed prostate cancer

OBJECTIVES

The prognostic value of baseline tumor burden of prostate cancer was rarely studied. We aimed to evaluate the whole-body tumor burden of ⁶⁸Ga- prostate specific membrane antigen-HBED-CC (⁶⁸Ga-PSMA-11) PET/CT in newly diagnosed prostate cancer semi-automatically, and explore its preliminary application in predicting prognosis.

METHODS

Similar to metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of ¹⁸F-FDG PET/CT, ⁶⁸Ga-PSMA-11 PET/CT tumor burden parameters including whole-body PSMA tumor volume (wbPSMA-TV) and whole-body total lesions PSMA uptake (wbTL-PSMA) were acquired semi-automatically. The intra-observer and inter-observer reliability was analyzed. The relationship between tumor burden and prostate-specific antigen (PSA) value or Gleason score was investigated. The preliminary application of tumor burden in predicting progression-free survival (PFS) was explored.

RESULTS

Fifty-nine newly diagnosed prostate cancer patients were retrospectively analyzed. Semi-automatic quantification of whole-body tumor burden had excellent intra-observer and inter-observer consistency [all intra-class correlation coefficient (ICC) > 0.990]. wbPSMA-TV and wbTL-PSMA were 32.6 (range 1.0-3968.2) cm³ and 161.9 (range 6.0-24971.7), respectively. wbPSMA-TV and wbTL-PSMA correlated with PSA (r = 0.858, p < 0.001; r = 0.879, p < 0.001) and Gleason score (r = 0.793, p < 0.001; r = 0.805, p < 0.001) significantly. In univariate analysis, wbPSMA-TV, wbTL-PSMA, SUV_max, SUV_peak, SUV_mean, PSMA-TV, TL-PSMA of primary tumor, fPSA and Gleason score were independent significant predictors of PFS (all p < 0.05). Moreover, in multivariate analysis, wbTL-PSMA [hazard ratio (HR): 1.001, p = 0.014] and Gleason score (HR: 5.124, p = 0.031) can significantly predict progression-free prognosis.

CONCLUSIONS

As imaging biomarkers, wbPSMA-TV and wbTL-PSMA correlated with clinical characteristics significantly. High wbTL-PSMA or Gleason score was associated with shorter PFS of newly diagnosed prostate cancer independently.

Thoracic positron emission tomography: 18F-fluorodeoxyglucose and beyond

Ongoing technologic and therapeutic advancements in medicine are now testing the limits of conventional anatomic imaging techniques. The ability to image physiology, rather than simply anatomy, is critical in the management of multiple disease processes, especially in oncology. Nuclear medicine has assumed a leading role in detecting, diagnosing, staging and assessing treatment response of various pathologic entities, and appears well positioned to do so into the future. When combined with computed tomography (CT) or magnetic resonance imaging (MRI), positron emission tomography (PET) has become the sine quo non technique of evaluating most solid tumors especially in the thorax. PET/CT serves as a key imaging modality in the initial evaluation of pulmonary nodules, often obviating the need for more invasive testing. PET/CT is essential to staging and restaging in bronchogenic carcinoma and offers key physiologic information with regard to treatment response. A more recent development, PET/MRI, shows promise in several specific lung cancer applications as well. Additional recent advancements in the field have allowed PET to expand beyond imaging with ¹⁸F-flurodeoxyglucose (FDG) alone, now with the ability to specifically image certain types of cell surface receptors. In the thorax this predominantly includes ⁶⁸Ga-DOTATATE which targets the somatostatin receptors abundantly expressed in neuroendocrine tumors, including bronchial carcinoid. This receptor targeted imaging technique permits targeting these tumors with therapeutic analogues such as ¹⁷⁷Lu labeled DOTATATE. Overall, the proper utilization of PET in the thorax has the ability to directly impact and improve patient care.