PET quantification with a histogram derived total activity metric: superior quantitative consistency compared to total lesion glycolysis with absolute or relative SUV thresholds in phantoms and lung cancer patients

[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.

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.

Preoperative 18F-FDG PET/CT and CT radiomics for identifying aggressive histopathological subtypes in early stage lung adenocarcinoma

Lung adenocarcinoma (ADC) is the most common non-small cell lung cancer. Surgical resection is the primary treatment for early-stage lung ADC while lung-sparing surgery is an alternative for non-aggressive cases. Identifying histopathologic subtypes before surgery helps determine the optimal surgical approach. Predominantly solid or micropapillary (MIP) subtypes are aggressive and associated with a higher likelihood of recurrence and metastasis and lower survival rates. This study aims to non-invasively identify these aggressive subtypes using preoperative 18F-FDG PET/CT and diagnostic CT radiomics analysis. We retrospectively studied 119 patients with stage I lung ADC and tumors ≤ 2 cm, where 23 had aggressive subtypes (18 solid and 5 MIPs). Out of 214 radiomic features from the PET/CT and CT scans and 14 clinical parameters, 78 significant features (3 CT and 75 PET features) were identified through univariate analysis and hierarchical clustering with minimized feature collinearity. A combination of Support Vector Machine classifier and Least Absolute Shrinkage and Selection Operator built predictive models. Ten iterations of 10-fold cross-validation (10 ×10-fold CV) evaluated the model. A pair of texture feature (PET GLCM Correlation) and shape feature (CT Sphericity) emerged as the best predictor. The radiomics model significantly outperformed the conventional predictor SUVmax (accuracy: 83.5% vs. 74.7%, p = 9e-9) and identified aggressive subtypes by evaluating FDG uptake in the tumor and tumor shape. It also demonstrated a high negative predictive value of 95.6% compared to SUVmax (88.2%, p = 2e-10). The proposed radiomics approach could reduce unnecessary extensive surgeries for non-aggressive subtype patients, improving surgical decision-making for early-stage lung ADC patients.

The Quest for an Accurate Functional Tumor Volume with 68Ga-DOTATATE PET/CT

⁶⁸Ga-labeled somatostatin analog (SSA) PET/CT is now a standard-of-care component in the management of neuroendocrine tumors (NETs). However, treatment response for NETs is still assessed with morphologic size measurements from other modalities, which can result in inaccuracy about the disease burden. Functional tumor volume (FTV) acquired from SSA PET/CT has been suggested as a possible metric, but no validated measurement tool to measure FTV exists. We tested the precision of multiple FTV computational approaches compared with morphologic volume measurements to identify a candidate for incorporation into future FTV studies to assess tumor burden more completely and accurately. Methods: The clinical and imaging data of 327 NET patients were collected at Memorial Sloan Kettering Cancer Center between December 2016 and April 2018. Patients were required to have SSA PET/CT and dedicated CT scans within 6 wk and were excluded if they had any intervention between scans. When paired studies were evaluated, 150 correlating lesions demonstrated SSA. Lesions were excluded if they contained necrotic components or were lobulated. This exclusion resulted in 94 lesions in 20 patients. The FTV for each lesion was evaluated with a hand-drawn assessment and 3 automated techniques: 50% threshold from SUV_max, 42% threshold from SUV_max, and background-subtracted lesion activity. These measurements were compared with volume calculated from morphologic volume measurements. Results: The FTV calculation methods showed varying correlations with morphologic volume measurements. FTV using a 42% threshold had a 0.706 correlation, hand-drawn volume from PET imaging had a 0.657 correlation, FTV using a 50% threshold had a 0.645 correlation, and background-subtracted lesion activity had a 0.596 correlation. The Bland-Altman plots indicated that all FTV methods had a positive mean difference from morphologic volume, with a 50% threshold showing the smallest mean difference. Conclusion: FTV determined with thresholding of SUV_max demonstrated the strongest correlation with traditional morphologic lesion volume assessment and the least bias. This method was more accurate than FTV calculated from hand-drawn volume assessments. Threshold-based automated FTV assessment promises to better determine disease extent and prognosis in patients with NETs.

Utility and limitations of metabolic parameters in head and neck cancer: finding a practical segmentation method

PURPOSE

Although metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have shown good prognostic value in head and neck cancer (HNC), there are still many issues to resolve before their potential application in standard clinical practice. The purpose of this study was to compare the discrimination ability of two relevant segmentation methods in HNC and to evaluate the potential benefit of adding lymph nodes' metabolism (LNM) to the measurements.

METHODS

We retrospectively analyzed a recently published database of 62 patients with HNC treated with chemoradiotherapy. MTV and TLG were measured using an absolute threshold of SUV2.5. Comparison analysis with previously published background-level threshold (BLT) results was done through Concordance index (C-index) in eight prognostic models.

RESULTS

BLT obtained better C-index values in five out of the eight models. The addition of LNM improved C-index values in six of the prognostic models.

CONCLUSION

We found a potential benefit in adding LNM to the main tumor measurements, as well as in using a BLT for MTV segmentation compared to the most commonly used SUV2.5 threshold. Despite its limitations, this study suggests a practical and simple manner to use these parameters in standard clinical practice, aiming to help elaborate a general consensus.

Semiautomatic assessment of whole-body tumor burden with 18F-PSMA-1007 in biochemical recurrent prostate cancer

OBJECTIVE

The aim of the study was to evaluate the 18F-PSMA-1007 PET/computed tomography (CT) semiautomatic volumetric parameters to assess the whole-body tumor burden and its correlation with prostate-specific antigen (PSA) and Gleason score in patients with biochemically recurrent prostate cancer (PCa).

MATERIALS AND METHODS

A total of 110 patients referred for 18F-PSMA-1007 PET/CT due to biochemical recurrence were retrospectively analyzed. Whole-body total lesion prostate-specific membrane antigen (wbTl-PSMA) and whole-body PSMA-derived tumor volume (wbPSMA-TV) metrics on 18F-PSMA-1007 were obtained semiautomatically in dedicated software. A Spearman test was performed to explore the correlation of volumetric imaging parameters with PSA levels and Gleason score. To analyze the association between volumetric measures and PSA subgroups, we used a Kruskal-Wallis test and a Dunn's test to identify each group causing an observed difference.

RESULTS

A total of 492 metastatic lesions were analyzed, and a significant correlation was found between wbTL-PSMA (R = 0.63, P < 0.0001) and wbPSMA-TV (R = 0.49, P < 0.0001) with serum PSA. A statistically significant difference with wbTL-PSMA was found in patients with a PSA less than or equal 0.5 ng/ml and PSA in the range of 0.51-1.0 ng/ml.

CONCLUSION

18F-PSMA-1007 PSMA volumetric parameters can provide a quantitative imaging biomarker for whole-body tumor burden.

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.

Fluorine-18 fluorodeoxyglucose positron emission tomography-based textural features for prediction of event prone carotid atherosclerotic plaques

BACKGROUND

Texture analysis has been increasingly used in the field of positron emission tomography (PET)/computed tomography (CT) imaging with Fluorine-18 fluorodeoxyglucose (18F-FDG), aiming at assessing tumor heterogeneity. The purpose of the present study is to examine the feasibility of performing texture analysis in carotid arteries, investigate the value of textural features as predictors of potential plaque vulnerability using as reference standards histological and immunohistochemical data and compare their performance with conventional uptake measurements.

METHODS

67 different 18F-FDG PET-based textural features were extracted from carotid images of 21 patients with high-grade carotid stenosis undergoing endarterectomy. To identify the more reliable predictors, univariate logistic regression analysis was performed. The accuracy was satisfactory in case of an Area Under the Receiver Operating Characteristic (ROC) curve (AUC) ≥ 0.80.

RESULTS

First measure of information correlation (AUC = 0.87, P < 0.001), large zone low gray level emphasis (AUC = 0.87, P < 0.001), and normalized run length non-uniformity (AUC = 0.84, P < 0.001) were the most optimal textural features for identifying characteristics of plaque vulnerability based on histological analysis. Addition of textural features to target-to-background ratio (TBR) (AUC = 0.74, P = 0.031) resulted in an AUC = 0.92 (P < 0.001), however, this did not reach statistical significance (Pdiff = 0.09). Intensity histogram standard deviation (AUC = 0.87, P < 0.001) and joint variance (AUC = 0.81, P = 0.001) were the most efficient features for signal differential in relation to immunohistochemical findings and provided incremental value compared to TBR (Pdiff = 0.02).

CONCLUSION

Texture analysis can be applied in 18F-FDG PET carotid imaging providing valuable information for plaque characterization.

The Utility of PET/CT Metabolic Parameters Measured Based on Fixed Percentage Threshold of SUVmax and Adaptive Iterative Algorithm in the New Revised FIGO Staging System for Stage III Cervical Cancer

Objectives: The main aim of this study was to evaluate the differences in metabolic parameters of positron emission tomography with 2-deoxy-2-[fluorine-18] fluoro-D-glucose integrated with computed tomography (¹⁸F-FDG PET/CT) measured based on fixed percentage threshold of maximum standard uptake value (SUVmax) and adaptive iterative algorithm (AT-AIA) in patients with cervical cancer. Metabolic parameters in stage III patients subdivided into five groups according to FIGO and T staging (IIIB-T3B, IIIC1-T2B, IIIC1-T3B, IIIC2-T2B, IIIC2-T3B) were compared.

Methods: In total, 142 patients with squamous cell cervical cancer subjected to ¹⁸F-FDG-PET/CT before treatment were retrospectively reviewed. SUVmax, mean standard uptake value (SUVmean), maximum glucose homogenization (GNmax), mean glucose homogenization (GNmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and glucose homogenization total lesion glycolysis (GNTLG) values measured based on the above two measurement methods of all 142 patients (IIB-IVB) and 102 patients in the above five groups were compared.

Results: MTV measured based on fixed percentage threshold of SUVmax was lower than that based on AT-AIA (p < 0.05). MTV_40%, MTV_0.5, TLG_0.5, GNTLG_40%, and GNTLG_0.5 values were significantly different among the five groups (p < 0.05) while the rest parameters were comparable (p > 0.05). All metabolic parameters of group IIIB-T3B were comparable to those of the other four groups. MTV_40%, MTV_0.5, GNTLG_40%, and GNTLG_0.5 in group IIIC1-T2B relative to IIIC1-T3B and those of group IIIC2-T2B relative to group IIIC2-T3B were significantly different. All metabolic parameters of group IIIC1-T2B relative to IIIC2-T2B and those of group IIIC1-T3B relative to group IIIC2-T3B were not significantly different.

Conclusion: Metabolic parameters obtained with the two measurement methods showed a number of differences. Selection of appropriate methods for measurement of ¹⁸F-FDG-PET/CT metabolic parameters is important to facilitate advances in laboratory research and clinical applications. When stage III patients had the same T stage, their metabolic parameters of local tumor were not significantly different, regardless of the presence or absence of lymph node metastasis, location of metastatic lymph nodes in the pelvic cavity or para-abdominal aorta. These results support the utility of the revised FIGO system for stage III cervical cancer, although our T-staging of stage III disease is incomplete.

Differentiation between non-small cell lung cancer and radiation pneumonitis after carbon-ion radiotherapy by 18F-FDG PET/CT texture analysis

The differentiation of non-small cell lung cancer (NSCLC) and radiation pneumonitis (RP) is critically essential for selecting optimal clinical therapeutic strategies to manage post carbon-ion radiotherapy (CIRT) in patients with NSCLC. The aim of this study was to assess the ability of ¹⁸F-FDG PET/CT metabolic parameters and its textural image features to differentiate NSCLC from RP after CIRT to develop a differential diagnosis of malignancy and benign lesion. We retrospectively analyzed ¹⁸F-FDG PET/CT image data from 32 patients with histopathologically proven NSCLC who were scheduled to undergo CIRT and 31 patients diagnosed with RP after CIRT. The SUV parameters, metabolic tumor volume (MTV), total lesion glycolysis (TLG) as well as fifty-six texture parameters derived from seven matrices were determined using PETSTAT image-analysis software. Data were statistically compared between NSCLC and RP using Wilcoxon rank-sum tests. Diagnostic accuracy was assessed using receiver operating characteristics (ROC) curves. Several texture parameters significantly differed between NSCLC and RP (p < 0.05). The parameters that were high in areas under the ROC curves (AUC) were as follows: SUV_max, 0.64; GLRLM run percentage, 0.83 and NGTDM coarseness, 0.82. Diagnostic accuracy was improved using GLRLM run percentage or NGTDM coarseness compared with SUV_max (p < 0.01). The texture parameters of ¹⁸F-FDG uptake yielded excellent outcomes for differentiating NSCLC from radiation pneumonitis after CIRT, which outperformed SUV-based evaluation. In particular, GLRLM run percentage and NGTDM coarseness of ¹⁸F-FDG PET/CT images would be appropriate parameters that can offer high diagnostic accuracy.

PSMA whole-body tumor burden in primary staging and biochemical recurrence of prostate cancer

PURPOSE

The objective of this study was to evaluate whether ⁶⁸Ga-PSMA PET/CT whole-body tumor burden (PSMAwbtb) is associated with clinical parameters and laboratory parameters in prostate cancer patients.

METHODS

We retrospectively evaluated prostate cancer patients submitted to PSMA PET/CT for primary staging purposes or due to biochemical recurrence (BR). PSMAwbtb metrics (total volume of PSMA-avid tumor (PSMA-TV)) and total uptake of PSMA-avid lesions (PSMA-TL) were calculated semi-automatically. Spearman's rank correlations between PSMAwbtb metrics and clinical, laboratory parameters (age, time-to-BR, years of diagnosis of prostate cancer, free and total serum PSA levels, and the Gleason score) and with the highest SUVmax of a lesion (hSUVmax) were analyzed.

RESULTS

Among the 257 PSMA PET/CT studies, there were 46 scans (17.9%) performed for primary staging and 211 (82.1%) for BR. PSMA-TV and PSMA-TL were calculated for the 157 positive scans (58.8%), which were 43 patients (93.5%) in the primary staging group and 114 patients (54.0%) in the BR group. In the primary staging group, we observed a significant correlation between PSMA-TL and hSUVmax (p = 0.0021). In the BR group, there was a significant direct correlation between PSMA-TL and the variables age (p = 0.0031), total serum PSA values (p = < 0.0001), free serum PSA values (p = < 0.0001), and the hSUVmax (p = < 0.0001). Similar results were obtained for PSMA-TV.

CONCLUSION

PSMAwbtb has a direct and positive correlation with serum PSA values and age in prostate cancer patients with BR.

Optimal method for metabolic tumour volume assessment of cervical cancers with inter-observer agreement on [18F]-fluoro-deoxy-glucose positron emission tomography with computed tomography

PURPOSE

Cervical cancer metabolic tumour volume (MTV) derived from [18F]-FDG PET/CT has a role in prognostication and therapy planning. There is no standard method of outlining MTV on [18F]-FDG PET/CT. The aim of this study was to assess the optimal method to outline primary cervical tumours on [18F]-FDG PET/CT using MRI-derived tumour volumes as the reference standard.

METHODS

81 consecutive cervical cancer patients with pre-treatment staging MRI and [18F]-FDG PET/CT imaging were included. MRI volumes were compared with different PET segmentation methods. Method 1 measured MTVs at different SUV_max thresholds ranging from 20 to 60% (MTV₂₀-MTV₆₀) with bladder masking and manual adjustment when required. Method 2 created an isocontour around the tumour prior to different SUV_max thresholds being applied. Method 3 used an automated gradient method. Inter-observer agreement of MTV, following manual adjustment when required, was recorded.

RESULTS

For method 1, the MTV₂₅ and MTV₃₀ were closest to the MRI volumes for both readers (mean percentage change from MRI volume of 2.9% and 13.4% for MTV₂₅ and - 13.1% and - 2.0% for MTV₃₀ for readers 1 and 2). 70% of lesions required manual adjustment at MTV₂₅ compared with 45% at MTV₃₀. There was excellent inter-observer agreement between MTV₃₀ to MTV₆₀ (ICC ranged from 0.898-0.976 with narrow 95% confidence intervals (CIs)) and moderate agreement at lower thresholds (ICC estimates of 0.534 and 0.617, respectively for the MTV₂₀ and MTV₂₅ with wide 95% CIs). Bladder masking was performed in 86% of cases overall. For method 2, excellent correlation was demonstrated at MTV₂₅ and MTV₃₀ (mean % change from MRI volume of -3.9% and - 8.6% for MTV₂₅ and - 16.9% and 19% for MTV₃₀ for readers 1 and 2, respectively). This method also demonstrated excellent ICC across all thresholds with no manual adjustment. Method 3 demonstrated excellent ICC of 0.96 (95% CI 0.94-0.97) but had a mean percentage difference from the MRI volume of - 19.1 and - 18.2% for readers 1 and 2, respectively. 21% required manual adjustment for both readers.

CONCLUSION

MTV₃₀ provides the optimal correlation with MRI volume taking into consideration the excellent inter-reader agreement and less requirement for manual adjustment.

Enhanced prognostic stratification of neoadjuvant treated lung squamous cell carcinoma by computationally-guided tumor regression scoring

INTRODUCTION

The amount of residual tumor burden after neoadjuvant chemotherapy is an important prognosticator, but for non-small cell lung carcinoma (NSCLC), no official regression scoring system is yet established. Computationally derived histological regression scores could provide unbiased and quantitative readouts to complement the clinical assessment of treatment response.

METHODS

Histopathologic tumor regression was microscopically assessed on whole cases in a neoadjuvant chemotherapy-treated cohort (NAC, n = 55 patients) of lung squamous cell carcinomas (LSCC). For each patient, the slide showing the least pathologic regression was selected for subsequent computational analysis and histological features were quantified: percentage of vital tumor cells (cTu.Percentage), total surface covered by vital tumor cells (cTu.Area), area of the largest vital tumor fragment (cTu.Size.max), and total number of vital tumor fragments (cTu.Fragments). A chemo-naïve LSCC cohort (CN, n = 104) was used for reference. For 23 of the 55 patients [¹⁸F]-Fluorodeoxyglucose (FDG) PET/CT measurements of maximum standard uptake value (SUV_max), background subtracted lesion activity (BSL) and background subtracted volume (BSV) were correlated with pathologic regression. Survival analysis was carried out using Cox regression and receiver operating characteristic (ROC) curve analysis using a 3-years cutoff.

RESULTS

All computational regression parameters significantly correlated with relative changes of BSV FDG PET/CT values after neoadjuvant chemotherapy. ROC curve analysis of histological parameters of NAC patients showed that cTu.Percentage was the most accurate prognosticator of overall survival (ROC curve AUC = 0.77, p-value = 0.001, Cox regression HR = 3.6, p = 0.001, variable cutoff < = 30 %).

CONCLUSIONS

This study demonstrates the prognostic relevance of computer-derived histopathologic scores. Additionally, the analysis carried out on slides displaying the least pathologic regression correlated with overall pathologic response and PET/CT values. This might improve the objective histopathologic assessment of tumor response in neoadjuvant setting.

18F-FDG PET/CT in Restaging and Evaluation of Response to Therapy in Lung Cancer: State of the Art

BACKGROUND

Metabolic information provided by 18F-FDG PET/CT are useful for initial staging, therapy planning, response evaluation, and to a lesser extent for the follow-up of non-small cell lung cancer (NSCLC). To date, there are no established clinical guidelines in treatment response and early detection of recurrence.

OBJECTIVE

To provide an overview of 18F-FDG PET/CT in NSCLC and in particular, to discuss its utility in treatment response evaluation and restaging of lung cancer.

METHODS

A comprehensive search was used based on PubMed results. From all studies published in English those that explored the role of 18F-FDG PET/CT in the treatment response scenario were selected.

RESULTS

Several studies have demonstrated that modifications in metabolic activity, expressed by changes in SUV both in the primary tumor as well as in regional lymph nodes, are associated with tumor response and survival. Beside SUV, other metabolic parameters (i.e. MTV, TLG, and percentage changes) are emerging to be helpful for predicting clinical outcomes.

CONCLUSION

18F-FDG parameters appear to be promising factors for evaluating treatment response and for detecting recurrences, although larger prospective trials are needed to confirm these evidences and to determine optimal cut-off values.

Semi-automatic segmentation from intrinsically-registered 18F-FDG-PET/MRI for treatment response assessment in a breast cancer cohort: comparison to manual DCE-MRI

Objectives

To investigate the reliability of simultaneous positron emission tomography and magnetic resonance imaging (PET/MRI)-derived biomarkers using semi-automated Gaussian mixture model (GMM) segmentation on PET images, against conventional manual tumor segmentation on dynamic contrast-enhanced (DCE) images.

Materials and methods

Twenty-four breast cancer patients underwent PET/MRI (following 18F-fluorodeoxyglucose (18F-FDG) injection) at baseline and during neoadjuvant treatment, yielding 53 data sets (24 untreated, 29 treated). Two-dimensional tumor segmentation was performed manually on DCE–MRI images (manual DCE) and using GMM with corresponding PET images (GMM–PET). Tumor area and mean apparent diffusion coefficient (ADC) derived from both segmentation methods were compared, and spatial overlap between the segmentations was assessed with Dice similarity coefficient and center-of-gravity displacement.

Results

No significant differences were observed between mean ADC and tumor area derived from manual DCE segmentation and GMM–PET. There were strong positive correlations for tumor area and ADC derived from manual DCE and GMM–PET for untreated and treated lesions. The mean Dice score for GMM–PET was 0.770 and 0.649 for untreated and treated lesions, respectively.

Discussion

Using PET/MRI, tumor area and mean ADC value estimated with a GMM–PET can replicate manual DCE tumor definition from MRI for monitoring neoadjuvant treatment response in breast cancer.

Verification of image quality and quantification in whole-body positron emission tomography with continuous bed motion

OBJECTIVE

Whole-body dynamic imaging using positron emission tomography (PET) facilitates the quantification of tracer kinetics. It is potentially valuable for the differential diagnosis of tumors and for the evaluation of therapeutic efficacy. In whole-body dynamic PET with continuous bed motion (CBM) (WBDCBM-PET), the pass number and bed velocity are key considerations. In the present study, we aimed to investigate the effect of a combination of pass number and bed velocity on the quantitative accuracy and quality of WBDCBM-PET images.

METHODS

In this study, WBDCBM-PET imaging was performed at a body phantom using seven bed velocity settings in combination with pass numbers. The resulting image quality was evaluated. For comparing different acquisition settings, the dynamic index (DI) was obtained using the following formula: [P/S], where P represents the pass number, and S represents the bed velocity (mm/s). The following physical parameters were evaluated: noise equivalent count at phantom (NEC_phantom), percent background variability (N_10 mm), percent contrast of the 10 mm hot sphere (Q_{H, 10 mm}), the Q_{H, 10 mm}/N_10 mm ratio, and the maximum standardized uptake value (SUV_max). Furthermore, visual evaluation was performed.

RESULTS

The NEC_phantom was equivalent for the same DI settings regardless of the bed velocity. The N_10 mm exhibited an inverse correlation (r < - 0.89) with the DI. Q_H,10 mm was not affected by DI, and a correlation between Q_H,10 mm/N_10 mm ratio and DI was found at all the velocities (r > 0.93). The SUV_max of the spheres was not influenced by the DI. The coefficient of variations caused by bed velocity decreased in larger spheres. There was no significant difference between the bed velocities on visual evaluation.

CONCLUSION

The quantitative accuracy and image quality achieved with WBDCBM-PET was comparable to that achieved with non-dynamic CBM, regardless of the pass number and bed velocity used during imaging for a given acquisition time.

Prognostic Value of 18F-Fluorodeoxyglucose PET/Computed Tomography in Non-Small-Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death with a poor prognosis. Numerous factors contribute to treatment outcome. 18F-fluorodeoxyglucose (FDG) uptake reflects tumor metabolic activity and is an important prognosticator in patients with NSCLC. Volume-based FDG-PET parameters reflect the metabolic status of a malignancy more accurately than maximum standardized uptake value and thus are better prognostic markers in lung cancer. FDG-avid tumor burden parameters may help clinicians to predict treatment outcomes before and during therapy so that treatment can be adjusted to achieve the best possible outcomes while avoiding side effects.

Current Methods to Define Metabolic Tumor Volume in Positron Emission Tomography: Which One is Better?

Numerous methods to segment tumors using ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) have been introduced. Metabolic tumor volume (MTV) refers to the metabolically active volume of the tumor segmented using FDG PET, and has been shown to be useful in predicting patient outcome and in assessing treatment response. Also, tumor segmentation using FDG PET has useful applications in radiotherapy treatment planning. Despite extensive research on MTV showing promising results, MTV is not used in standard clinical practice yet, mainly because there is no consensus on the optimal method to segment tumors in FDG PET images. In this review, we discuss currently available methods to measure MTV using FDG PET, and assess the advantages and disadvantages of the methods.

Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer

Aim

To study the influence of dual time point 18F-FDG PET/CT in textural features and SUV-based variables and their relation among them.

Methods

Fifty-six patients with locally advanced breast cancer (LABC) were prospectively included. All of them underwent a standard 18F-FDG PET/CT (PET-1) and a delayed acquisition (PET-2). After segmentation, SUV variables (SUVmax, SUVmean, and SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained. Eighteen three-dimensional (3D) textural measures were computed including: run-length matrices (RLM) features, co-occurrence matrices (CM) features, and energies. Differences between all PET-derived variables obtained in PET-1 and PET-2 were studied.

Results

Significant differences were found between the SUV-based parameters and MTV obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1. In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run emphasis, gray-level non-uniformity, homogeneity, and dissimilarity. Textural variables showed relations with MTV and TLG.

Conclusion

Significant differences of textural features were found in dual time point 18F-FDG PET/CT. Thus, a dynamic behavior of metabolic characteristics should be expected, with higher heterogeneity in delayed PET acquisition compared with the standard PET. A greater heterogeneity was found in bigger tumors.

Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results

OBJECTIVES

To investigate the usefulness of voxel-based analysis of standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs) for evaluating soft-tissue tumour malignancy with a PET/MR system.

METHODS

Thirty-five subjects with either ten low/intermediate-grade tumours or 25 high-grade tumours were prospectively enrolled. Zoomed diffusion-weighted and fluorodeoxyglucose (¹⁸FDG)-PET images were acquired along with fat-suppressed T2-weighted images (FST2WIs). Regions of interest (ROIs) were drawn on FST2WIs including the tumour in all slices. ROIs were pasted onto PET and ADC-maps to measure SUVs and ADCs within tumour ROIs. Tumour volume, SUVmax, ADCminimum, the heterogeneity and the correlation coefficients of SUV and ADC were recorded. The parameters of high- and low/intermediate-grade groups were compared, and receiver operating characteristic (ROC) analysis was also performed.

RESULTS

The mean correlation coefficient for SUV and ADC in high-grade sarcomas was lower than that of low/intermediate-grade tumours (-0.41 ± 0.25 vs. -0.08 ± 0.34, P < 0.01). Other parameters did not differ significantly. ROC analysis demonstrated that correlation coefficient showed the best diagnostic performance for differentiating the two groups (AUC 0.79, sensitivity 96.0%, specificity 60%, accuracy 85.7%).

CONCLUSIONS

SUV and ADC determined via PET/MR may be useful for differentiating between high-grade and low/intermediate-grade soft tissue tumours.

KEY POINTS

• PET/MR allows voxel-based comparison of SUVs and ADCs in soft-tissue tumours. • A comprehensive assessment of internal heterogeneity was performed with scatter plots. • SUVmax or ADCminimum could not differentiate high-grade sarcoma from low/intermediate-grade tumours. • Only the correlation coefficient between SUV and ADC differentiated the two groups. • The correlation coefficient showed the best diagnostic performance by ROC analysis.

Three-dimensional substructure measurements for the differential diagnosis of ground glass nodules

BACKGROUND

We analyzed the differences between maximum and peak computed tomography (CT) numbers (M-P), respectively representing the densities of the solid center and the main periphery of ground-glass nodules (GGNs), and the average change in M-P velocity (V(M-P)) during follow-up to differentiate between pre-invasive (PIA) and invasive adenocarcinoma (IAC).

METHODS

Data of 102 patients were retrospectively collected and analyzed in our study including 43 PIAs and 59 IACs. Diameters, total volumes, and the maximum and peak CT numbers in CT number histograms were measured and followed for at least 3 months. This study was registered retrospectively.

RESULTS

The M-P values for IACs were higher than those for PIAs (p = 0.001), with an area under the curve (AUC) of 0.810 and a threshold of 489.5 Hounsfield units (HU) in ROC analysis. The V(M-P) values for IACs were smaller than those for PIAs (p = 0.04), with an AUC of 0.805 and a threshold of 11.01 HU/day.

CONCLUSIONS

M-P and V(M-P) values may help distinguish IACs from PIAs by representing the changes in the sub-structural densities of GGNs during follow-up.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

In-depth analysis of interreader agreement and accuracy in categorical assessment of brown adipose tissue in (18)FDG-PET/CT

PURPOSE

To evaluate the interreader agreement of a three-tier craniocaudal grading system for brown fat activation and investigate the accuracy of the distinction between the three grades.

MATERIALS AND METHODS

After IRB approval, 340 cases were retrospectively selected from patients undergoing (18)FDG-PET/CT between 2007 and 2015 at our institution, with 85 cases in each grade and 85 controls with no active brown fat. Three readers evaluated all cases independently. Furthermore standardized uptake values (SUV) measurements were performed by two readers in a subset of 53 cases. Agreement between the readers was assessed with Cohen's Kappa (k), the concordance correlation coefficient (CCC) and the intraclass correlation coefficient (ICC). Accuracy was assessed with Bland-Altman and receiver operating characteristics (ROC) analysis. A Bonferroni-corrected two-tailed p<0.016 was considered statistically significant.

RESULTS

Agreement for BAT grade was excellent by all three metrics with k=0.83-0.89, CCC=0.83-0.89 and ICC=0.91-0.94. Bland-Altman analysis revealed only slight average over- or underestimation (-0.01-0.14) with the majority of disagreements within one grade. ROC analysis yielded slightly less accurate classification between higher vs. lower grades (Area under the ROC curves 0.78-0.84 vs. 0.88-0.92) but no significant differences between readers. Agreement was also excellent for the maximum SUV and the total brown fat volume (k=0.90 and 0.94, CCC=0.93 and 0.99, ICC=0.96 and 0.99), but Bland-Altman plots revealed a tendency to underestimate activity by one of the readers.

CONCLUSION

Grading the activation of brown fat by assessment of the most caudally activated depots results in excellent interreader agreement, comparable to SUV measurements.

18F-FDG PET/CT of Non-Small Cell Lung Carcinoma Under Neoadjuvant Chemotherapy: Background-Based Adaptive-Volume Metrics Outperform TLG and MTV in Predicting Histopathologic Response

Assessment of tumor response after chemotherapy using (18)F-FDG PET metrics is gaining acceptance. Several studies have suggested that the parameters metabolically active tumor volume (MTV) and total lesion glycolysis (TLG) are superior to SUVmax for measuring tumor burden. However, the measurement of MTV and TLG is still controversial; the most common method uses an absolute threshold of 42% of SUVmax Recently, we implemented a background-adaptive method to determine the background-subtracted lesion activity (BSL) and the background-subtracted volume (BSV). In this study, we investigated the correlation between such PET metrics and histopathologic response in non-small cell lung carcinoma (NSCLC).

METHODS

Forty-four NSCLC patients were retrospectively identified. Their PET/CT data on both types of scan before and after neoadjuvant chemotherapy were analyzed regarding SUVmax, MTV, TLG, BSL, and BSV, as well as the relative changes in these parameters. The tumor regression score as an indicator of histopathologic response was scored on hematoxylin- and eosin-stained sections of the surgical specimens using a 4-tiered scale (scores 1-4). The correlation between score and the absolute and relative PET metrics after chemotherapy was analyzed using Spearman rank correlation tests.

RESULTS

Tumors that demonstrated a good response after neoadjuvant chemotherapy had significantly lower (18)F-FDG activity than nonresponding tumors (scores 3 and 4: SUVmax, 4.2 [range, 1.8-7.9] vs. scores 1 and 2: SUVmax, 8.1 [range, 1.4-40.4]; P = 0.001). The same was found for change in SUVmax and score (P = 0.001). PET volume metrics based on a 42% fixed threshold for SUVmax did not correlate with score (TLG, P = 0.505; MTV, P = 0.386). However, both of the background activity-based PET volume metrics-BSL and BSV-significantly correlated with score (P < 0.001 each).

CONCLUSION

PET volume metrics based on background-adaptive methods correlate better with histopathologic tumor regression score in NSCLC patients under neoadjuvant chemotherapy than algorithms and methods using a fixed threshold (42% SUVmax).

A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

Pulmonary ground-glass nodules diagnosis: mean change rate of peak CT number as a discriminative factor of pathology during a follow-up

OBJECTIVE

We aimed to analyse the peak CT number (PEAK) in CT number histogram of ground-glass nodules (GGN), meaning the most frequent density of pixels in the image of pulmonary nodule, based on three-dimensional (3D) reconstructive model pre-operatively, and the mean rate of PEAK change (V-PEAK) during a follow-up of GGN for differential diagnosis between pre-invasive adenocarcinoma (PIA) and invasive adenocarcinoma (IAC).

METHODS

CT number histogram of pixels in GGN was made automatically by 3D measurement software. Diameter, total volume, PEAK and V-PEAK were measured from CT data sets of different groups classified by pathology, subtype and number of GGN, respectively.

RESULTS

Among all 102 cases, 47 were PIA, including atypical adenomatous hyperplasia (n = 29) and adenocarcinoma in situ (n = 18), and 55 were IAC, including minimally IAC (MIA, n = 4). By Wilcoxon test, PEAK of IAC was significantly higher than that of PIA (p < 0.001). By receiver operating curve analysis, area under the curve (AUC) was 0.857 and threshold -820.50 Hounsfield units (HU) for differentiation between PIA and IAC. V-PEAK of IAC was unexpectedly remarkably smaller than that of PIA (p < 0.001) with AUC and threshold being 0.810 and -0.829 HU day(-1), respectively.

CONCLUSION

Pre-operative PEAK and V-PEAK, which interpret and evaluate the change of volume and density of pulmonary nodule simultaneously from both exterior and interior perspectives, can help to distinguish IAC from PIA.

ADVANCES IN KNOWLEDGE

This study provided researchers of GGN another perspective, taking both volume and density of nodules into consideration for pathological evaluation.

Assessing and accounting for the impact of respiratory motion on FDG uptake and viable volume for liver lesions in free-breathing PET using respiration-suspended PET images as reference

PURPOSE

To assess and account for the impact of respiratory motion on the variability of activity and volume determination of liver tumor in positron emission tomography (PET) through a comparison between free-breathing (FB) and respiration-suspended (RS) PET images.

METHODS

As part of a PET/computed tomography (CT) guided percutaneous liver ablation procedure performed on a PET/CT scanner, a patient's breathing is suspended on a ventilator, allowing the acquisition of a near-motionless PET and CT reference images of the liver. In this study, baseline RS and FB PET/CT images of 20 patients undergoing thermal ablation were acquired. The RS PET provides near-motionless reference in a human study, and thereby allows a quantitative evaluation of the effect of respiratory motion on PET images obtained under FB conditions. Two methods were applied to calculate tumor activity and volume: (1) threshold-based segmentation (TBS), estimating the total lesion glycolysis (TLG) and the segmented volume and (2) histogram-based estimation (HBE), yielding the background-subtracted lesion (BSL) activity and associated volume. The TBS method employs 50% of the maximum standardized uptake value (SUVmax) as the threshold for tumors with SUVmax≥2× SUVliver-bkg, and tumor activity above this threshold yields TLG50%. The HBE method determines local PET background based on a Gaussian fit of the low SUV peak in a SUV-volume histogram, which is generated within a user-defined and optimized volume of interest containing both local background and lesion uptakes. Voxels with PET intensity above the fitted background were considered to have originated from the tumor and used to calculate the BSL activity and its associated lesion volume.

RESULTS

Respiratory motion caused SUVmax to decrease from RS to FB by -15%±11% (p=0.01). Using TBS method, there was also a decrease in SUVmean (-18%±9%, p=0.01), but an increase in TLG50% (18%±36%) and in the segmented volume (47%±52%, p=0.01) from RS to FB PET images. The background uptake in normal liver was stable, 1%±9%. In contrast, using the HBE method, the differences in both BSL activity and BSL volume from RS to FB were -8%±10% (p=0.005) and 0%±16% (p=0.94), respectively.

CONCLUSIONS

This is the first time that almost motion-free PET images of the human liver were acquired and compared to free-breathing PET. The BSL method's results are more consistent, for the calculation of both tumor activity and volume in RS and FB PET images, than those using conventional TBS. This suggests that the BSL method might be less sensitive to motion blurring and provides an improved estimation of tumor activity and volume in the presence of respiratory motion.

Volume-based quantitative FDG PET/CT metrics and their association with optimal debulking and progression-free survival in patients with recurrent ovarian cancer undergoing secondary cytoreductive surgery

OBJECTIVE

Our aim was to evaluate the associations between quantitative (18)F-fluorodeoxyglucose positron-emission tomography (FDG-PET) uptake metrics, optimal debulking (OD) and progression-free survival (PFS) in patients with recurrent ovarian cancer undergoing secondary cytoreductive surgery.

METHODS

Fifty-five patients with recurrent ovarian cancer underwent FDG-PET/CT within 90 days prior to surgery. Standardized uptake values (SUVmax), metabolically active tumour volumes (MTV), and total lesion glycolysis (TLG) were measured on PET. Exact logistic regression, Kaplan-Meier curves and the log-rank test were used to assess associations between imaging metrics, OD and PFS.

RESULTS

MTV (p = 0.0025) and TLG (p = 0.0043) were associated with OD; however, there was no significant association between SUVmax and debulking status (p = 0.83). Patients with an MTV above 7.52 mL and/or a TLG above 35.94 g had significantly shorter PFS (p = 0.0191 for MTV and p = 0.0069 for TLG). SUVmax was not significantly related to PFS (p = 0.10). PFS estimates at 3.5 years after surgery were 0.42 for patients with an MTV ≤ 7.52 mL and 0.19 for patients with an MTV > 7.52 mL; 0.46 for patients with a TLG ≤ 35.94 g and 0.15 for patients with a TLG > 35.94 g.

CONCLUSION

FDG-PET metrics that reflect metabolic tumour burden are associated with optimal secondary cytoreductive surgery and progression-free survival in patients with recurrent ovarian cancer.

KEY POINTS

• Both TLG and MTV were associated with optimal tumour debulking. • There was no significant association between SUVmax and tumour debulking status. • Patients with higher MTV and/or TLG had significantly shorter PFS. • SUVmax was not significantly related to PFS.