Predictive and prognostic value of metabolic tumour volume and total lesion glycolysis in solid tumours

Prognostic Value of PSMA PET/CT in Prostate Cancer

Prostate-specific membrane antigen (PSMA) is a transmembrane glycoprotein expressed in the majority of prostate cancer (PCa). PSMA has an enzymatic function that makes metabolic substrates such as folate available for utilization by PCa cells. Intracellular folate availability drives aggressive tumor phenotype. PSMA expression is, therefore, a marker of aggressive tumor biology. The large extracellular domain of PSMA is available for targeting by diagnostic and therapeutic radionuclides, making it a suitable cellular epitope for theranostics. PET imaging of radiolabeled PSMA ligands has several prognostic utilities. In the prebiopsy setting, intense PSMA avidity in a prostate lesion correlate well with clinically significant PCa (csPCa) on histology. When used for staging, PSMA PET imaging outperforms conventional imaging for the accurate staging of primary PCa, and findings on imaging predict post-treatment outcomes. The biggest contribution of PSMA PET imaging to PCa management is in the biochemical recurrence setting, where it has emerged as the most sensitive imaging modality for the localization of PCa recurrence by helping to guide salvage therapy. PSMA PET obtained for localizing the site of recurrence is prognostic, such that a higher lesion number predicts a less favorable outcome to salvage radiotherapy or surgical intervention. Systemic therapy is given to patients with advanced PCa with distant metastasis. PSMA PET is useful for predicting response to treatments with chemotherapy, first- and second-line androgen deprivation therapies, and PSMA-targeted radioligand therapy. Artificial intelligence using machine learning algorithms allows for the mining of information from clinical images not visible to the human eyes. Artificial intelligence applied to PSMA PET images, therefore, holds great promise for prognostication in PCa management.

Principal Component Analysis Applied to Radiomics Data: Added Value for Separating Benign from Malignant Solitary Pulmonary Nodules

Here, we report on the added value of principal component analysis applied to a dataset of texture features derived from 39 solitary pulmonary lung nodule (SPN) lesions for the purpose of differentiating benign from malignant lesions, as compared to the use of SUVmax alone. Texture features were derived using the LIFEx software. The eight best-performing first-, second-, and higher-order features for separating benign from malignant nodules, in addition to SUVmax (MaximumGreyLevelSUVbwIBSI184IY), were included for PCA. Two principal components (PCs) were retained, of which the contributions to the total variance were, respectively, 87.6% and 10.8%. When included in a logistic binomial regression analysis, including age and gender as covariates, both PCs proved to be significant predictors for the underlying benign or malignant character of the lesions under study (p = 0.009 for the first PC and 0.020 for the second PC). As opposed to SUVmax alone, which allowed for the accurate classification of 69% of the lesions, the regression model including both PCs allowed for the accurate classification of 77% of the lesions. PCs derived from PCA applied on selected texture features may allow for more accurate characterization of SPN when compared to SUVmax alone.

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 value of [18F]-FDG PET/CT in patients with meta-static breast cancer treated with cyclin-dependent inhibitors

Objective

The addition of cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) to endocrine therapy impressively improved the outcome of patients with hormone receptor-positive metastatic breast cancer. Despite their great efficacy, not all patients respond to treatment and many of them develop acquired resistance. The aim of this retrospective study was to assess the role of [18F]-FDG PET/CT in predicting PFS and OS in breast cancer patients treated with CDK4/6i.

Methods

114 patients who performed an [18F]-FDG PET/CT scan before (PET1) and 2-6 months (PET2) after starting treatment were retrospectively enrolled. Metabolic response was evaluated by EORTC, PERCIST and Deauville Score and correlated to PFS and OS.

Results

In patients who did not progress at PET2 (n = 90), PFS rates were not significantly different between classes of response by EORTC and PERCIST. Conversely, patients showing a Deauville score ≤3 had a longer PFS (median PFS 42 vs 21.0 months; p = 0.008). A higher total metabolic tumor volume at PET1 (TMTV1) was also associated with a shorter PFS (median 18 vs 42 months; p = 0.0026). TMTV1 and Deauville score were the only independent prognostic factors for PFS at multivariate analysis and their combination stratified the population in four definite classes of relapse risk. Conversely, the above parameters did not affect OS which was only influenced by a progressive metabolic disease at PET2 (3-years survival rate 29.8 vs 84.9%; p<0.0001).

Conclusion

TMTV and metabolic response by Deauville score were significant prognostic factors for PFS in patients with breast cancer treated with CDK4/6i. Their determination could help physicians to select patients who may need a closer follow up.

Differences in Tumour Aggressiveness Based on Molecular Subtype and Race Measured by [18F]FDG PET Metabolic Metrics in Patients with Invasive Carcinoma of the Breast

Breast cancer in women of African descent tends to be more aggressive with poorer prognosis. This is irrespective of the molecular subtype. [¹⁸F]FDG PET/CT metrics correlate with breast cancer aggressiveness based on molecular subtype. This study investigated the differences in [¹⁸F]FDG PET/CT metrics of locally advanced invasive ductal carcinoma (IDC) among different racial groups and molecular subtypes. Qualitative and semiquantitative readings of [¹⁸F]FDG PET/CT acquired in women with locally advanced IDC were performed. Biodata including self-identified racial grouping and histopathological data of the primary breast cancer were retrieved. Statistical analysis for differences in SUVmax, MTV and TLG of the primary tumour and the presence of regional and distant metastases was conducted based on molecular subtype and race. The primary tumour SUVmax, MTV, TLG and the prevalence of distant metastases were significantly higher in Black patients compared with other races (p < 0.05). The primary tumour SUVmax and presence of distant metastases in the luminal subtype and the primary tumour SUVmax and TLG in the basal subtype were significantly higher in Black patients compared with other races (p < 0.05). The significantly higher PET parameters in Black patients with IDC in general and in those with luminal and basal carcinoma subtypes suggest a more aggressive disease phenotype in this race.

Prognostic value of baseline 18F-FDG PET/CT in patients with esophageal squamous cell carcinoma treated with definitive (chemo)radiotherapy

PURPOSE

To investigate the prognostic value of baseline ¹⁸F-FDG PET/CT in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive (chemo)radiotherapy.

METHODS

A total of 98 ESCC patients with cTNM stage T1-4, N1-3, M0 who received definitive (chemo)radiotherapy after ¹⁸F-FDG PET/CT examination from December 2013 to December 2020 were retrospectively analyzed. Clinical factors included age, sex, histologic differentiation grade, tumor location, clinical stage, and treatment strategies. Parameters obtained by ¹⁸F-FDG PET/CT included SUV_max of primary tumor (SUV_Tumor), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV_max of lymph node (SUV_LN), PET positive lymph nodes (PLNS) number, the shortest distance between the farthest PET positive lymph node and the primary tumor in three-dimensional space after the standardization of the patient BSA (SD_max(LN-T)). Univariate and multivariate analysis was conducted by Cox proportional hazard model to explore the significant factors affecting overall survival (OS) and progression-free survival (PFS) in ESCC patients.

RESULTS

Univariate analysis showed that tumor location, SUV_Tumor, MTV, TLG, PLNS number, SD_{max (LN-T)} were significant predictors of OS and tumor location, and clinical T stage, SUV_Tumor, MTV, TLG, SD_{max (LN-T)} were significant predictors of PFS (all p < 0.1). Multivariate analysis showed that MTV and SD_{max (LN-T)} were independent prognostic factors for OS (HR = 1.018, 95% CI 1.006-1.031; p = 0.005; HR = 6.988, 95% CI 2.119-23.042; p = 0.001) and PFS (HR = 1.019, 95% CI 1.005-1.034; p = 0.009; HR = 5.819, 95% CI 1.921-17.628; p = 0.002). Combined with independent prognostic factors MTV and SD_{max (LN-T)}, we can further stratify patient risk.

CONCLUSIONS

Before treatment, ¹⁸F-FDG PET/CT has important prognostic value for patients with ESCC treated with definitive (chemo)radiotherapy. The lower the value of MTV and SD_{max (LN-T)}, the better the prognosis of patients.

Deauville score versus ratio Deauville score in the interpretation of interim 18F-FDG PET-CT and in prediction of outcome in children with FDG-avid extra-nodal lymphomas

Background

Pediatric lymphoma is a common hematological neoplasm, representing the third most frequent childhood malignancy. 18F-fluoro-2-deoxyglucose–positron emission tomography has been found to be useful in lymphoma staging, prediction of prognosis and risk stratification of lymphoma patients. Although the interpretation of interim PET (after two cycles of chemotherapy) using the qualitative visual method of 5-point Deauville score has been widely accepted, semiquantitative methods of interpretation were evaluated by many studies and showed a better prediction of prognosis. The purpose of this study was to evaluate the prognostic role of the semiquantitative ratio Deauville score (rDS), defined as the ratio between target lesion and liver maximum standardized uptake values in children with FDG-avid extra-nodal lymphomas, undergoing interim FDG-PET/CT, and to compare it with the 5-point Deauville score (5p-DS).

Methods

This prospective study included 89 children with FDG-avid extra-nodal lymphoma. Interim PET was interpreted using both visual (5p-DS) and the semiquantitative method (rDS). The visual method depends on visual comparison of FDG uptake between lesions and liver as a reference organ for activity and considered lesions with activity higher than liver to be positive, while the semiquantitative method depends on making a ratio between the most active lesion and liver SUVmax. Receiver operating characteristic approach was applied to identify the optimal cut-point of rDS with respect to response to therapy and prognosis, and the prognostic significance of rDS was compared with 5p-DS.

Results

The ROC analysis for rDS as a predictor of progression showed an optimal cut-point of 1.25. Both 5p-DS and rDS were strong outcome predictors. Patients with negative 5p-DS and patients with rDS < 1.25 had a similar 3-year PFS (87%). Patients with a positive 5p-DS had a 3-year PFS of 67.4%, while patients with rDS > 1.25 had a 3-year PFS of 60%.

Conclusions

rDS could be suggested as an accurate prognostic factor in children with lymphoma undergoing interim FDG-PET/CT. However, larger studies with more homogenous sample regarding histopathological subtypes and chemotherapy lines are needed to confirm these data.

Principal component analysis of texture features derived from FDG PET images of melanoma lesions

Background

The clinical utility of radiomics is hampered by a high correlation between the large number of features analysed which may result in the “bouncing beta” phenomenon which could in part explain why in a similar patient population texture features identified and/or cut-off values of prognostic significance differ from one study to another. Principal component analysis (PCA) is a technique for reducing the dimensionality of large datasets containing highly correlated variables, such as texture feature datasets derived from FDG PET images, increasing data interpretability whilst at the same time minimizing information loss by creating new uncorrelated variables that successively maximize variance. Here, we report on PCA of a texture feature dataset derived from 123 malignant melanoma lesions with a significant range in lesion size using the freely available LIFEx software.

Results

Thirty-eight features were derived from all lesions. All features were standardized. The statistical assumptions for carrying out PCA analysis were met. Seven principal components with an eigenvalue > 1 were identified. Based on the “elbow sign” of the Scree plot, only the first five were retained. The contribution to the total variance of these components derived using Varimax rotation was, respectively, 30.6%, 23.6%, 16.1%, 7.4% and 4.1%. The components provided summarized information on the locoregional FDG distribution with an emphasis on high FDG uptake regions, contrast in FDG uptake values (steepness), tumour volume, locoregional FDG distribution with an emphasis on low FDG uptake regions and on the rapidity of changes in SUV intensity between different regions.

Conclusions

PCA allowed to reduce the dataset of 38 features to a set of 5 uncorrelated new variables explaining approximately 82% of the total variance contained within the dataset. These principal components may prove more useful for multiple regression analysis considering the relatively low numbers of patients usually included in clinical trials on FDG PET texture analysis. Studies assessing the superior differential diagnostic, predictive or prognostic value of principal components derived using PCA as opposed to the initial texture features in clinical relevant settings are warranted.

M1 stage subdivisions based on 18F-FDG PET-CT parameters to identify locoregional radiotherapy for metastatic nasopharyngeal carcinoma

Purpose

To establish a risk classification of de novo metastatic nasopharyngeal carcinoma (mNPC) patients based on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET-CT) radiomics parameters to identify suitable candidates for locoregional radiotherapy (LRRT).

Methods

In all, 586 de novo mNPC patients who underwent ¹⁸F-FDG PET-CT prior to palliative chemotherapy (PCT) were involved. A Cox regression model was performed to identify prognostic factors for overall survival (OS). Candidate PET-CT parameters were incorporated into the PET-CT parameter score (PPS). Recursive partitioning analysis (RPA) was applied to construct a risk stratification system.

Results

Multivariate Cox regression analyses revealed that total lesion glycolysis of locoregional lesions (LRL-TLG), the number of bone metastases (BMs), metabolic tumor volume of distant soft tissue metastases (DSTM-MTV), pretreatment Epstein-Barr virus DNA (EBV DNA), and liver involvement were independent prognosticators for OS. The number of BMs, LRL-TLG, and DSTM-MTV were incorporated as the PPS. Eligible patients were divided into three stages by the RPA-risk stratification model: M1a (low risk, PPS_low + no liver involvement), M1b (intermediate risk, PPS_low + liver involvement, PPS_high + low EBV DNA), and M1c (high risk, PPS_high + high EBV DNA). PCT followed by LRRT displayed favorable OS rates compared to PCT alone in M1a patients (p < 0.001). No significant survival difference was observed between PCT plus LRRT and PCT alone in M1b and M1c patients (p > 0.05).

Conclusions

The PPS-based RPA stratification model could identify suitable candidates for LRRT. Patients with stage M1a disease could benefit from LRRT.

Dynamic Characteristics and Predictive Capability of Tumor Voxel Dose-Response Assessed Using 18F-FDG PET/CT Imaging Feedback

Purpose

Tumor voxel dose–response matrix (DRM) can be quantified using feedback from serial FDG-PET/CT imaging acquired during radiotherapy. This study investigated the dynamic characteristics and the predictive capability of DRM.

Methods

FDG-PET/CT images were acquired before and weekly during standard chemoradiotherapy with the treatment dose 2 Gy × 35 from 31 head and neck cancer patients. For each patient, deformable image registration was performed between the pretreatment/baseline PET/CT image and each weekly PET/CT image. Tumor voxel DRM was derived using linear regression on the logarithm of the weekly standard uptake value (SUV) ratios for each tumor voxel, such as SUV measured at a dose level normalized to the baseline SUV₀. The dynamic characteristics were evaluated by comparing the DRM_i estimated using a single feedback image acquired at the ith treatment week (i = 1, 2, 3, or 4) to the DRM estimated using the last feedback image for each patient. The predictive capability of the DRM estimated using 1 or 2 feedback images was evaluated using the receiver operating characteristic test with respect to the treatment outcome of tumor local–regional control or failure.

Results

The mean ± SD of tumor voxel SUV measured at the pretreatment and the 1st, 2nd, 3rd, 4th, and last treatment weeks was 6.76 ± 3.69, 5.72 ± 3.43, 3.85 ± 2.22, 3.27 ± 2.25, 2.5 ± 1.79, and 2.23 ± 1.27, respectively. The deviations between the DRM_i estimated using the single feedback image obtained at the ith week and the last feedback image were 0.86 ± 4.87, −0.06 ± 0.3, −0.09 ± 0.17, and −0.09 ± 0.12 for DRM₁, DRM₂, DRM₃, and DRM₄, respectively. The predictive capability of DRM₃ and DRM₄ was significant (p < 0.001). The area under the curve (AUC) was increased with the increase in treatment dose level. The DRMs constructed using the single feedback image achieved an AUC of 0.86~1. The AUC was slightly improved to 0.94~1 for the DRMs estimated using 2 feedback images.

Conclusion

Tumor voxel metabolic activity measured using FDG-PET/CT fluctuated noticeably during the first 2 treatment weeks and obtained a stabilized reduction rate thereafter. Tumor voxel DRM constructed using a single FDG-PET/CT feedback image after the 2nd treatment week (>20 Gy) has a good predictive capability. The predictive capability improved continuously using a later feedback image and marginally improved when two feedback images were applied.

Volumetric parameters from [18 F]FDG PET/CT predicts survival in patients with high-grade gastroenteropancreatic neuroendocrine neoplasms

A positive fluorine-18 labelled 2-deoxy-2-fluoroglucose ([¹⁸ F]FDG) positron emission tomography/computed tomography (PET/CT) has been associated with more aggressive disease and less differentiated neuroendocrine neoplasms (NEN). Although a high maximum standardized uptake value (SUV_max ) predicts poor outcome in NEN, volumetric parameters from [¹⁸ F]FDG PET have not been evaluated for prognostication in a pure high-grade gastroenteropancreatic (GEP) NEN cohort. In this retrospective observational study, we evaluated the volumetric PET parameters total metabolic tumour volume (tMTV) and total total lesion glycolysis (tTLG) for independent prognostication of overall survival (OS). High-grade GEP NEN patients with [¹⁸ F]FDG PET/CT examination and biopsy within 90 days were included. Total MTV and tTLG were calculated using an adaptive thresholding software. Patients were dichotomised into low and high metabolic groups based on median tMTV and tTLG. OS was compared using Kaplan-Meier estimator and log-rank test. Uni and multivariable Cox regression was used to estimate effect sizes and adjust for tumour differentiation and SUV_max . Sixty-six patients (median age 64 years) were included with 14 NET G3 and 52 NEC cases after histological re-evaluation. Median tMTV was 208 cm³ and median tTLG 1899 g. Median OS in the low versus high tMTV-group was 21.2 versus 5.7 months (HR 2.53, p = 0.0007) and 22.8 versus 5.7 months (HR 2.42, p = 0.0012) in the tTLG-group. Adjusted for tumour differentiation and SUV_max , tMTV and tTLG still predicted for poor OS, and both tMTV and tTLG were stronger prognostic parameters than SUV_max . Both regression models showed a strong association between volumetric parameters and OS for both neuroendocrine tumours (NET) G3 and neuroendocrine carcinomas (NEC). OS for the tTLG low metabolic NEC was much higher than for the tTLG high metabolic NET G3 (18.3 vs. 5.7 months). High-grade GEP NEN patients with high tMTV or tTLG had a worse OS regardless of tumour differentiation (NET G3 or NEC). Volumetric PET parameters were stronger prognostic parameters than SUV_max .

PET-CTBased Quantitative Parameters for Assessment of Treatment Response and Disease Activity in Cancer and Noncancerous Disorders

The various semiquantitative and quantitative PET-CT parameters provide measurement of disease activity and assessment of treatment response in the PET-CT studies. These include standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), and total metabolic tumor volume (TMTV). Thresholding and adaptive thresholding methods are commonly used algorithms for the evaluation of global disease activity. Readily available commercial software frequently in-built with the current generation PET-CT scanners for providing easy, less time consuming, highly reproducible, and more accurate measurement of global disease activity on PET-CT imaging in evaluation of malignant as well as benign disorders.

The Use of 18F-FDG PET/CT Metabolic Parameters in Predicting Overall Survival in Patients Undergoing Restaging for Malignant Melanoma

Malignant melanoma is one of the more aggressive cancers in the skin, with an increasing incidence every year. Melanoma has a better prognosis if diagnosed early and survival tends to decrease once the disease has metastasized. Positron emission tomography (PET) with 2-[¹⁸F]fluoro-2-deoxy-D-glucose (¹⁸F-FDG) has been used extensively over the past two decades in staging and assessing responses to therapy in patients with melanoma. Metabolic PET parameters have been demonstrated to be independent prognostic factors for progression-free survival (PFS) and overall survival (OS) in different malignancies, melanoma included. In our study, we evaluated the metabolic parameters of ¹⁸F-FDG PET/CT (flourodeoxyglucose positron emission tomography/computed tomography) in predicting the overall survival in patients with malignant melanoma who presented for restaging. Metabolic PET parameters (maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG)) of the primary tumor, as well as whole-body MTV and TLG of the metastatic disease, were measured. Survival curves for OS were constructed and mortality rates were determined using the different PET variables. Forty-nine patients who presented for a PET/CT restaging in melanoma were included in this study. We found that non-survivors had significantly higher median MTV (11.86 cm³ vs. 5.68 cm³; p-value = 0.022), TLG (3125 vs. 14; p-value = 0.0357), whole-body MTV (53.9 cm³ vs. 14.4 cm³; p-value = 0.0076) and whole-body TLG (963.4 vs. 114.6; p-value = 0.0056). This demonstrated that high MTV and TLG values of the primary tumor and whole-body TLG as quantified by ¹⁸F-FDG PET/CT were prognostic factors for overall survival. The findings may potentially guide clinicians in decision making and identifying patients with a poorer prognosis.

Predicting pathological response and overall survival in locally advanced gastric cancer patients undergoing neoadjuvant chemotherapy: the role of PET/computed tomography

BACKGROUND

Gastric cancer is the second leading cause of cancer-related deaths, with a 5-year survival rate of about 20-25%. The ability to predict pathological response (PR) to neoadjuvant chemotherapy (NACT); hence, overall survival (OS) probability of patients can allow the clinician to individualize treatment strategies. We investigated the role of F-18 fluorodeoxyglucose PET-computed tomography (F-18 FDG PET/CT) in predicting histopathologic response and prognosis in locally advanced gastric cancer (LAGC) patients undergoing NACT.

METHODS

F-18FDG PET/CT images taken before and after NACT, adenocarcinoma histopathology and operation pyesis reports of 43 LAGC patients were analyzed. Maximum (SUVmax) and mean (SUVmean) standardized uptake values, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of lesions were measured before and after NACT. Changes in percentage were calculated for ΔSUVmax%, ΔSUVmean%, ΔMTV%, ΔTLG%, and cutoff values were determined by receiver operating characteristic curve analysis. NACT response in pathology pyesis was determined according to the College of American Pathologists classification. PR and OS were analyzed with Kaplan-Meier and Cox proportional hazards regression models based on cutoffs found with PET measurements.

RESULTS

Cutoffs were ΔSUVmax = 33.31%, ΔSUVmean = 42.96%, ΔMTV = 30.38%, and ΔTLG = 28.14%, and all patients showed significance in PR and OS based on these cutoffs (all P < 0.01). PET/CT findings before and after NACT (ΔMTV > 30.38%, ΔTLG > 28.14%) predicted PR with 100% sensitivity and specificity. Multivariate analysis showed ΔSUVmean as an independent risk factor predicting OS (hazard ratio 0.348, 95% confidence interval 2.91-22.3, P = 0.03).

CONCLUSIONS

Metabolic parameters obtained with F-18 FDG PET/CT scanning before and after NACT in LAGC patients can accurately predict PR and OS.

Prognostic value of total metabolic tumour volume and therapy-response assessment by [18F]FDG PET/CT in patients with metastatic melanoma treated with BRAF/MEK inhibitors

OBJECTIVES

Target therapy with BRAF/MEK inhibitors in metastatic melanoma is characterised by a high response rate; however, acquired resistance to treatment develops in many cases. We aimed to investigate if baseline total metabolic tumour volume (TMTV) and therapy-response assessment by [¹⁸F]FDG PET/CT have a prognostic role on progression-free survival (PFS) and overall survival (OS) in patients with metastatic melanoma receiving BRAF ± MEK inhibitors.

METHODS

Fifty-seven patients who performed an [¹⁸F]FDG PET/CT at baseline and on treatment were retrospectively evaluated. A Cox proportional-hazard model was used to examine associations between OS and PFS with baseline clinical/PET parameters as well as for PET response.

RESULTS

According to EORTC criteria, 34 patients were classified as responders (partial/complete metabolic response [PMR/CMR]) and 23 as non-responders (progressive/stable metabolic disease [PMD/SMD]). Baseline characteristics associated with a shorter PFS were more than two metastatic organ sites and TMTV > 56 cm³; the latter was the only independent feature at multivariate analysis. Patients achieving a CMR were associated with a prolonged PFS compared with those with PMR (median PFS 42.9 vs 8.8 months; p = 0.009). Disease progression occurred in new-onset disease sites in 87.5% of CMR, 7.1% of PMR and 34.8% of PMD/SMD (p < 0.001). High baseline TMTV and lack of treatment response were independent prognostic factors for OS, stratifying patients in three different prognostic classes (median OS 6.7, 18.3 and 102.2 months, respectively).

CONCLUSIONS

Baseline TMTV and metabolic response may be useful prognostic indicators for PFS and OS in patients with advanced melanoma treated with BRAF/MEK inhibitors.

KEY POINTS

• In a retrospective cohort of 57 metastatic melanoma patients treated with BRAF/MEK inhibitors, a TMTV > 56 cm³ at baseline [¹⁸F]FDG PET/CT was significantly correlated with a shorter PFS and OS. • The combined use of baseline TMTV along with PET response during treatment allowed for the identification of three groups of patients with very different median OS.

Impact of time of flight and point spread function on quantitative parameters of lung lesions in 18F-FDG PET/CT

Background

Image reconstruction algorithm is one of the important factors affecting the quantitative parameters of PET/CT. The purpose of this study was to investigate the effects of time of flight (TOF) and point spread function (PSF) on quantitative parameters of lung lesions in ¹⁸F-FDG PET/CT.

Methods

This retrospective study evaluated 60 lung lesions in 39 patients who had undergone ¹⁸F-fluoro-deoxy-glucose (FDG) PET/CT. All lesions larger than 10 mm in diameter were included in the study. The PET data were reconstructed with a baseline ordered-subsets expectation–maximization (OSEM) algorithm, OSEM + PSF, OSEM + TOF and OSEM + TOF + PSF respectively. The differences of maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG)and signal to noise ratio (SNR)were compared among different reconstruction algorithms.

Results

Compared with OSEM reconstruction, using OSEM + TOF + PSF increased SUVmean and SUVmax by 23.73% and 22.71% respectively, and SNR increased by 70.18%, MTV decreased by 23.84% (p < 0.01). The percentage difference was significantly higher in smaller lesions (diameter 10–22 mm) than in larger lesions (diameter 23–44 mm), and significantly higher in low contrast lesions (SNR ≤ 15.31) than in high contrast lesions (SNR > 15.31). The difference of TLG among various reconstruction algorithms is relatively small, the highest value is − 6.48% of OSEM + TOF + PSF, and the lowest value is 0.81% of OSEM + TOF.

Conclusion

TOF and PSF significantly affected the quantitative parameters of lung lesions in ¹⁸F-FDG PET/CT. OSEM + TOF + PSF can significantly increased SUVmax, SUVmean and SNR, and significantly reduce MTV, especially in small lesions and low contrast lesions. TLG can be relatively stable in different reconstruction algorithms.

Radionuclide Imaging of Invasive Fungal Disease in Immunocompromised Hosts

Invasive fungal disease (IFD) leads to increased mortality, morbidity, and costs of treatment in patients with immunosuppressive conditions. The definitive diagnosis of IFD relies on the isolation of the causative fungal agents through microscopy, culture, or nucleic acid testing in tissue samples obtained from the sites of the disease. Biopsy is not always feasible or safe to be undertaken in immunocompromised hosts at risk of IFD. Noninvasive diagnostic techniques are, therefore, needed for the diagnosis and treatment response assessment of IFD. The available techniques that identify fungal-specific antigens in biological samples for diagnosing IFD have variable sensitivity and specificity. They also have limited utility in response assessment. Imaging has, therefore, been applied for the noninvasive detection of IFD. Morphologic imaging with computed tomography (CT) and magnetic resonance imaging (MRI) is the most applied technique. These techniques are neither sufficiently sensitive nor specific for the early diagnosis of IFD. Morphologic changes evaluated by CT and MRI occur later in the disease course and during recovery after successful treatment. These modalities may, therefore, not be ideal for early diagnosis and early response to therapy determination. Radionuclide imaging allows for targeting the host response to pathogenic fungi or specific structures of the pathogen itself. This makes radionuclide imaging techniques suitable for the early diagnosis and treatment response assessment of IFD. In this review, we aimed to discuss the interplay of host immunity, immunosuppression, and the occurrence of IFD. We also discuss the currently available radionuclide probes that have been evaluated in preclinical and clinical studies for their ability to detect IFD.

Radiomics-Based Texture Analysis of 68Ga-DOTATATE Positron Emission Tomography and Computed Tomography Images as a Prognostic Biomarker in Adults With Neuroendocrine Cancers Treated With 177Lu-DOTATATE

Purpose

Neuroendocrine tumors (NET) are rare cancers with variable behavior. A better understanding of prognosis would aid individualized management. The aim of this hypothesis-generating pilot study was to investigate the prognostic potential of tumor heterogeneity and tracer avidity in NET using texture analysis (TA) of ⁶⁸Ga-DOTATATE positron emission tomography (PET) and non-enhanced computed tomography (CT) performed at baseline in patients treated with ¹⁷⁷Lu-DOTATATE. It aims to justify a larger-scale study to evaluate its clinical value.

Methods

The pretherapy ⁶⁸Ga-DOTATATE PET-CT scans of 44 patients with metastatic NET (carcinoid, pancreatic, thyroid, head and neck, catecholamine-secreting, and unknown primary NET) treated with ¹⁷⁷Lu-DOTATATE were analyzed retrospectively using commercially available texture analysis research software. Image filtration extracted and enhanced objects of different sizes (fine, medium, coarse), then quantified heterogeneity by statistical and histogram-based parameters (mean intensity, standard deviation, entropy, mean of positive pixels, skewness, and kurtosis). Regions of interest were manually drawn around up to five of the most ⁶⁸Ga-DOTATATE avid lesions for each patient. ⁶⁸Gallium uptake on PET was quantified as SUV_max and SUV_mean. Associations between imaging and clinical markers with progression-free (PFS) and overall survival (OS) were assessed using univariate Kaplan-Meier analysis. Independence of the significant univariate markers of survival was tested using multivariate Cox regression analysis.

Results

Measures of heterogeneity (higher kurtosis, higher entropy, and lower skewness) on coarse-texture scale CT and unfiltered PET images predicted shorter PFS (CT coarse kurtosis: p=0.05, PET entropy: p=0.01, PET skewness: p=0.03) and shorter OS (CT coarse kurtosis: p=0.05, PET entropy: p=0.01, PET skewness p=0.02). Conventional PET parameters such as SUV_max and SUV_mean showed trends towards predicting outcome but were not statistically significant. Multivariate analysis identified that CT-TA (coarse kurtosis: HR=2.57, 95% CI=1.22–5.38, p=0.013) independently predicted PFS, and PET-TA (unfiltered skewness: HR=9.05, 95% CI=1.19–68.91, p=0.033) independently predicted OS.

Conclusion

These preliminary data generate a hypothesis that radiomic analysis of neuroendocrine cancer on ⁶⁸Ga-DOTATATE PET-CT may be of prognostic value and a valuable addition to the assessment of patients.

Mid-treatment Fluorodeoxyglucose Positron Emission Tomography in Human Papillomavirus-related Oropharyngeal Squamous Cell Carcinoma Treated with Primary Radiotherapy: Nodal Metabolic Response Rate can Predict Treatment Outcomes

AIMS

To evaluate whether biomarkers derived from fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) performed prior to (prePET) and during the third week (interim PET; iPET) of radiotherapy can predict treatment outcomes in human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPC).

MATERIALS AND METHODS

This retrospective analysis included 46 patients with newly diagnosed OPC treated with definitive (chemo)radiation and all patients had confirmed positive HPV status (HPV+OPC) based on p16 immunohistochemistry. The maximum standardised uptake value (SUV_max), metabolic tumour volume (MTV) and total lesional glycolysis (TLG) of primary, index node (node with the highest TLG) and total lymph nodes and their median percentage (≥50%) reductions in iPET were analysed, and correlated with 5-year Kaplan-Meier and multivariable analyses (smoking, T4, N2b-3 and AJCC stage IV), including local failure-free survival, regional failure-free survival, locoregional failure-free survival (LRFFS), distant metastatic failure-free survival (DMFFS), disease-free survival (DFS) and overall survival.

RESULTS

There was no association of outcomes with prePET parameters observed on multivariate analysis. A complete metabolic response of primary tumour was seen in 13 patients; the negative predictive value for local failure was 100%. More than a 50% reduction in total nodal MTV provided the best predictor of outcomes, including LRFFS (88% versus 47.1%, P = 0.006, hazard ratio = 0.153) and DFS (78.2% versus 41.2%, P = 0.01, hazard ratio = 0.234). More than a 50% reduction in index node TLG was inversely related to DMFFS: a better nodal response was associated with a higher incidence of distant metastatic failure (66.7% versus 100%, P = 0.009, hazard ratio = 3.0).

CONCLUSION

The reduction (≥50%) of volumetric nodal metabolic burden can potentially identify a subgroup of HPV+OPC patients at low risk of locoregional failure but inversely at higher risk of distant metastatic failure and may have a role in individualised adaptive radiotherapy and systemic therapy.

Prognostic value of tumor metabolic imaging phenotype by FDG PET radiomics in HNSCC

OBJECTIVE

Tumor metabolic phenotype can be assessed with integrated image pattern analysis of ¹⁸F-fluoro-deoxy-glucose (FDG) Positron Emission Tomography/Computed Tomography (PET/CT), called radiomics. This study was performed to assess the prognostic value of radiomics PET parameters in head and neck squamous cell carcinoma (HNSCC) patients.

METHODS

¹⁸F-fluoro-deoxy-glucose (FDG) PET/CT data of 215 patients from HNSCC collection free database in The Cancer Imaging Archive (TCIA), and 122 patients in Seoul St. Mary's Hospital with baseline FDG PET/CT for locally advanced HNSCC were reviewed. Data from TCIA database were used as a training cohort, and data from Seoul St. Mary's Hospital as a validation cohort. With the training cohort, primary tumors were segmented by Nestles' adaptive thresholding method. Segmental tumors in PET images were preprocessed using relative resampling of 64 bins. Forty-two PET parameters, including conventional parameters and texture parameters, were measured. Binary groups of homogeneous imaging phenotypes, clustered by K-means method, were compared for overall survival (OS) and disease-free survival (DFS) by log-rank test. Selected individual radiomics parameters were tested along with clinical factors, including age and sex, by Cox-regression test for OS and DFS, and the significant parameters were tested with multivariate analysis. Significant parameters on multivariate analysis were again tested with multivariate analysis in the validation cohort.

RESULTS

A total of 119 patients, 70 from training, and 49 from validation cohort, were included in the study. The median follow-up period was 62 and 52 months for the training and the validation cohort, respectively. In the training cohort. binary groups with different metabolic radiomics phenotypes showed significant difference in OS (p = 0.036), and borderline difference in DFS (p = 0.086). Gray-Level Non-Uniformity for zone (GLNU_GLZLM) was the most significant prognostic factor for both OS (hazard ratio [HR] 3.1, 95% confidence interval [CI] 1.4-7.3, p = 0.008) and DFS (HR 4.5, CI 1.3-16, p = 0.020). Multivariate analysis revealed GLNU_GLZLM as an independent prognostic factor for OS (HR 3.7, 95% CI 1.1-7.5, p = 0.032). GLNU_GLZLM remained as an independent prognostic factor in the validation cohort (HR 14.8. 95% CI 3.3-66, p < 0.001).

CONCLUSIONS

Baseline FDG PET radiomics contain risk information for survival prognosis in HNSCC patients. The metabolic heterogeneity parameter, GLNU_GLZLM, may assist clinicians in patient risk assessment as a feasible prognostic factor.

Characterization of FDG PET Images Using Texture Analysis in Tumors of the Gastro-Intestinal Tract: A Review

Radiomics or textural feature extraction obtained from positron emission tomography (PET) images through complex mathematical models of the spatial relationship between multiple image voxels is currently emerging as a new tool for assessing intra-tumoral heterogeneity in medical imaging. In this paper, available literature on texture analysis using FDG PET imaging in patients suffering from tumors of the gastro-intestinal tract is reviewed. While texture analysis of FDG PET images appears clinically promising, due to the lack of technical specifications, a large variability in the implemented methodology used for texture analysis and lack of statistical robustness, at present, no firm conclusions can be drawn regarding the predictive or prognostic value of FDG PET texture analysis derived indices in patients suffering from gastro-enterologic tumors. In order to move forward in this field, a harmonized image acquisition and processing protocol as well as a harmonized protocol for texture analysis of tumor volumes, allowing multi-center studies excluding statistical biases should be considered. Furthermore, the complementary and additional value of CT-imaging, as part of the PET/CT imaging technique, warrants exploration.

Prognostic and Predictive Values of Metabolic Parameters of 18F-FDG PET/CT in Patients With Non-Small Cell Lung Cancer Treated With Chemotherapy

Objectives:

Increasing interests have been focused on using artificial intelligence (AI) to extend prognostic value of medical imaging. Feature extraction is a critical step for successful application of AI. The aim of this study was to explore several metabolic parameters measured by ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) as potential AI features in predicting the effectiveness of chemotherapy in patients with non-small cell lung cancer (NSCLC).

Methods:

A set of metabolic parameters of PET/CT and clinical characteristics were detected from 137 patients with NSCLC treated with at least 1 cycle of chemotherapy. Survival receiver–operating characteristic (ROC) analysis was used to define the more significant parameters chosen for the following survival analysis. Patient survival was analyzed by Kaplan-Meier method, log-rank test, and Cox regression.

Results:

Survival ROC showed that maximum standardized uptake value (SUVmax), metabolic tumor volume 50% (MTV50), and total lesion glycolysis 50% (TLG50) had larger area under the curve, and the optimal cutoff values were 11.72, 4.04, and 34.55, respectively. Univariate and multivariate analyses synergistically showed that late PET/CT stage and MTV50 >4.04 were independent factors of poor survival in patients with NSCLC who received chemotherapy.

Conclusions:

Several potential prognostic biomarkers of PET/CT imaging have been extracted for predicting survival and selecting patients with NSCLC who are more likely to benefit from chemotherapy. The identification may accelerate the development of AI methods to improve treatment outcome for NSCLC.

Potential Applications of PET-Based Novel Quantitative Techniques in Pediatric Diseases and Disorders

The progress made in hybrid PET imaging during the past decades has significantly expanded the role of this modality in both clinical and research applications. Semi-quantitative PET/CT has been the workhorse of clinical PET/CT due to its simplicity and availability. In addition to semi-quantitative PET/CT, volumetric PET and global metabolic activity have recently shown promise in a more accurate assessment of various diseases. PET/CT has been widely used in pediatric oncologic and non-oncologic diseases. Here we have highlighted few of the pitfalls in the quantitative PET/CT and their potential remedies which have potential in PET/CT evaluation of pediatric diseases.

The relationship between FDG PET/CT-defined metabolic parameters and the histopathological subtype of oesophageal carcinomas

Purpose

18F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) combined with computed tomography (CT) scan is accepted as a standard tool in the staging of oesophageal cancer (OC). Histological subtype of tumour is known to be a major determinant of prognosis and metabolic behaviour. In this study, we aimed to evaluate the effect of histological subtypes of OC on standard uptake value (SUV_max), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) obtained by PET/CT, and also to compare this effect with prognosis.

Material and methods

Images and clinical course data of 57 patients who were diagnosed with EC and treated in our hospital between 2009 and 2016 were evaluated in a retrospective manner. PET/CT images were re-analysed in terms of metabolic parameters, and observations were compared with histological subtypes.

Results

No significant difference was observed between histological subtypes with SUV_max, overall survival (OS), or progression-free survival (PFS). Thus, MTV was observed to be related with histological subtype; MTV values of adenocancer patients were significantly higher than those of squamous cell cancer patients.

Conclusions

Metabolic tumour volume was related with histological subtype of OC, but clinical staging, TLG, and SUV_max values were not related with histological subtype, which may suggest the use of MTV as a routine parameter for OC and inclusion of MTV observations in prognostic scoring.

A Pilot Study of Texture Analysis of Primary Tumor [18F]FDG Uptake to Predict Recurrence in Surgically Treated Patients with Non-small Cell Lung Cancer

PURPOSE

To examine whether the heterogeneous texture parameters in primary tumor can predict prognosis of patients with non-small cell lung cancer (NSCLC) received surgery after 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography (PET)/X-ray computed tomography (CT).

PROCEDURE

This retrospective study included 55 patients with NSCLC who underwent [¹⁸F]FDG-PET/CT before surgery from January 2011 and December 2015. SUV-related (SUVmax and SUVmean), volumetric (metabolic tumor volume [SUV ≥ 2.5], and total lesion glycolysis) and texture parameters (local parameters; entropy, homogeneity, and dissimilarity and regional parameters; intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) were obtained. Tumor size, TNM stage, SUV-related, volumetric, and texture parameters were compared between the patients with progression and without progression using Mann-Whitney's U or χ² test and progression-free survival (PFS) and prognostic significance were assessed by Kaplan-Meier method and Cox regression analysis, respectively.

RESULTS

Nineteen patients eventually showed progression, and 36 patients were alive without progression during clinical follow-up (median follow-up PFS; 23 months [range, 1-71]). The patients with progression showed significantly larger tumor size (p < 0.001), higher IV (p = 0.010), and higher SZV (p = 0.007) than those without progression. PFS was significantly shorter in patients with large tumor size (p = 0.008), high T stage (p = 0.009), high stage (p = 0.013), high IV (p = 0.012), and high SZV (p = 0.015) at univariate analysis. At multivariate analysis, stage (hazard ratio [HR] 1.62, p = 0.035) and IV (hazard ratio 6.19, p = 0.048) were only remained independent predictors for PFS.

CONCLUSIONS

The regional heterogeneity texture parameters IV and SZV can predict tumor progression, and IV has the potential to predict prognosis of surgically treated NSCLC patients.

18F-FDG Pet Parameters and Radiomics Features Analysis in Advanced Nsclc Treated with Immunotherapy as Predictors of Therapy Response and Survival

Objectives: (1.1) to evaluate the association between baseline 18F-FDG PET/CT semi-quantitative parameters of the primary lesion with progression free survival (PFS), overall survival (OS) and response to immunotherapy, in advanced non-small cell lung carcinoma (NSCLC) patients eligible for immunotherapy; (1.2) to evaluate the application of radiomics analysis of the primary lesion to identify features predictive of response to immunotherapy; (1.3) to evaluate if tumor burden assessed by 18F-FDG PET/CT (N and M factors) is associated with PFS and OS. Materials and Methods: we retrospectively analyzed clinical records of advanced NCSLC patients (stage IIIb/c or stage IV) candidate to immunotherapy who performed 18F-FDG PET/CT before treatment to stage the disease. Fifty-seven (57) patients were included in the analysis (F:M 17:40; median age = 69 years old). Notably, 38/57 of patients had adenocarcinoma (AC), 10/57 squamous cell carcinoma (SCC) and 9/57 were not otherwise specified (NOS). Overall, 47.4% patients were stage IVA, 42.1% IVB and 8.8% IIIB. Immunotherapy was performed as front-line therapy in 42/57 patients and as second line therapy after chemotherapy platinum-based in 15/57. The median follow up after starting immunotherapy was 10 months (range: 1.5–68.6). Therapy response was assessed by RECIST 1.1 criteria (CT evaluation every 4 cycles of therapy) in 48/57 patients or when not feasible by clinical and laboratory data (fast disease progression or worsening of patient clinical condition in nine patients). Radiomics analysis was performed by applying regions of interest (ROIs) of the primary tumor delineated manually by two operators and semi-automatically applying a threshold at 40% of SUVmax. Results: (1.1) metabolic tumor volume (MTV) (p = 0.028) and total lesion glycolysis (TLG) (p = 0.035) were significantly associated with progressive vs. non-progressive disease status. Patients with higher values of MTV and TLG had higher probability of disease progression, compared to those patients presenting with lower values. SUVmax did not show correlation with PD status, PFS and OS. MTV (p = 0.027) and TLG (p = 0.022) also resulted in being significantly different among PR, SD and PD groups, while SUVmax was confirmed to not be associated with response to therapy (p = 0.427). (1.2) We observed the association of several radiomics features with PD status. Namely, patients with high tumor volume, TLG and heterogeneity expressed by “skewness” and “kurtosis” had a higher probability of failing immunotherapy. (1.3) M status at 18F-FDG PET/CT was significantly associated with PFS (p = 0.002) and OS (p = 0.049). No significant associations were observed for N status. Conclusions: 18F-FDG PET/CT performed before the start of immunotherapy might be an important prognostic tool able to predict the disease progression and response to immunotherapy in patients with advanced NSCLC, since MTV, TLG and radiomics features (volume and heterogeneity) are associated with disease progression.

Total metabolic tumor volume by 18F-FDG PET/CT for the prediction of outcome in patients with non-small cell lung cancer

OBJECTIVE

Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are imaging parameters derived from 18F-FDG PET/CT that have been proposed for risk stratification of cancer patients. The aim of our study was to test whether these whole-body volumetric imaging parameters may predict outcome in patients with non-small cell lung cancer (NSCLC).

METHODS

Sixty-five patients (45 men, 20 women; mean age ± SD, 65 ± 12 years), with histologically proven NSCLC who had undergone 18F-FDG PET/CT scan before any therapy, were included in the study. Imaging parameters including SUV_max, SUV_mean, total MTV (MTV_TOT) and whole-body TLG (TLG_WB) were determined. Univariate and multivariate analyses of clinical and imaging variables were performed using Cox proportional hazards regression. Survival analysis was performed using Kaplan-Meier method and log-rank tests.

RESULTS

A total of 298 lesions were analyzed including 65 primary tumors, 114 metastatic lymph nodes and 119 distant metastases. MTV_TOT and TLG_WB could be determined in 276 lesions. Mean value of MTV_TOT was 81.83 ml ± 14.63 ml (SE) whereas mean value of TLG_WB was 459.88 g ± 77.02 g (SE). Univariate analysis showed that, among the variables tested, primary tumor diameter (p = 0.0470), MTV of primary tumor (p = 0.0299), stage (p < 0.0001), treatment (p < 0.0001), MTV_TOT (p = 0.0003) and TLG_WB (p = 0.0002) predicted progression-free survival in NSCLC patients, while age (p = 0.0550), MTV of primary tumor (p = 0.0375), stage (p < 0.0001), treatment (p < 0.0001), MTV_TOT (p = 0.0001) and TLG_WB (p = 0.0008) predicted overall survival. At multivariate analysis age, TLG_WB and stage were retained in the model for prediction of progression-free survival (p < 0.0001), while age, MTV_TOT and stage were retained in the model for prediction of overall survival (p < 0.0001). Survival analysis showed that patients with TLG_WB ≤ 54.7 g had a significantly prolonged progression-free survival as compared to patients with TLG_WB > 54.7 g (p < 0.0001). Moreover, overall survival was significantly better in patients showing a MTV_TOT ≤ 9.5 ml as compared to those having MTV_TOT > 9.5 ml (p < 0.0001). Similar results were obtained in a subgroup of 43 patients with advanced disease (stages III and IV).

CONCLUSIONS

Whole-body PET-based volumetric imaging parameters are able to predict outcome in NSCLC patients.

Prognostic value of 18F-FDG PET/MR imaging biomarkers in oesophageal squamous cell carcinoma

PURPOSE

To correlate the clinical stage and prognosis of oesophageal squamous cell carcinoma (SCC) using the imaging biomarkers from integrated positron emission tomography (PET)/magnetic resonance imaging (MRI).

METHODS

In total, 54 consecutive patients with oesophageal SCC who receive PET/MRI scan were recruited before treatment. The imaging biomarkers used were the mean and minimal apparent diffusion coefficients (ADC_mean and ADC_min), standardized uptake value (SUV), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) of tumours. The correlation between each imaging biomarker and survival was investigated using the Cox proportional hazards model.

RESULTS

ADC_mean was negatively correlated with SUV_max (r = -0.414, P =  0.025). ADC_min was negatively correlated with SUV_max (r = -0.423, P =  0.001) and SUV_peak (r = -0.402, P =  0.003), and was significantly lower in M1 than in M0 tumours (829.6 vs. 1069.8, P = 0.005). MTV was significantly higher in T3 + (P <  0.001), N1 + (P = 0.014) and TNM stage III + (P <  0.001) tumours. TLG was significantly higher in T3 + (P <  0.001), N1 + (P <  0.001), M1 (P =  0.045) and TNM stage III + (P <  0.001) tumours. The MTV/ADC_min ratio exhibited the highest area under the receiver operating characteristic curve (AUROC) for predicting M1 and advanced TNM stage tumours. Multivariate analysis for progression-free survival (PFS) and overall survival (OS) showed that a larger MTV/ADC_min was associated with a shorter PFS and OS (P = 0.024 and 0.046, respectively).

CONCLUSION

The imaging biomarkers in integrated PET/MRI may predict clinical stage and survival in patients with oesophageal SCC.

Volumetric parameters on 18F-FDG PET/CT predict the survival of patients with gastric cancer associated with their expression status of c-MET

Background

This study aimed to investigate the prognostic value of volumetric parameters on ¹⁸F- fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) in gastric-cancer patients, according to the expression status of c-MET (MET proto-oncogene, receptor tyrosine kinase), which was previously unclear.

Methods

The study included 61 patients with advanced gastric cancer. Data on the baseline ¹⁸F-FDG PET/CT, clinical-pathological information, progression-free survival (PFS), and overall survival (OS) were collected. The maximum standardized uptake value (SUV_max), peak SUV (SUV_peak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of gastric tumors in situ were measured on PET/CT. The expression status of c-MET was recorded based on immunohistochemical staining. Associations between the parameters on PET/CT and patients’ survival outcomes were analyzed in relation to expression status of c-MET.

Results

Patients with positive c-MET expression had significantly shorter PFS (11.5 vs. 17.6 months, P = 0.039) and OS (17.0 vs. 24.3 months, P = 0.043), and had gastric tumors with a larger MTV (70.8 ± 53.11 vs. 41.1 ± 52.32, P = 0.034) and TLG (428.39 ± 442.95 vs. 205.7 ± 354.40, P = 0.039), compared with those with negative c-MET expression. However, SUV_max (9.6 ± 7.40 vs. 8.0 ± 4.91, P = 0.335) and SUV_peak (7.7 ± 5.99 vs. 6.62 ± 4.08, P = 0.438) were similar between these two patient groups. In patients with c-MET-positive tumors, MTV and TLG were independent factors in predicting patient OS after correction by distant metastasis (hazards ratio = 1.014 and 1.002, respectively; P = 0.024 and 0.027, respectively), while these associations were not significant in patients with c-MET-negative tumors.

Conclusions

Patients with c-MET-positive gastric cancer had higher MTV and TLG values compared to those with c-MET-negative gastric cancer. In patients with c-MET-positive gastric cancer, volumetric parameters on ¹⁸F-FDG PET/CT have prognostic value for patient overall survival.

Deep Convolutional Neural Network-Based Positron Emission Tomography Analysis Predicts Esophageal Cancer Outcome

In esophageal cancer, few prediction tools can be confidently used in current clinical practice. We developed a deep convolutional neural network (CNN) with 798 positron emission tomography (PET) scans of esophageal squamous cell carcinoma and 309 PET scans of stage I lung cancer. In the first stage, we pretrained a 3D-CNN with all PET scans for a task to classify the scans into esophageal cancer or lung cancer. Overall, 548 of 798 PET scans of esophageal cancer patients were included in the second stage with an aim to classify patients who expired within or survived more than one year after diagnosis. The area under the receiver operating characteristic curve (AUC) was used to evaluate model performance. In the pretrain model, the deep CNN attained an AUC of 0.738 in identifying patients who expired within one year after diagnosis. In the survival analysis, patients who were predicted to be expired but were alive at one year after diagnosis had a 5-year survival rate of 32.6%, which was significantly worse than the 5-year survival rate of the patients who were predicted to survive and were alive at one year after diagnosis (50.5%, p < 0.001). These results suggest that the prediction model could identify tumors with more aggressive behavior. In the multivariable analysis, the prediction result remained an independent prognostic factor (hazard ratio: 2.830; 95% confidence interval: 2.252–3.555, p < 0.001). We conclude that a 3D-CNN can be trained with PET image datasets to predict esophageal cancer outcome with acceptable accuracy.

Challenges and caveats of a multi-center retrospective radiomics study: an example of early treatment response assessment for NSCLC patients using FDG-PET/CT radiomics

Background

Prognostic models based on individual patient characteristics can improve treatment decisions and outcome in the future. In many (radiomic) studies, small size and heterogeneity of datasets is a challenge that often limits performance and potential clinical applicability of these models. The current study is example of a retrospective multi-centric study with challenges and caveats. To highlight common issues and emphasize potential pitfalls, we aimed for an extensive analysis of these multi-center pre-treatment datasets, with an additional ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scan acquired during treatment.

Methods

The dataset consisted of 138 stage II-IV non-small cell lung cancer (NSCLC) patients from four different cohorts acquired from three different institutes. The differences between the cohorts were compared in terms of clinical characteristics and using the so-called ‘cohort differences model’ approach. Moreover, the potential prognostic performances for overall survival of radiomic features extracted from CT or FDG-PET, or relative or absolute differences between the scans at the two time points, were assessed using the LASSO regression method. Furthermore, the performances of five different classifiers were evaluated for all image sets.

Results

The individual cohorts substantially differed in terms of patient characteristics. Moreover, the cohort differences model indicated statistically significant differences between the cohorts. Neither LASSO nor any of the tested classifiers resulted in a clinical relevant prognostic model that could be validated on the available datasets.

Conclusion

The results imply that the study might have been influenced by a limited sample size, heterogeneous patient characteristics, and inconsistent imaging parameters. No prognostic performance of FDG-PET or CT based radiomics models can be reported. This study highlights the necessity of extensive evaluations of cohorts and of validation datasets, especially in retrospective multi-centric datasets.

Fluorodeoxyglucose Positron Emission Tomography integrated with computed tomography in carcinoma of the cervix: Its impact on accurate staging and the predictive role of its metabolic parameters

OBJECTIVES

To determine the impact of FDG-PET/CT in the initial staging of cervical cancer among women with and without HIV and to determine the abilities of FDG-PET/CT metabolic parameters in predicting the presence of distant metastasis.

METHODS

We reviewed the FDG-PET/CT images of women with FIGO stage IB2 to IVA carcinoma of the cervix. We compared the FIGO stage before and after FDG-PET/CT. Maximum and mean standardized uptake values (SUVmax and SUVmean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary lesion were determined. We compared these parameters between the HIV-infected and uninfected woman and also determined their abilities to predict the presence of distant metastasis.

RESULTS

126 women, mean age 48.05 ± 11.80 years were studied. Seventy-three patients were HIV-infected. The disease was upstaged in 65 patients, 32 of which were upstaged to stage IVB. HIV-infected women were younger (43.36 ± 8.03 years versus 54.51 ± 13.12, p<0.001) and had more advanced disease (p = 0.022) compared with HIV-uninfected. In a univariate logistic regression adjusted for the FIGO stage of the disease, there were significant associations between MTV and TLG of the primary tumor and distant metastasis. SUVmax, SUVmean, MTV and TLG performed well in predicting the presence of distant metastasis with areas under the curves (AUCs) of 0.63, 0.66, 0.80 and 0.77 respectively. These performances improved after adjustment for the FIGO stage of the disease with AUCs of 0.80, 0.79, 0.84 and 0.82 for SUVmax, SUVmean, MTV and TLG respectively.

CONCLUSION

Inclusion of 18F-FDG-PET/CT in the pre-therapy assessment of cervical cancer improves the accuracy of staging in about half of the patients. The metabolic parameters of the primary tumor perform well in predicting the presence of distant metastases.

Radiomics: Principles and radiotherapy applications

Radiomics is defined as the extraction of a large quantity of quantitative image features. The different radiomic indexes that have been proposed in the literature are described as well as the various factors that have an impact on the robustness of these indexes. We will see that several hundred quantitative features can be extracted per lesion and imaging modality. The ever-growing number of features studied raises the question of the statistical method of analysis used. This review addresses the research supporting the clinical use of radiomics in oncology in the staging of disease, discrimination between healthy and pathological tissues, the identification of genetic features, the prediction of patient survival, the response to treatment, the recurrence after radiotherapy and chemoradiotherapy and the side effects. Based on the existing literature, it remains difficult to identify features that should be used for current clinical practice.

Role of multi-modality functional imaging in differentiation between benign and malignant thyroid 18F-fluorodeoxyglucose incidentaloma

PURPOSE

To evaluate the diagnostic performance of multi-modality functional imaging in differentiating malignant and benign thyroid ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) incidentaloma.

METHODS

This study included 87 patients with thyroid ¹⁸F-FDG incidentalomas detected by ¹⁸F-FDG- positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) and diagnosed at surgery or biopsy, who received ¹⁸F-FDG-PET/CT, diffusion-weighted MR imaging (DWI) and ultrasound elastography (USE). The metabolic tumor volume (MTV), total lesion glycolysis (TLG), apparent diffusion coefficient (ADC) values and ultrasound elasticity scores of thyroid ¹⁸F-FDG incidentalomas were measured and compared in benign and malignant thyroid incidentalomas. The differences of malignant and benign thyroid incidentalomas were tested by χ² test, Fisher's exact test, t test, or Mann-Whitney U test. The diagnostic performance was evaluated and optimal cut-off values were determined in distinguishing malignant from benign thyroid incidentalomas by receiver operating characteristic curve analysis.

RESULTS

MTV, TLG and USE scores of malignant thyroid incidentalomas were significantly higher than benign; but ADC value was significantly lower. We defined the functional imaging parameters TLG < 2.48, ADC > 1.80 × 10^-3mm²/s, and USE score of 1 as markers of benign thyroid incidentalomas and each scored -1 point; TLG ≥ 2.48, ADC ≤ 1.80 × 10^-3mm²/s, and USE score of 4 as markers of malignancy and each scored 1 point. Combined multi-functional imaging parameters achieved the highest performance (84.6% sensitivity and 97.1% specificity) for distinguish malignant from benign thyroid incidentaloma with AUC 0.957 (95% CI 0.917, 0.997).

CONCLUSIONS

Functional imaging might help to distinguishing malignant from benign thyroid ¹⁸F-FDG incidentalomas, and combined multi-functional imaging parameters could improve it.

Metabolic tumor burden on postsurgical PET/CT predicts survival of patients with gastric cancer

Background

The prognostic value of postoperative ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) to patients with gastric cancer remains unclear. This study aims to investigate the prognostic value of whole body (WB) metabolic tumor burden (MTB_WB) on postsurgical ¹⁸F-FDG PET/CT to patients with gastric cancer.

Methods

A total of 376 patients with surgeries-confirmed gastric cancer were enrolled. Clinicopathologic information, overall survival (OS) and MTB_WB parameters on postsurgical PET/CT, in terms of WB maximum standardized uptake value (SUV_WBmax), WB metabolic tumor volume (MTV_WB), and WB total lesion glycolysis (TLG_WB) were collected. In-between differences of patient clinicopathologic characteristics, OS and MTB_WB measurements were compared using chi-square test, Fisher’s exact test, Student’s t test or the Kaplan-Meier survival analysis. The optimal cutoffs of MTB_WB measurements were calculated through the receiver operating characteristic (ROC) curve analysis. Univariable and multivariable Cox proportional hazard regression were performed to test the predictive value of the clinicopathologic factors and MTB_WB measurements to patient survival.

Results

The PET-positive patients had significantly decreased OS based on either Kaplan-Meier survival analysis (P <  0.001) or univariable Cox regression (hazard ratio [HR] = 2.850, P <  0.001). In patients with PET-positive tumors, the associations between OS and SUV_WBmax, MTV_WB and TLG_WB were significant, both in univariable analysis (P <  0.001, P <  0.001 and P = 0.001, respectively) and in multivariable analysis (P = 0.002, P <  0.001 and P = 0.005, respectively). Patient OS among groups dichotomized by cutoffs of SUV_WBmax > 8.6, MTV_WB > 91.5 cm³, and TLG_WB > 477.6 cm³ were significantly different (P = 0.001, P <  0.001 and P = 0.001, respectively).

Conclusions

MTB_WB, in terms of SUV_WBmax, MTV_WB and TLG_WB, on postsurgical ¹⁸F-FDG PET/CT provides prognostic value to patients with gastric cancer after curative resection.

Metabolic parameters of sequential 18F-FDG PET/CT predict overall survival of esophageal cancer patients treated with (chemo-) radiation

BACKGROUND

To evaluate the prognostic value of metabolic parameters of pre-treatment and interim 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for overall survival (OS) of esophageal cancer(EC) patients undergoing (chemo-) radiotherapy.

METHODS

A retrospective analysis of 134 patients with pathology confirmed squamous cell EC treated between July 2009 and October 2013 in our hospital was performed. Inclusion criteria for this study were curative intended radiotherapy and availability of pre-treatment and interim 18F-FDG PET. 18F-FDG PET/CT scans were acquired before treatment and after 40 Gray (Gy) of radiotherapy. Maximum standard uptake value (SUV_max), metabolic tumor volume(MTV), total lesion glycolysis (TLG), and the percentual changes during both PET scans were recorded. The parameters were named as SUVmax1,MTV1,TLG1,SUVmax2,MTV2,TLG2,△SUV_max,△MTV and △TLG. The receiver operating characteristic curve (ROC) was used to analyze the relationship between metabolic parameters and OS, survival analysis was carried out by Kaplan-Meier and Cox regression analysis.

RESULTS

Univariate survival analysis showed that SUVmax2、MTV1、△MTV、TLG1、TLG2 and △TLG were associated with OS. Based on the largest Youden index of ROC curves, patients with SUVmax2 < 7.8, MTV1 < 10.5, △MTV < 0.075, TLG1 < 59.8, TLG2 < 44.3 and △TLG < 0.27 tended to live longer. Stratified for these parameters, the estimated median survival time were 27.9 months (m) vs 9.8 m, 36.9 m vs 11.3 m, 41.6 m vs 12 m, 48.9 m vs 14.3 m, 32.6 m vs 13.2 m, and 41.6 m vs 14.5 m. Cox multi-factor regression analyses revealed SUV_max2 as an independent prognostic factor for OS complementary to TNM staging and the length of primary tumor.

CONCLUSIONS

Sequential 18F-FDG PET/CT metabolic parameters bear important prognostic value for OS of EC patients. 18F-FDG PET/CT scan before treatment and during chemoradiotherapy seems helpful to evaluate the effect of chemoradiotherapy, guide clinical decisions and provide patients with personalized treatment.

Evaluation of lobar lymph node metastasis in non-small cell lung carcinoma using modified total lesion glycolysis

Background

Volumetric parameters based on 3-dimensional reconstruction have recently been introduced for cancer staging. We aimed to improve the ability to diagnose hilar lymph node metastasis in patients with non-small cell lung cancer.

Methods

We evaluated 142 patients with non-small cell lung cancer who underwent right upper lobectomy and radical lymph node dissection. Metastatic involvement of right upper lobar lymph nodes was assessed using high-resolution computed tomography (HRCT) and 18F-2-floro-2-deoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT).

Results

On receiver operating characteristic (ROC) curve analysis, the area under the curves (AUC) for short axis, maximum of standardized uptake value (SUV_max), total lesion glycolysis (TLG) and modified TLG (mTLG) were 0.79, 0.77, 0.76, and 0.87, respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mTLG, using the optimal cut off value (2.45), for diagnosis of lobar lymph node metastasis were 71%, 88%, 44%, and 96%, respectively. Hilar asymmetric uptake (HAU) of FDG was larger in true-positive cases than in false-negative cases (P<0.01). Furthermore, the size of metastatic foci in the lymph node was smaller in false-negative cases (P=0.012).

Conclusions

Modified TLG is a good parameter to diagnose metastatic right upper lobar lymph nodes. Micrometastasis in the lymph node is difficult to predict using the current diagnostic method. However, more careful evaluation is required in patients with symmetric FDG accumulation at hilar region because hilar lymph nodes respond to various causes such as benign pulmonary diseases.

Diagnostic Value of FDG PET-CT Quantitative Parameters and Deauville-Like 5 Point-Scale in Predicting Malignancy of Focal Thyroid Incidentaloma

Objective: To evaluate the diagnostic value of FDG PET-CT metabolic parameters and Deauville-like 5 point-scale to predict malignancy in a population of patients presenting focal thyroid incidentaloma (fTI).

Design: This retrospective study included 41 fTI, classified according to cytological and histological data as benign (BL) or malignant lesion (ML). FDG PET-CT semi-quantitative parameters (SUVmax, SUVmean, SUVpeak, MTV, TLG), tumor to liver SUVmean ratio (TLRmax and TLRmean), tumor to blood-pool SUVmean ratio (TBRmax and TBRmean) were calculated. Each fTI was also classified on a Deauville-like 5-point scale (DS) currently used in lymphoma. Comparison between BL and ML was performed for each parameter and a ROC analysis was conducted.

Results: All quantitative PET metabolic parameters (SUV parameters, volume based parameters and SUV ratio) were higher in ML compared with BL, yet no significant difference was reported. fTI (uptake) malignancy rate according to DS grades 2, 3, 4, and 5 was, respectively, 25% (1 of 4), 28.6% (2 of 7), 8.3% (1 of 12), and 33.3% (6 of 18) with no significant difference between ML and BL groups. Results of ROC analysis showed that mean TBR had the highest AUC in our cohort (0.66 95%CI [0.41; 0.91]) with a cut-off value of 2.2. Specificity of MTV and TLG was 100% (cut-off values: MTV 9.6 ml, TLG 22.9 g) and their sensitivity was 30 and 40%, respectively.

Conclusion: Our study did not highlight any FDG PET/CT parameter predictor of fTI malignancy.

Metabolic tumour volume is prognostic in patients with non-small-cell lung cancer treated with stereotactic ablative radiotherapy

Introduction

Stereotactic ablative radiotherapy (sabr) is a relatively new technique for the curative-intent treatment of patients with inoperable early-stage non-small-cell lung cancer (nsclc). Previous studies have demonstrated a prognostic value for positron emission tomography-computed tomography (pet/ct) parameters, including maximal standardized uptake value (suv_max), metabolic tumour volume (mtv), and total lesion glycolysis (tlg) in lung cancer patients. We aimed to determine which pet/ct parameter is most prognostic of local control (lc) and overall survival (os) in patients treated with sabr for nsclc.

Methods

We conducted a retrospective review of patients treated with sabr for stage I inoperable nsclc at BC Cancer between 2009 and 2013. The Akaike information criterion was used to compare the prognostic value of the various pet/ct parameters.

Results

The study included 134 patients with a median age of 76 years. Median tumour diameter was 2.2 cm, gross tumour volume was 8.1 mL, suv_max was 7.9, mtv was 2.4 mL, and tlg was 10.9 suv·mL. The 2-year lc was 92%, and os was 66%. On univariate and multivariate analysis, imaging variables including tumour size, gross tumour volume, suv_max, mtv, and tlg were all associated with worse lc. Tumour size was not associated with significantly worse os, but other imaging variables were. The pet/ct parameter most prognostic of lc was mtv. Compared with suv_max, tlg and mtv were more prognostic of os.

Conclusions

In patients with early-stage nsclc treated with sabr, mtv appears to be prognostic of lc and os.

Efficacy of 4'-[methyl-11C] thiothymidine PET/CT before and after neoadjuvant therapy for predicting therapeutic responses in patients with esophageal cancer: a pilot study

Background

4′-[Methyl-11C] thiothymidine (4DST) has been introduced as a new cell proliferation imaging PET tracer that incorporates into DNA directly. The aim of this prospective study was to evaluate the efficacy of 4DST PET/CT for predicting responses to neoadjuvant therapy in patients with esophageal cancer comparing with FDG PET/CT.

Methods

Twenty-six patients who had pre- and post-therapeutic 4DST and FDG PET/CT and underwent esophagectomy following neoadjuvant therapy were used for the analysis. Based on pathological findings, patients were divided into two groups: non-responders and responders. The maximum standardized uptake value (SUVmax), metabolic tumor volume, total lesion glycolysis, and total lesion proliferation of the primary lesion were measured for FDG and 4DST PET.

Results

The pathological diagnosis revealed 16 responders and 10 non-responders. Non-responders showed significantly higher 4DST post-therapeutic SUVmax (_postSUVmax) than responders, whereas FDG _postSUVmax showed no statistically significant difference (non-responders vs. responders: 4DST, 6.7 vs. 3.3, p = 0.001; FDG, 6.1 vs. 4.5, p = 0.11). Responders showed a greater reduction in percentage changes of 4DST and FDG SUVmax (ΔSUVmax) from baseline to post-therapeutic PET (non-responders vs. responders: 4DST, − 2.9% vs. − 56.7%, p < 0.001; FDG, − 36.3% vs. − 72.6%, p < 0.001). In ROC analysis, ΔSUVmax and _postSUVmax with 4DST provided great diagnostic performance for predicting responses (area under the curve: 4DST ΔSUVmax = 0.92, 4DST _postSUVmax = 0.88).

Conclusions

4DST PET/CT has a great potential for predicting pathologic response to neoadjuvant therapy in patients with esophageal cancer; it may be slightly superior to that with FDG PET/CT.

Impact of PET reconstruction protocols on quantification of lesions that fulfil the PERCIST lesion inclusion criteria

BACKGROUND

The aim of this study was to compare liver and oncologic lesion standardized uptake values (SUV) obtained through two different reconstruction protocols, GE's newest clinical lesion detection protocol (Q.Clear) and the EANM Research Ltd (EARL) harmonization protocol, and to assess the clinical relevance of potential differences and possible implications for daily clinical practice using the PERCIST lesional inclusion criteria. NEMA phantom recovery coefficients (RC) and SUV normalized for lean body mass (LBM), referred to as SUV normalized for LBM (SUL), of liver and lesion volumes of interest were compared between the two reconstruction protocols. Head-to-toe PET/CT examinations and raw data from 64 patients were retrospectively retrieved. PET image reconstruction was carried out twice: once optimized for quantification, complying with EARL accreditation requirements, and once optimized for lesion detection, according to GE's Q.Clear reconstruction settings.

RESULTS

The two reconstruction protocols showed different NEMA phantom RC values for different sphere sizes. Q.Clear values were always highest and exceeded the EARL accreditation maximum for smaller spheres. Comparison of liver SUL_mean showed a statistically significant but clinically irrelevant difference between both protocols. Comparison of lesion SUL_peak and SUL_max showed a statistically significant, and clinically relevant, difference of 1.64 and 4.57, respectively.

CONCLUSIONS

For treatment response assessment using PERCIST criteria, the harmonization reconstruction protocol should be used as the lesion detection reconstruction protocol using resolution recovery systematically overestimates true SUL values.

18F-FDG-PET/CT features of primary tumours for predicting the risk of recurrence in thyroid cancer after total thyroidectomy: potential usefulness of combination of the SUV-related, volumetric, and heterogeneous texture parameters

OBJECTIVE:

This retrospective study examined whether the primary tumour 18F-FDG uptake features could predict the high-risk of recurrence in differentiated thyroid cancer (DTC) patients.

METHODS:

The enrolled 114 DTC patients underwent preoperative ¹⁸F-FDG-PET/CT. SUVmax, SUVmean, metabolic tumour volume (MTV), total lesion glycolysis (TLG) and 6 texture parameters were obtained. Because the texture features can be confounded by the tumour volume effects, ¹⁸F-FDG-avid tumour patients were divided into two groups (tumours with MTV ≤ 10.0 cm³ and >10.0 cm³). Diagnostic performance for predicting the high-risk was evaluated by the area under the curve (AUC) by the ROC curve analysis.

RESULTS:

Eighty eight ¹⁸F-FDG-avid tumours revealed more advanced-risk classification (p = 0.015 → 0.02) than 26 ¹⁸F-FDG-nonavid tumours, which yielded no high-risk patients. In the 44 MTV > 10.0 cm^{3 18}F-FDG-avid tumour patients, 8 high-risk patients revealed significantly higher SUVmax, SUVmean, MTV, TLG, intensity variability and size-zone variability, and lower zone percentage than 36 non-high-risk patients (p < 0.001-0.016). Their AUC (diagnostic accuracy) ranged between 0.77 (66%) and 0.92 (91%). When each parameter was scored as 0 (negative for high-risk) or 1 (positive for high-risk) according to each threshold criterion, and the 7 parameter summed score ≥5 was defined as high-risk, the accuracy was 93.2% (AUC: 0.98) in the MTV > 10.0 cm^{3 18}F-FDG-avid tumour patients.

CONCLUSION:

For primary MTV > 10.0 cm^{3 18}F-FDG-avid DTCs, the combined use of SUV-related, volumetric, and texture parameters may be more useful to identify high-risk patients than the individual parameters.

ADVANCES IN KNOWLEDGE:

Combined use of SUV-related, volumetric, and texture parameters may be useful to identify high-risk DTC patients.

An effective computer aided diagnosis model for pancreas cancer on PET/CT images

Background and objective: Pancreas cancer is a digestive tract tumor with high malignancy, which is difficult for diagnosis and treatment at early time. To this end, this paper proposes a computer aided diagnosis (CAD) model for pancreas cancer on Positron Emission Tomography/Computed Tomography (PET/CT) images.

METHODS

There are three essential steps in the proposed CAD model, including (1) pancreas segmentation, (2) feature extraction and selection, (3) classifier design, respectively. First, pancreas segmentation is performed using simple linear iterative clustering (SLIC) on CT pseudo-color images generated by the gray interval mapping (GIP) method. Second, dual threshold principal component analysis (DT-PCA) is developed to select the most beneficial feature combination, which not only considers principal features but also integrates some non-principal features into a new polar angle representation. Finally, a hybrid feedback-support vector machine-random forest (HFB-SVM-RF) model is designed to identify normal pancreas or pancreas cancer and the key is to use 8 types of SVMs to establish the decision trees of RF.

RESULTS

The proposed CAD model is tested on 80 cases of PET/CT data (from General Hospital of Shenyang Military Area Command) and achieves the average pancreas cancer identification accuracy of 96.47%, sensibility of 95.23% and specificity of 97.51%, respectively. In addition, the proposed pancreas segmentation method is also evaluated using a public dataset with 82 3D CT scans from the National Institutes of Health (NIH) Clinical Center and its performance is found to surpass other methods, with a mean Dice coefficient of 78.9% and Jaccard index of 65.4%.

CONCLUSIONS

Collectively, contrast experiments in 10-fold cross validation demonstrate the efficiency and accuracy of the proposed CAD model as well as its performance advantages as compared with related methods.

Accurate FDG PET tumor segmentation using the peritumoral halo layer method: a study in patients with esophageal squamous cell carcinoma

Background

In a previous study, FDG PET tumor segmentation (SegPHL) using the peritumoral halo layer (PHL) was more reliable than fixed threshold methods in patients with thyroid cancer. We performed this study to validate the reliability and accuracy of the PHL method in patients with esophageal squamous cell carcinomas (ESCCs), which can be larger and more heterogeneous than thyroid cancers.

Methods

A total of 121 ESCC patients (FDG avid = 85 (70.2%); FDG non-avid = 36 (29.8%)) were enrolled in this study. In FDG avid ESCCs, metabolic tumor length (ML) using SegPHL (ML_PHL), fixed SUV 2.5 threshold (ML_2.5), and fixed 40% of maximum SUV (SUVmax) (ML_40%) were measured. Regression and Bland-Altman analyses were performed to evaluate associations between ML, endoscopic tumor length (EL), and pathologic tumor length (PL). A comparison test was performed to evaluate the absolute difference between ML and PL. Correlation with tumor threshold determined by the PHL method (PHL tumor threshold) and SUVmax was evaluated.

Results

ML_PHL, ML_2.5, and ML_40% correlated well with EL (R² = 0.6464, 0.5789, 0.3321, respectively; p < 0.001) and PL (R² = 0.8778, 0.8365, 0.6266, respectively; p < 0.001). However, ML_2.5 and ML_40% showed significant proportional error with regard to PL; there was no significant error between ML_PHL and PL. ML_PHL showed the smallest standard deviation on Bland-Altman analyses. The absolute differences between ML and PL were significantly smaller for ML_PHL and ML_40% than for ML_2.5 (p < 0.0001). The PHL tumor threshold showed an inverse correlation with SUVmax (σ = − 0.923, p < 0.0001).

Conclusions

SegPHL was more accurate than fixed threshold methods in ESCC. The PHL tumor threshold was adjusted according to SUVmax of ESCC.