Whole-body Metabolic Tumor Volume Research Articles

Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer

Objectiveto build a risk stratification by incorporating PET/CT-based deep learning features and whole-body metabolic tumor volume (MTVwb), which was to make predictions about overall survival (OS) and progression-free survival (PFS) for those with non-small cell lung cancer (NSCLC) as a complement to the TNM staging. Materials and MethodsThe study enrolled 590 patients with NSCLC (413 for training and 177 for testing). Features were extracted by employing a convolutional neural network. The combined risk stratification (CRS) was constructed by the selected features and MTVwb, which were contrasted and integrated with TNM staging. In the testing set, the above was verified. ResultsMultivariate analysis revealed that CRS was an independent predictor of OS and PFS. C-indexes of the CRS demonstrated statistically significant increases in comparison to TNM staging, excepting predicting OS in the testing set (for OS, C-index = 0.71 vs. 0.691 in the training set and 0.73 vs. 0.736 in the testing set; for PFS, C-index = 0.702 vs. 0.686 in the training set and 0.732 vs. 0.71 in the testing set). The nomogram that combined CRS with TNM staging demonstrated the most superior model performance in the training and testing sets (C-index = 0.741 and 0.771). ConclusionThe addition of CRS improves TNM staging's predictive power and shows potential as a useful tool to support physicians in making treatment decisions.

Predictive significance of pretreatment 18F-FDG PET volumetric parameters on survival outcomes in pediatric patients with locally advanced undifferentiated nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a rare pediatric cancer. Most children are first diagnosed with advanced locoregional disease. Identification of patients at higher risk of treatment failure is crucial as they may benefit from more aggressive initial treatment approaches. 18Fluorine-labeled fluoro-2-deoxyglucose positron emission tomography (18F-FDG PET) has shown promise as a prognostic tool for predicting outcomes. Retrospective study of pediatric patients with locally advanced undifferentiated NPC who underwent 18F-FDG PET/CT prior to intial treatment. Predictive significance of metabolic PET parameters on survival outcomes were estimated. Thirty-two children were included, age range was 7.1-18years at the time of diagnosis. The median follow-up duration was 46.1months. Three patients (9.4%) were classified as AJCC stage IIb, 13 patients (40.6%) as stage IIIa, eight patients (25%) as stage IIIb, and eight patients (25%) as stage IVa. Our findings revealed that high whole-body metabolic tumor volume at the threshold of hepatic reference SUVmean (WB-MTV-HR) (>135mL) was associated with significantly lower event-free survival (EFS) compared to the low WB-MTV-HR group (≤135mL) (3-year EFS: 50%±18% vs. 82%±8%; p=.015). Additionally, the 3-year overall survival (OS) rates differed significantly between the high whole-body metabolic tumor volume at the threshold of an SUV of 2.5 isocontour (WB-MTV-2.5) group (MTV >74mL) and the low WB-MTV-2.5 group (MTV ≤74mL) (63%±18% vs. 100%; p=.021). Our study suggests that WB-MTV parameters could serve as significant prognostic factors for disease progression in pediatric patients with locally advanced undifferentiated NPC. However, further prospective studies with larger sample sizes are needed to validate these findings.

Artificial intelligence–based, volumetric assessment of the bone marrow metabolic activity in [18F]FDG PET/CT predicts survival in multiple myeloma

PurposeMultiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [18F]FDG PET/CT can provide prognostic information in MM, but it is hampered by issues regarding standardization of scan interpretation. Our group has recently demonstrated the feasibility of automated, volumetric assessment of bone marrow (BM) metabolic activity on PET/CT using a novel artificial intelligence (AI)–based tool. Accordingly, the aim of the current study is to investigate the prognostic role of whole-body calculations of BM metabolism in patients with newly diagnosed MM using this AI tool.Materials and methodsForty-four, previously untreated MM patients underwent whole-body [18F]FDG PET/CT. Automated PET/CT image segmentation and volumetric quantification of BM metabolism were based on an initial CT-based segmentation of the skeleton, its transfer to the standardized uptake value (SUV) PET images, subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, ten different uptake thresholds (AI approaches), based on reference organs or absolute SUV values, were applied for definition of pathological tracer uptake and subsequent calculation of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Correlation analysis was performed between the automated PET values and histopathological results of the BM as well as patients’ progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic (ROC) curve analysis was used to investigate the discrimination performance of MTV and TLG for prediction of 2-year PFS. The prognostic performance of the new Italian Myeloma criteria for PET Use (IMPeTUs) was also investigated.ResultsMedian follow-up [95% CI] of the patient cohort was 110 months [105–123 months]. AI-based BM segmentation and calculation of MTV and TLG were feasible in all patients. A significant, positive, moderate correlation was observed between the automated quantitative whole-body PET/CT parameters, MTV and TLG, and BM plasma cell infiltration for all ten [18F]FDG uptake thresholds. With regard to PFS, univariable analysis for both MTV and TLG predicted patient outcome reasonably well for all AI approaches. Adjusting for cytogenetic abnormalities and BM plasma cell infiltration rate, multivariable analysis also showed prognostic significance for high MTV, which defined pathological [18F]FDG uptake in the BM via the liver. In terms of OS, univariable and multivariable analysis showed that whole-body MTV, again mainly using liver uptake as reference, was significantly associated with shorter survival. In line with these findings, ROC curve analysis showed that MTV and TLG, assessed using liver-based cut-offs, could predict 2-year PFS rates. The application of IMPeTUs showed that the number of focal hypermetabolic BM lesions and extramedullary disease had an adverse effect on PFS.ConclusionsThe AI-based, whole-body calculations of BM metabolism via the parameters MTV and TLG not only correlate with the degree of BM plasma cell infiltration, but also predict patient survival in MM. In particular, the parameter MTV, using the liver uptake as reference for BM segmentation, provides solid prognostic information for disease progression. In addition to highlighting the prognostic significance of automated, global volumetric estimation of metabolic tumor burden, these data open up new perspectives towards solving the complex problem of interpreting PET scans in MM with a simple, fast, and robust method that is not affected by operator-dependent interventions.

Predicting epithelial ovarian cancer prognosis: correlation of posttreatment 18F-fluorodeoxyglucose positron emission tomography-computed tomography metabolic parameters, serum carbohydrate antigen, and human epididymis protein levels with overall survival.

Identifying reliable prognostic indicators can aid in improving patient care. The aim of this study was to establish the association of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) whole-body metabolic parameters, serum carbohydrate antigen 125 (CA125), and human epididymis protein 4 (HE4) with overall survival (OS) in patients with epithelial ovarian cancer (EOC) after surgery combined with platinum-based chemotherapy. From May 2014 to May 2019, a total of 79 patients with EOC who underwent posttreatment 18F-FDG PET/CT in the First Affiliated Hospital of Chongqing Medical University were included. Clinical data and laboratory indicators were obtained. The whole-body maximum standardized uptake value (WBSUVmax), whole-body metabolic tumor volume (WBMTV), and whole-body total lesion glycolysis (WBTLG) were measured and calculated on 18F-FDG PET/CT. The follow-up was conducted until February 2023, and the endpoint was death from any cause. Pearson correlation analysis, Kaplan-Meier, and Cox proportional regression were used in this study. The PET-positive (PET-P) patients had significantly decreased OS based on either Kaplan-Meier survival analysis (P<0.001) or univariate Cox regression analysis [hazard ratio (HR) =40.177, 95% confidence interval (CI): 2.690-600.134; P=0.007]. "Ln" is a logarithmic transformation with a base of "e" (natural logarithm). LnWBMTV, lnWBTLG, and therapy after PET were independent predictors of OS in a cohort of 63 PET-P patients. The difference in OS between groups sorted by the median WBMTV (4.16; P<0.001) and WBTLG (14.71; P<0.001) was statistically significant. There were statistically significant differences in CA125 and HE4 levels between patients in the PET-P and PET-negative (PET-N) groups (P<0.001). In the PET-P patient cohort, serum HE4 levels were substantially correlated with WBMTV and WBTLG. Kaplan-Meier survival analysis suggested a reduction in OS after treatment in patients with EOC positive for CA125, HE4, and PET (P<0.001). Post-PET/CT treatment strategy, WBMTV, and WBTLG demonstrated significant prognostic utility in predicting posttreatment OS in patients with EOC. Patients who tested positive for both tumor markers CA125 and HE4 and had a positive PET scan demonstrated a significantly poorer prognosis in terms of posttreatment OS.

Optimization of Metabolic Tumor Volume as a Prognostic Marker in CAR T-Cell Therapy for Aggressive Large B-cell NHL

BackgroundCD19-targeted chimeric antigen receptor (CAR) T-cell therapy has become a standard of care in relapsed/refractory (R/R) aggressive large B-cell non-Hodgkin lymphomas (B-NHL) though the majority of recipients do not receive durable disease benefit, prompting the need to better define risk factors for relapse/progression. ObjectivesWe performed a single-center, retrospective analysis of patients treated with commercial CAR T-cell therapy to evaluate the impact of tumor burden, as measured by whole-body metabolic tumor volume (MTV) from 18F fluorodeoxyglucose PET imaging, on treatment outcomes. Study DesignSixty-one patients treated with CAR T-cell therapy for R/R B-NHL between May 2016 and November 2021 were included. ResultsUsing a receiver operating characteristic curve-based MTV optimization cutoff of 450 mL, 1-year progression-free survival (PFS) was 22% for high MTV versus 54% for low MTV (P < .01), and 1-year overall survival (OS) was 37% and 73%, respectively (P = .01). In a subset of 46 patients, residual MTV of less than 106 mL at the day 30 (D30) disease assessment was associated with significantly improved outcomes (1-year OS 85% vs. 13%, P < .01). Incorporation of pretreatment MTV to the International Prognostic Index (IPI) scoring system significantly distinguished 2-year PFS and OS outcomes by 3 risk groups. ConclusionsOur findings suggest that both pretreatment and D30 MTV are predictive of outcomes among R/R B-NHL patients treated with CAR T-cell therapy. These data indicate that efforts to reduce pretreatment tumor burden may improve longitudinal clinical outcomes. Furthermore, D30 postinfusion MTV quantification may aid clinicians in optimally identifying patients at high-risk for progression, and in whom closer disease monitoring should be considered. MTV also adds prognostic value to patients with high-risk IPI and holds promise for incorporation in novel risk scoring systems which can identify patients prior to CAR T-cell therapy at highest risk of adverse outcomes.

Circulating Tumor DNA in Head and Neck Squamous Cell Carcinoma: Association with Metabolic Tumor Burden Determined with FDG-PET/CT.

The detection of circulating tumor DNA (ctDNA) with next-generation sequencing (NGS) in venous blood is a promising tool for the genomic profiling of head and neck squamous cell carcinoma (HNSCC). The association between ctDNA findings and metabolic tumor burden detected with FDG-PET/CT imaging is of particular interest for developing prognostic and predictive algorithms in HNSCC. Twenty-six prospectively enrolled HNSCC patients were eligible for further analysis. All patients underwent tumor tissue and venous liquid biopsy sampling and FDG-PET/CT before definitive oncologic treatment. An NGS-based commercial panel was used for a genomic analysis of the samples. Maximum variant allele frequency (VAF) in blood correlated positively with whole-body (WB) metabolic tumor volume (MTV) and total lesion glycolysis (TLG) (r = 0.510, p = 0.008 and r = 0.584, p = 0.002, respectively). A positive liquid biopsy was associated with high WB-TLG using VAF ≥ 1.00% or ≥5.00% as a cut-off value (p = 0.006 or p = 0.003, respectively). Additionally, ctDNA detection was associated with WB-TLG when only concordant variants detected in both ctDNA and tissue samples were considered. A high metabolic tumor burden based on FDG imaging is associated with a positive liquid biopsy and high maximum VAF. Our findings suggest a complementary role of metabolic and genomic signatures in the pre-treatment evaluation of HNSCC.

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma

Purpose[18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients.Materials and methodsWhole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1–6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian × 1.1 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 2: liver SUVmedian × 1.5 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 3: liver SUVmedian × 2 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients.ResultsBM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of β2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5.ConclusionsThe automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts.

Whole-body tumor segmentation from PET/CT images using a two-stage cascaded neural network with camouflaged object detection mechanisms.

Whole-body Metabolic Tumor Volume (MTVwb) is an independent prognostic factor for overall survival in lung cancer patients. Automatic segmentation methods have been proposed for MTV calculation. Nevertheless, most of existing methods for patients with lung cancer only segment tumors in the thoracic region. In this paper, we present a Two-Stage cascaded neural network integrated with Camouflaged Object Detection mEchanisms (TS-Code-Net) for automatic segmenting tumors from whole-body PET/CTimages. Firstly, tumors are detected from the Maximum Intensity Projection (MIP) images of PET/CT scans, and tumors' approximate localizations along z-axis are identified. Secondly, the segmentations are performed on PET/CT slices that contain tumors identified by the first step. Camouflaged object detection mechanisms are utilized to distinguish the tumors from their surrounding regions that have similar Standard Uptake Values (SUV) and texture appearance. Finally, the TS-Code-Net is trained by minimizing the total loss that incorporates the segmentation accuracy loss and the class imbalanceloss. The performance of the TS-Code-Net is tested on a whole-body PET/CT image data-set including 480 Non-Small Cell Lung Cancer (NSCLC) patients with five-fold cross-validation using image segmentation metrics. Our method achieves 0.70, 0.76, and 0.70, for Dice, Sensitivity and Precision, respectively, which demonstrates the superiority of the TS-Code-Net over several existing methods related to metastatic lung cancer segmentation from whole-body PET/CTimages. The proposed TS-Code-Net is effective for whole-body tumor segmentation of PET/CT images. Codes for TS-Code-Net are available at: https://github.com/zyj19/TS-Code-Net.

Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor.

Endocrine therapy (ET) with or without CDK4/6 inhibitors is the primary treatment choice for patients with estrogen receptor (ER)-positive and HER2-negative subtype of metastatic breast cancer (MBC). We examined the metabolic parameters identified using 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in terms of sensitivity, since no predictive factors exist. We included 136 patients with MBC treated with ET alone (n=107) or combined with CDK4/6 inhibitor (n=29) and examined using FDG-PET before treatment began. The highest maximum value of the standard uptake value (SUVmax), whole-body metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Progression-free survival (PFS) was significantly longer in patients with low levels of MTV, TLG, and SUVmax than those with higher levels (median PFS 49.5 vs. 20.7 months, p=0.001 for MTV, 49.5 vs. 20.7 months, p=0.0016 for TLG, 37.0 vs. 20.7 months, p=0.012 for SUVmax). Multivariable analysis revealed that TLG (hazard ratio=6.383, 95% confidence interval=1.167-34.913, p=0.033) was independently and significantly associated with PFS. The relationship between TLG levels and PFS was significant in patients treated with ET with (p=0.0054) and without (p=0.0188) CDK4/6 inhibitor. TLG at baseline was a significant predictor for sensitivity to ET alone or combined with CDK4/6 inhibitor. These data may be useful to identify patients that would benefit from ET.

Relation of whole-body metabolic tumor volume and total lesion glycolysis on fluorodeoxyglucose PET/computed tomography with clinical and laboratory parameters in newly diagnosed multiple myeloma.

This study aims to evaluate the relationships of metabolic fluorodeoxyglucose PET/computed tomography (FDG PET/CT) parameters such as whole-body metabolic tumor volume (WB MTV), WB-total lesion glycolysis (TLG), and bone marrow (BM)-mean standard uptake value (SUVmean) with clinical stage and other prognostic biomarkers in newly diagnosed multiple myeloma (MM) patients. Patients who underwent pretreatment PET/CT with the diagnosis of MM were evaluated retrospectively. The number of focal lesions, WB MTV, WB TLG, and BM SUVmean values were measured on FDG PET/CT images. Clinical stages and prognostic laboratory parameters were recorded the pretreatment period. WB MTV and WB TLG values were significantly higher in patients with more than three focal lesions on FDG PET/CT scan (all P < 0.001). According to the Revised International Staging System (R-ISS), all WB MTV, WB TLG, and BM SUVmean values are significantly higher in patients with stage 3 disease than in stages 1-2 ( P = 0.027, P = 0.019, P = 0.001, respectively). Serum creatinine level is positively correlated with WB MTV, WB TLG, and BM SUVmean values ( P = 0.020, P = 0.004, P < 0.001, respectively). In addition, the β2 microglobulin level, an essential biochemical prognostic parameter, was positively correlated with the BM SUVmean value ( P = 0.013). The BM SUVmean, WB MTV, and WB TLG values, which reflect FDG avid WB tumor burden, are associated with prognostic biomarkers and R-ISS stage in newly diagnosed MM patients. It contributes to the identification of high-risk patients at the pretreatment staging.

Prognostic usefulness of clinical features and pretreatment 18F-FDG PET/CT metabolic parameters in patients with angiosarcoma.

To investigate the prognostic value of clinical features and metabolic parameters in pretreatment 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/X-ray computed tomography (PET/CT) scans of patients with angiosarcoma, a rare neoplasm that has not been well characterized. In this retrospective study, 19 patients with a histopathologically confirmed diagnosis of angiosarcoma who had undergone pretreatment 18F-FDG PET/CT scans were enrolled. We recorded the age at presentation, sex, underlying diseases, sites of primary tumors, Karnofsky Performance Status (KPS) score, Eastern Cooperative Oncology Group (ECOG) score, time from onset to diagnosis, laboratory examinations, sites and sizes of primary tumors, treatment modalities, histologic features and American Joint Committee on Cancer (AJCC) stage, maximum standardized uptake value (SUVmax), average SUV (SUVavg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of primary tumors and the whole body. Univariate and multivariate survival analyses for overall survival were performed according to the metabolic parameters and other clinical variables. Patients ranged in age from 27 to 79 years (median: 59 years) with different angiosarcoma types covering all tumor grades and subtypes. Seven (7/19) patients had anemia of varying degrees of severity. Lymph node metastases (n=10) and/or distant metastases (n=11) of angiosarcoma were common. Bone or bone marrow (10/19) and lung (8/19) were the most common distant metastatic organs. Patients with bone metastases, low hemoglobin levels and high ferritin levels had significantly poorer overall survival than those with non-bone metastases, normal hemoglobin levels and normal ferritin levels by the log-rank test, with P values of 0.027, 0.030 and 0.015, respectively. Patients with multiple organ metastases had significantly poorer overall survival than those with single organ metastasis (log-rank P=0.008). In multivariate survival analysis, only whole-body metabolic tumor volume using SUVmax cut-off value of 2.5 (wMTV2.5) was a significant independent prognostic factor. For wMTV2.5, 870.3 cm3 was the best cut-off point to discriminate between a good and poor prognosis (log-rank P=0.01). The systemic 18F-FDG PET/CT with high sensitivity and specificity has significant advantages in the evaluation of angiosarcoma, particularly in detecting occult metastases. Bone metastases on 18F-FDG PET/CT, low hemoglobin levels and high ferritin levels were all associated with a poorer prognosis. MTV2.5 of the whole body is a significant independent metabolic prognostic factor for overall survival in patients with angiosarcoma.

Validation of Convolutional Neural Networks for Fast Determination of Whole-Body Metabolic Tumor Burden in Pediatric Lymphoma.

18F-FDG PET/CT quantification of whole-body tumor burden in lymphoma is not routinely performed because of the lack of fast methods. Although the semiautomatic method is fast, it is not fast enough to quantify tumor burden in daily clinical practice. Our purpose was to evaluate the performance of convolutional neural network (CNN) software in localizing neoplastic lesions in whole-body 18F-FDG PET/CT images of pediatric lymphoma patients. Methods: The retrospective image dataset, derived from the data pool of the International Atomic Energy Agency (coordinated research project E12017), included 102 baseline staging 18F-FDG PET/CT studies of pediatric lymphoma patients (mean age, 11 y). The images were quantified to determine the whole-body tumor burden (whole-body metabolic tumor volume [wbMTV] and whole-body total lesion glycolysis [wbTLG]) using semiautomatic software and CNN-based software. Both were displayed as semiautomatic wbMTV and wbTLG and as CNN wbMTV and wbTLG. The intraclass correlation coefficient (ICC) was applied to evaluate concordance between the CNN-based software and the semiautomatic software. Results: Twenty-six patients were excluded from the analysis because the software was unable to perform calculations for them. In the remaining 76 patients, CNN and semiautomatic wbMTV tumor burden metrics correlated strongly (ICC, 0.993; 95% CI, 0.989 - 0.996; P < 0.0001), as did CNN and semiautomatic wbTLG (ICC, 0.999; 95% CI, 0.998-0.999; P < 0.0001). However, the time spent calculating these metrics was significantly (<0.0001) less by CNN (mean, 19 s; range, 11-50 s) than by the semiautomatic method (mean, 21.6 min; range, 3.2-62.1 min), especially in patients with advanced disease. Conclusion: Determining whole-body tumor burden in pediatric lymphoma patients using CNN is fast and feasible in clinical practice.

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.

Developing a clinical and PET/CT volumetric prognostic index for risk assessment and management of NSCLC patients after initial therapy.

Currently, individual clinical prognostic variables are used sequentially with risk-stratification after TNM staging in clinical practice for the prognostic assessment of patients with NSCLC, which is not effective for estimating the collective impact of multiple individual variables on patient outcomes. Here, we developed a clinical and PET/CT volumetric prognostic (CPVP) index that integrates the prognostic power of multiple clinical variables and metabolic tumor volume from baseline FDG-PET, for use immediately after definitive therapy. This retrospective cohort study included 998 NSCLC patients diagnosed between 2004 and 2017, randomly assigned to two cohorts for modeling the CPVP index using Cox regression models examining overall survival (OS) and subsequent validation. The CPVP index generated from the model cohort included pretreatment variables (whole-body metabolic tumor volume [MTVwb], clinical TNM stage, tumor histology, performance status, age, race, gender, smoking history) and treatment type. A clinical variable (CV) index without MTVwb and PET/CT volumetric prognostic (PVP) index without clinical variables were also generated for comparison. In the validation cohort, univariate Cox modeling showed a significant association of the index with overall survival (OS; Hazard Ratio [HR] 3.14; 95% confidence interval [95% CI] =2.71 to 3.65, p < 0.001). Multivariate Cox regression analysis demonstrated a significant association of the index with OS (HR = 3.13, 95% CI =2.66 to 3.67, p < 0.001). The index showed greater prognostic power (C-statistic = 0.72) than any of its independent variables including clinical TNM stage (C-statistic ranged from 0.50 to 0.69, all p < 0.003), CV index (C-statistic = 0.68, p < 0.001) and PVP index (C-statistic = 0.70, p = 0.006). The CPVP index for NSCLC patients has moderately strong prognostic power and is more prognostic than its individual prognostic variables and other indices. It provides a practical tool for quantitative prognostic assessment after initial treatment and therefore may be helpful for the development of individualized treatment and monitoring strategy for NSCLC patients.

Predictive Value of Baseline [18F]FDG PET/CT for Response to Systemic Therapy in Patients with Advanced Melanoma.

Background/Aim: To evaluate the association between baseline [18F]FDG-PET/CT tumor burden parameters and disease progression rate after first-line target therapy or immunotherapy in advanced melanoma patients. Materials and Methods: Forty four melanoma patients, who underwent [18F]FDG-PET/CT before first-line target therapy (28/44) or immunotherapy (16/44), were retrospectively analyzed. Whole-body and per-district metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated. Therapy response was assessed according to RECIST 1.1 on CT scan at 3 (early) and 12 (late) months. PET parameters were compared using the Mann–Whitney test. Optimal cut-offs for predicting progression were defined using the ROC curve. PFS and OS were studied using Kaplan–Meier analysis. Results: Median (IQR) MTVwb and TLGwb were 13.1 mL and 72.4, respectively. Non-responder patients were 38/44, 26/28 and 12/16 at early evaluation, and 33/44, 21/28 and 12/16 at late evaluation in the whole-cohort, target, and immunotherapy subgroup, respectively. At late evaluation, MTVbone and TLGbone were higher in non-responders compared to responder patients (all p < 0.037) in the whole-cohort and target subgroup and MTVwb and TLGwb (all p < 0.022) in target subgroup. No significant differences were found for the immunotherapy subgroup. No metabolic parameters were able to predict PFS. Controversially, MTVlfn, TLGlfn, MTVsoft + lfn, TLGsoft + lfn, MTVwb and TLGwb were significantly associated (all p < 0.05) with OS in both the whole-cohort and target therapy subgroup. Conclusions: Higher values of whole-body and bone metabolic parameters were correlated with poorer outcome, while higher values of whole-body, lymph node and soft tissue metabolic parameters were correlated with OS.

Associations of whole-body 18F-FDG PET/CT parameters and SCC-Ag level with overall survival in patients with cervical cancer.

To explore the whole-body metabolic tumour volume (WBMTV), whole-body total lesion glycolysis (WBTLG) and tumour whole-body maximum standardised uptake value (WBSUVmax) of post-treatment 18F-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) in predicting the overall survival (OS) in patients with cervical squamous cell carcinoma (SCC). The clinical data of 74 patients with cervical SCC who received 18F-FDG PET/CT were retrospectively analysed. WBMTV, WBTLG and WBSUVmax, as well as the serum SCC-Ag level, were measured. The Kaplan-Meier method and Cox regression were used to analyse the relationships of PET/CT parameters with OS. The risk of death was 13.942-fold greater in the PET-positive group than in the PET-negative group (P < 0.001). In the PET-positive group, univariate analysis showed that OS was significantly correlated with WBMTV and WBTLG; it was not correlated with WBSUVmax, SCC-Ag, age, pathological stage or treatment after PET (P > 0.05). Patients with positive PET findings were divided into two groups according to the median of WBMTV or WBTLG; there was a significant difference in OS between the two groups. The risk of death in patients with positive PET imaging findings and high SCC-Ag level was 18.356-fold greater than in patients with negative PET imaging findings (P < 0.001). WBMTV and WBTLG have important prognostic value in the prediction of OS in post-treatment patients with cervical SCC. OS was significantly decreased in patients who had both positive PET imaging findings and high SCC-Ag level.

Evaluation of patients with advanced epithelial ovarian cancer before primary treatment: correlation between tumour burden assessed by [18F]FDG PET/CT volumetric parameters and tumour markers HE4 and CA125.

Accurate assessment of disease extent is required to select the best primary treatment for advanced epithelial ovarian cancer patients. Estimation of tumour burden is challenging and it is usually performed by means of a surgical procedure. Imaging techniques and tumour markers can help to estimate tumour burden non-invasively. 2-[18F]FDG PET/CT allows the evaluation of the whole-body disease. This study aimed to correlate HE4 and CA125 serum concentrations with tumour burden evaluated by volumetric 2-[18F]FDG PET/CT parameters in advanced high-grade epithelial ovarian cancer. We included 66 patients who underwent 2-[18F]FDG PET/CT and serum tumour markers determination before primary treatment. Volumes of interest were delimited in every pathological uptake. Whole-body metabolic tumour volume (wb_MTV) and total lesion glycolysis (wb_TLG) were calculated summing up every VOI's MTV value. SUVmax thresholds were set at 40% (MTV40 and TLG40) and 50% (MTV50 and TLG50). In addition, four VOI subgroups were defined: peritoneal carcinomatosis, retroperitoneal nodes, supradiaphragmatic nodes, and distant metastases. MTV and TLG were calculated for each group by adding up the corresponding MTV values. TLG was calculated likewise. wb_MTV and wb_TLG were found to be significantly correlated with serum CA125 and HE4 concentrations. The strongest correlation was observed between HE4 and wb_MTV40 (r = 0.62, p < 0.001). Pearson's correlation coefficients between peritoneal carcinomatosis MTV40 and tumour markers were 0.61 (p < 0.0001) and 0.29 (p = 0.02) for HE4 and CA125 respectively. None of these tumour markers showed a positive correlation with tumour load outside the abdominal cavity assessed by volumetric parameters. HE4 performs better than CA125 to predict metabolic tumour burden in high-grade epithelial ovarian cancer before primary treatment. 2-[18F]FDG PET/CT volumetric parameters arise as feasible tools for the objective assessment of tumour load and its anatomical distribution. These results support the usefulness of HE4 and PET/CT to improve the stratification of these patients in clinical practice. • In patients with high-grade advanced ovarian epithelial carcinoma, both CA125 and HE4 correlate to whole-body tumour burden assessed by PET/CT before primary treatment. • HE4 estimates peritoneal disease much better than CA125. • PET/CT volumetric parameters arise as feasible tools for the objective assessment of tumour load and its anatomical distribution.

Immune Checkpoint Inhibitors in Advanced NSCLC: [18F]FDG PET/CT as a Troubleshooter in Treatment Response.

Introduction: The aim of this study was to investigate whether [18F]FDG PET/CT-derived semi-quantitative parameters can predict immunotherapy treatment response in non-small cell lung cancer (NSCLC) patients. Secondly, immune-related adverse events (irAEs) and lymphoid cell-rich organs activation were evaluated. Materials and Methods: Twenty-eight patients who underwent [18F]FDG PET/CT scans before and at first restaging therapy with immuno-checkpoint inhibitors (ICIs) were retrospectively analyzed. PET-based semi-quantitative parameters extracted from both scans were respectively: SUVmax and SUVpeak of the target lesion, whole-body metabolic tumor volume (MTVWB), and whole-body total lesion glycolysis (TLGWB), as well as their interval changes (ΔSUVmaxTL, ΔSUVpeakTL, ΔMTVWB, ΔTLGWB). These PET-derived parameters were correlated to controlled disease (CD) assessed by RECIST 1.1. IrAEs, if present, were also described and correlated with clinical benefit (CB). SUVmax of the spleen and bone marrow at restaging scans were also correlated to CB. Results: The CD was achieved in 54% of patients. Out of 28 eligible patients, 13 (46%) experienced progressive disease (PD), 7 showed SD, 7 had PR, and only in one patient CR was achieved. ΔSUVmaxTL (p = 0.002) and ΔSUVpeakTL (p < 0.001) as well as ΔMTVWB (p < 0.001) and ΔTLGWB (p < 0.005) were significantly associated with PD vs. non-PD. IrAEs and lymphoid cell-rich organs activation did not correlate with CB. Conclusions: [18F]FDG PET/CT by using interval changes of PET-derived semi-quantitative parameters could represent a reliable tool in immunotherapy treatment response evaluation in NSCLC patients.

Development and validation of a prediction model based on the organ-based metabolic tumor volume on FDG-PET in patients with differentiated thyroid carcinoma.

Although patients with differentiated thyroid cancer (DTC) generally have a good prognosis, patients with a large metabolic tumor volume (MTV) on FDG-PET may experience poor clinical courses. We measured organ-based MTVs and tested its prognostic performance in comparison to conventional MTV (cMTV). We retrospectively analyzed the cases of 280 patients who received their first I-131 therapy in 2003-2014 at our hospital and showed an FDG-avid metastatic lesion. We randomly divided the patients into training (n = 190) and validation (n = 90) datasets. We classified the MTVs as MTVneck-node, MTVdistant-node, MTVlung, MTVbone, and MTVother-organs and tested with/without dichotomization vis-à-vis overall survival (OS). Based on the estimated weighting coefficients of the organ-based MTVs, we propose a new index: the adjusted whole-body MTV (aMTV). Using the validation dataset, we compared the aMTV with cMTV for predicting OS. In a univariate analysis, MTVdistant-node and MTVother-organs were more strongly correlated with the OS than the dichotomized forms, whereas the dichotomized forms of MTVneck-node, MTVlung, and MTVbone were more strongly correlated with OS than the continuous variables. The aMTV was thus expressed as 0.69 × dic(MTVneck-node) + 0.02 × MTVdistant-node + 1.05 × dic(MTVlung) + 1.58 × dic(MTVbone) + 0.01 × MTVother-organs, where dic(x) represents 0 or 1 based on the optimized cut-off. In the model evaluation using the validation group, aMTV was a significant predictor of OS with a higher c-index (0.7676) than cMTV (0.7218). In DTC patients with FDG-avid metastasis before I-131 therapy, all organ-based MTVs were significant predictors of prognosis. As the aMTV outperformed the cMTV for predicting prognoses, we recommend measuring the MTV on an organ basis.

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

Simple SummaryThe advent of immune-checkpoint inhibitors (ICIs) has significantly changed the management of patients with non-small cell lung cancer (NSCLC). Although the assessment of PD-L1 expression remains the gold standard for the selection of cases for immunotherapy, previous experiments have investigated whether metabolic parameters from positron emission tomography (PET) scans could have a similar predictive role. In our retrospective study, we assessed if baseline fluorodeoxyglucose PET (FDG PET) can represent a further tool for selecting patients who are eligible for ICI therapy. Among the parameters tested, a surrogate of the entire tumor burden (metabolic tumor volume, MTV) demonstrated better performance in selecting patients with adequate disease control, as well as those with better overall and progression-free survival. These promising findings from a real-world experiment stress once again the pivotal role of PET scanning in the management of patients with NSCLC, requiring further validation on larger and prospective cohorts before its implementation in the stratification of patients for immunotherapy.Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pembrolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume—wMTV, total lesion glycolysis—wTLG, higher standardized uptake volume maximum and mean—SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respectively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.