International Benchmark for Total Metabolic Tumor Volume Measurement in Baseline 18F-FDG PET/CT of Lymphoma Patients: A Milestone Toward Clinical Implementation.

Total metabolic tumor volume (TMTV) is prognostic in lymphoma. However, cutoff values for risk stratification vary markedly, according to the tumor delineation method used. We aimed to create a standardized TMTV benchmark dataset allowing TMTV to be tested and applied as a reproducible biomarker. Methods: Sixty baseline 18F-FDG PET/CT scans were identified with a range of disease distributions (20 follicular, 20 Hodgkin, and 20 diffuse large B-cell lymphoma). TMTV was measured by 12 nuclear medicine experts, each analyzing 20 cases split across subtypes, with each case processed by 3-4 readers. LIFEx or ACCURATE software was chosen according to reader preference. Analysis was performed stepwise: TMTV1 with automated preselection of lesions using an SUV of at least 4 and a volume of at least 3 cm3 with single-click removal of physiologic uptake; TMTV2 with additional removal of reactive bone marrow and spleen with single clicks; TMTV3 with manual editing to remove other physiologic uptake, if required; and TMTV4 with optional addition of lesions using mouse clicks with an SUV of at least 4 (no volume threshold). Results: The final TMTV (TMTV4) ranged from 8 to 2,288 cm3, showing excellent agreement among all readers in 87% of cases (52/60) with a difference of less than 10% or less than 10 cm3 In 70% of the cases, TMTV4 equaled TMTV1, requiring no additional reader interaction. Differences in the TMTV4 were exclusively related to reader interpretation of lesion inclusion or physiologic high-uptake region removal, not to the choice of software. For 5 cases, large TMTV differences (>25%) were due to disagreement about inclusion of diffuse splenic uptake. Conclusion: The proposed segmentation method enabled highly reproducible TMTV measurements, with minimal reader interaction in 70% of the patients. The inclusion or exclusion of diffuse splenic uptake requires definition of specific criteria according to lymphoma subtype. The publicly available proposed benchmark allows comparison of study results and could serve as a reference to test improvements using other segmentation approaches.

Fluorine-18 FDG PET/CT and New NIMS Grading System for Chemotherapy Response in Breast Cancer.

Background: Positron emission tomography with computed tomography (PET-CT) using fluorine 18-fluorodeoxyglucose (F-18 FDG) is increasingly used to stage patients with locally advanced breast cancer and for assessing treatment response after neoadjuvant chemotherapy (NACT). Aims and Objectives: The aim of the study was to assess the correlation between PET-CT parameters and pathologic response of breast primary after NACT in breast cancer patients and to devise a grading system called NIMS grading system for response assessment using PET quantitative parameters. Materials and Methods: 55 patients who underwent F-18 FDG PET-CT before starting the therapy and again after completion of therapy were identified and included in the study. The clinical data and the histopathologic findings were recorded. All the patients received chemotherapy followed by surgery with axillary lymph node dissection. The PET-CT results were interpreted both qualitatively by visual analysis and quantitatively by estimating maximum Standardized uptake values(SUVmax) and other parameters - SUVmean, SUL, SUVBSA, Metabolic tumor volume (MTV) and Total lesion glycolysis (TLG). Results: The sensitivity and specificity of F-18 FDG PET-CT to detect the residual disease after neoadjuvant chemotherapy was 75.6% & 92.8% respectively. Differences between complete response and residual disease were significant for ΔSUVmax(p=0.005), ΔSUVmean(p=0.006), ΔSUL (0.005) and ΔSUVBSA(0.004), while ΔMTV and ΔTLG were not significantly different between the two groups. The new NIMS grading system included scoring of ΔSUVmax, ΔSUVBSA, ΔTLG and ΔMTV on scale of 1 to 4 and correlated well with PERCIST criteria. Conclusion: F-18 FDG PET-CT had a good accuracy in the detection of residual disease after completion of NACT. Pre chemotherapy PET-CT is not adequate to predict the response of primary tumour to chemotherapy. However, changes in the values of various PET-CT parameters are a sensitive tool to assess the response to chemotherapy. The new grading system is easy to use and showed good correlation to PERCIST.

Lymphoma: The Added Value of Radiomics, Volumes and Global Disease Assessment.

Lymphoma represents a condition that holds promise for cure with existing treatment modalities; nonetheless, the primary clinical obstacle lies in advancing therapeutic outcomes by pinpointing high-risk individuals who are unlikely to respond favorably to standard therapy. In this article, the authors will delineate the significant strides achieved in the lymphoma field, with a particular emphasis on the 3 prevalent subtypes: Hodgkin lymphoma, diffuse large B-cell lymphomas, and follicular lymphoma.

Role of Novel Quantitative Imaging Techniques in Hematological Malignancies.

Hematological malignancies exhibit a widespread distribution, necessitating evaluation of disease activity over the entire body. In clinical practice, visual analysis and semiquantitative parameters are used to assess 18F-FDGPET/CT imaging, which solely represents measurements of disease activity from limited area and may not adequately reflect global disease assessment. An efficient method for assessing the global disease burden of hematological malignancies is to employ PET/computed tomography based novel quantitative parameters. In this article, we explored novel quantitative parameters on PET/CT imaging for assessing global disease burden and the potential role of artificial intelligence (AI) to determine these parameters in evaluation of hematological malignancies.

New predictors of microvascular invasion for small hepatocellular carcinoma ≤ 3 cm.

BACKGROUND: Microvascular invasion (MVI) is a risk factor for postoperative recurrence of hepatocellular carcinoma (HCC), even in early-stage HCC. In small HCC ≤ 3 cm, treatment options include anatomical resection or non-anatomical resection, and MVI has a major effect on treatment decisions. We aimed to identify the predictors of MVI in small HCC ≤ 3 cm. METHODS: We retrospectively studied 129 patients with very early or early-stage HCC ≤ 3 cm who had undergone 18F-fluorodeoxyglucose positron emission tomography/computed tomography and subsequent hepatic resection from January 2016 to August 2023. These patients were divided into the derivation cohort (n = 86) and validation cohort (n = 43). We examined the risk factors for MVI using logistic regression analysis, and established a predictive scoring system in the derivation cohort. We evaluated the accuracy of our scoring system in the validation cohort. RESULTS: In the derivation cohort, a Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3), prothrombin induced by vitamin K deficiency or antagonist-II (PIVKA-II), and metabolic tumor volume (MTV) were independent predictors of MVI. We established the scoring system using these three factors. In the validation test, there were no MVI-positive cases with a score of 0 and 1, and all cases were MVI-positive with a score of 4. Moreover, with a score ≥ 2, the sensitivity, specificity, and accuracy of our scoring system were 100%, 71.4%, and 81.4%, respectively. CONCLUSIONS: Our scoring system can accurately predict MVI in small HCC ≤ 3 cm, and could contribute to establishing an appropriate treatment strategy.

Differentially expressed genes associated with high metabolic tumor volume served as diagnostic markers and potential therapeutic targets for pancreatic cancer.

BACKGROUND: The lack of distinct biomarkers for pancreatic cancer is a major cause of early-stage detection difficulty. The pancreatic cancer patient group with high metabolic tumor volume (MTV), one of the values measured from positron emission tomography-a confirmatory method and standard care for pancreatic cancer, showed a poorer prognosis than those with low MTV. Therefore, MTV-associated differentially expressed genes (DEGs) may be candidates for distinctive markers for pancreatic cancer. This study aimed to evaluate the possibility of MTV-related DEGs as markers or therapeutic targets for pancreatic cancer. METHODS: Tumor tissues and their normal counterparts were obtained from patients undergoing preoperative 18F-FDG PET/CT. The tissues were classified into MTV-low and MTV-high groups (7 for each) based on the MTV2.5 value of 4.5 (MTV-low: MTV2.5 < 4.5, MTV-high: MTV2.5 ≥ 4.5). Gene expression fold change was first calculated in cancer tissue compared to its normal counter and then compared between low and high MTV groups to obtain significant DEGs. To assess the suitability of the DEGs for clinical application, the correlation of the DEGs with tumor grades and clinical outcomes was analyzed in TCGA-PAAD, a large dataset without MTV information. RESULTS: Total RNA-sequencing (MTV RNA-Seq) revealed that 44 genes were upregulated and 56 were downregulated in the high MTV group. We selected the 29 genes matching MTV RNA-seq patterns in the TCGA-PAAD dataset, a large clinical dataset without MTV information, as MTV-associated genes (MAGs). In the analysis with the TCGA dataset, MAGs were significantly associated with patient survival, treatment outcomes, TCGA-PAAD-suggested markers, and CEACAM family proteins. Some MAGs showed an inverse correlation with miRNAs and were confirmed to be differentially expressed between normal and cancerous pancreatic tissues. Overexpression of KIF11 and RCC1 and underexpression of ADCY1 and SDK1 were detected in ~ 60% of grade 2 pancreatic cancer patients and associated with ~ 60% mortality in stages I and II. CONCLUSIONS: MAGs may serve as diagnostic markers and miRNA therapeutic targets for pancreatic cancer. Among the MAGs, KIF11, RCC1, ADCY, and SDK1 may be early diagnostic markers.

[18F]FDG-PET/CT-based risk stratification in women with locally advanced uterine cervical cancer.

BACKGROUND: [18F]FDG-PET/CT is used for staging and treatment planning in patients with locally advanced cervical cancer (LACC). We studied if a PET-based prediction model could provide additional risk stratification beyond International Federation of Gynaecology and Obstetrics (FIGO) staging in our population with LACC to aid treatment decision making. METHODS: In total, 183 patients with LACC treated with chemoradiation between 2013 and 2018 were included. Patients were treated according to FIGO 2009 and retrospectively reclassified according to FIGO 2018 staging system. After validation of an existing PET-based prediction model, the predicted recurrent free survival (RFS), disease specific survival (DSS) and overall survival (OS) at 1, 3, and 5 years, based on metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax) and highest level of [18F]FDG-positive node was calculated. Then the observed survival was compared to the predicted survival. An area under the curve (AUC) close to or higher than 0.7 was considered adequate for accurate prediction. The Youden (J) index defined survival chance cutoff values for low and high risk groups. RESULTS: All AUC values for the comparison between predicted and observed outcomes were > 0.7 except for 5-year RFS and for 5-year OS which were close to 0.7 (0.684 and 0.650 respectively). Cutoff values for low and high risk survival chance were 0.44 for the 3-year RFS and 0.47 for the 5-year OS. The FIGO 2009 system could not differentiate between the risk profiles. After reclassification according to FIGO 2018, all patients with stage IIIC2 and IVB fell in the high risk and almost all patients with stages IB2-IIIB and IVA in the low risk group. In patients with stage IIIC1 disease the FIGO stage cannot discriminate between the risk profiles. CONCLUSIONS: Low and high risk patients with LACC can be identified with the PET-based prediction model. In particular patients with stage IIIC1 need additional risk stratification besides the FIGO 2018 staging. The Kidd model could be a useful tool to aid treatment decision making in these patients. Our results also support the choice of [18F]FDG-PET/CT imaging in patients with LACC.

Metabolic Tumor Volume as Significant Predictor for Chemotherapy Containing PD-L1 Blocker in Extensive Stage Small Cell Lung Cancer.

BACKGROUND/AIM: Chemo-immunotherapy, including the programmed death ligand 1 (PD-L1) antibody, is an effective treatment for patients with extensive-stage small-cell lung cancer (ES-SCLC). However, no biomarker has been established for the prediction of chemo-immunotherapy. Therefore, we investigated the potential of 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) as a predictive marker. PATIENTS AND METHODS: Forty-six patients with ES-SCLC who received 18F-FDG-PET immediately before combined platinum-based chemotherapy with PD-L1 blockade as a first-line treatment were eligible, and the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on 18F-FDG uptake were evaluated. RESULTS: PD-L1 and tumor infiltrative lymphocytes (TILs) were immunohistochemically analyzed in 36 of the 46 patients. A high MTV was significantly associated with poor performance status and low albumin levels, and there was a significant association between low albumin and high TLG. Univariate analysis identified sex, Brinkman index, and MTV as significant predictors of progression-free survival (PFS), and sex, SUVmax, MTV, and TLG as significant factors of overall survival (OS). Multivariate analysis revealed that sex, Brinkman index, and MTV were independent prognostic factors for PFS, and sex, SUVmax, MTV, and TLG were significant predictors of OS. SUVmax was significantly higher in patients with positive PD-L1 expression than in those with negative expression but was not significantly different between positive and negative TILs. Moreover, the levels of MTV and TLG were not closely associated with the levels of PD-L1 and TILs. CONCLUSION: MTV or TLG metabolic tumor activity is suitable for the prediction of chemo-immunotherapy outcomes in patients with ES-SCLC.

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

PURPOSE: Multiple 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 METHODS: Forty-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. RESULTS: Median 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. CONCLUSIONS: The 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.

TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images - a multi-center generalizability analysis.

PURPOSE: Total metabolic tumor volume (TMTV) segmentation has significant value enabling quantitative imaging biomarkers for lymphoma management. In this work, we tackle the challenging task of automated tumor delineation in lymphoma from PET/CT scans using a cascaded approach. METHODS: Our study included 1418 2-[18F]FDG PET/CT scans from four different centers. The dataset was divided into 900 scans for development/validation/testing phases and 518 for multi-center external testing. The former consisted of 450 lymphoma, lung cancer, and melanoma scans, along with 450 negative scans, while the latter consisted of lymphoma patients from different centers with diffuse large B cell, primary mediastinal large B cell, and classic Hodgkin lymphoma cases. Our approach involves resampling PET/CT images into different voxel sizes in the first step, followed by training multi-resolution 3D U-Nets on each resampled dataset using a fivefold cross-validation scheme. The models trained on different data splits were ensemble. After applying soft voting to the predicted masks, in the second step, we input the probability-averaged predictions, along with the input imaging data, into another 3D U-Net. Models were trained with semi-supervised loss. We additionally considered the effectiveness of using test time augmentation (TTA) to improve the segmentation performance after training. In addition to quantitative analysis including Dice score (DSC) and TMTV comparisons, the qualitative evaluation was also conducted by nuclear medicine physicians. RESULTS: Our cascaded soft-voting guided approach resulted in performance with an average DSC of 0.68 ± 0.12 for the internal test data from developmental dataset, and an average DSC of 0.66 ± 0.18 on the multi-site external data (n = 518), significantly outperforming (p < 0.001) state-of-the-art (SOTA) approaches including nnU-Net and SWIN UNETR. While TTA yielded enhanced performance gains for some of the comparator methods, its impact on our cascaded approach was found to be negligible (DSC: 0.66 ± 0.16). Our approach reliably quantified TMTV, with a correlation of 0.89 with the ground truth (p < 0.001). Furthermore, in terms of visual assessment, concordance between quantitative evaluations and clinician feedback was observed in the majority of cases. The average relative error (ARE) and the absolute error (AE) in TMTV prediction on external multi-centric dataset were ARE = 0.43 ± 0.54 and AE = 157.32 ± 378.12 (mL) for all the external test data (n = 518), and ARE = 0.30 ± 0.22 and AE = 82.05 ± 99.78 (mL) when the 10% outliers (n = 53) were excluded. CONCLUSION: TMTV-Net demonstrates strong performance and generalizability in TMTV segmentation across multi-site external datasets, encompassing various lymphoma subtypes. A negligible reduction of 2% in overall performance during testing on external data highlights robust model generalizability across different centers and cancer types, likely attributable to its training with resampled inputs. Our model is publicly available, allowing easy multi-site evaluation and generalizability analysis on datasets from different institutions.

Prognostic value of baseline and interim [18F]FDG PET metabolic parameters in pediatric Hodgkin's lymphoma.

BACKGROUND: Hodgkin lymphoma (HL) in pediatric populations has a high survival rate but poses risks for long-term morbidities. Although [18F]fluoro­2­deoxy­2­d­glucose positron emission tomography ([18F]FDG PET) scans offer potential for improved risk stratification, the definitive prognostic value of quantitative [18F]FDG PET parameters remains unclear for pediatric HL. METHODS: A single-center, retrospective study included pediatric patients diagnosed with HL between 2016 and 2023 treated according to EuroNet-PHL-C1 and DAL/GPOH-HD protocols. Patients underwent baseline and interim PET/CT scans after two chemotherapy cycles. Event-free survival (EFS) was the primary endpoint, Deauville score was the secondary endpoint. Quantitative [18F]FDG PET parameters included SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) that were evaluated using two segmentation methods (SUV 2.5, 41% SUVmax). Survival outcomes were assessed using Cox regression analysis. RESULTS: A total of 115 patients (50 males, median age 14.2 years) were studied, with a median follow-up period of 35 months. During this period, 16 cases (13.9%) of relapse or progression were noted. Baseline and interim MTV 2.5, MTV 41%, TLG 2.5, and TLG 41%, along with interim SUVmax, were significantly associated with worse EFS and correlated with post-treatment Deauville scores. In multivariable analysis, interim MTV 2.5 > 0 ml (adj. hazard ratio, HR: 3.89, p = 0.009) and interim TLG 41% ≥ 30 g (adj. HR: 7.98, p = 0.006) were independent risk factors for EFS. CONCLUSION: Baseline and interim [18F]FDG PET parameters can serve as significant prognostic indicators for EFS and treatment response in pediatric HL. These quantitative measures could enhance individualized, risk-adapted treatment strategies for children and adolescents with HL.

Volume-based 18F-FDG PET/CT predicts prognosis and outcome of active surveillance for intra-abdominal desmoid tumor.

PURPOSE: Desmoid tumor (DT) is a rare monoclonal, fibroblastic proliferation characterized by a variable and often unpredictable clinical course. Initial active surveillance is recommended by current guideline, and surgery is one of the main therapies for DT. Predicting the prognosis and outcome of active surveillance for intra-abdominal DT is pressing issue. METHODS: The study included eighteen patients with intra-abdominal DT. Metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum standardized uptake value (SUVmax) were measured. We analyzed their relationship with the outcome of active surveillance, as well as clinical, prognostic, and pathological data. RESULTS: The MTV and TLG of recurrent DT were significantly higher than those of non-recurrent DT (P < 0.001 and P = 0.00, respectively). The ROC curve suggested that the appropriate cutoff values for distinguishing recurrent DT from non-recurrent DT were 760.8 for MTV (sensitivity = 1, specificity = 0.857 and AUC = 0.929), and 1318.4 for TLG (sensitivity = 1, specificity = 0.786, and AUC = 0.911). The cutoff values of MTV and TLG significantly correlated with PFS using the Kaplan-Meier method (P = 0.002 and P = 0.007, respectively). MTV and TLG could distinguish DTs with subsequent progression from stable ones (P = 0.004 and P = 0.004, respectively). The ROC curve suggested that the appropriate cutoff values for distinguishing DTs with subsequent progression from stable ones were 197.1 for MTV (sensitivity = 0.9, specificity = 1, and AUC = 0.900), and 445.45 for TLG (sensitivity = 0.9, specificity = 1, and AUC = 0.900). CONCLUSION: Volume-based 18F-FDG-PET can predict prognosis of intra-abdominal DT. MTV and TLG can predict the outcome of active surveillance for intra-abdominal DT. MTV and TLG can potentially be predictors of surgical risk and difficulty.

Metabolic parameters of pretreatment 2-[18F]fluoro-D-glucose positron emission tomography for prognosis in patients with gallbladder adenocarcinoma: a cohort study.

Background: The incidence of gallbladder adenocarcinoma (GBA) is relatively low, yet it exhibits a high degree of malignancy and a significantly low 5-year survival rate. The aim of this study was to investigate the prognostic value of pretreatment 2-[18F]fluoro-D-glucose positron emission tomography {2-[18F]FDG PET} parameters in predicting outcomes for patients with GBA. Methods: In total, 67 patients with GBA who underwent 2-[18F]FDG PET/computed tomography (CT) before treatment were retrospectively analyzed at Chinese PLA General Hospital from January 2012 to June 2022. All patients were diagnosed by pathology, and their baseline characteristics and clinical data were collected. The metabolic PET parameters of the primary and metastatic lesions were measured, including the maximum and average standardized uptake values (SUVs), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). The prognostic significance of metabolic parameters and other clinical variables was assessed using Cox proportional hazards regression models. Differences in progression-free survival (PFS) and overall survival (OS) in relation to metabolic parameters were examined using the Kaplan-Meier method. Results: During a median follow-up period of 14.2 months, 43 patients (64.2%) experienced tumor recurrence or progression, and 38 patients (56.7%) died of cancer. In the univariate Cox regression analysis, liver parenchymal invasion (P=0.001), lymph node metastasis (P=0.007), distant metastases (P=0.049), tumor differentiation (P=0.028), surgery (P=0.014), carcinoembryonic antigen (CEA) level (P=0.030), carbohydrate antigen 19-9 (CA19-9) level (P=0.003), TLG (P=0.005), MTV (P<0.001), sum of the TLGs of the primary and metastatic lesions (total TLG, tTLG) (P=0.001), and sum of the MTVs of the primary and metastatic lesions (total MTV, tMTV) (P<0.001) were significant predictors of PFS. In multivariate analysis, MTV was an independent predictor of PFS [hazard ratio (HR) =2.785; 95% confidence interval (CI): 1.204-6.441; P=0.017]. In the univariate Cox regression analysis, liver parenchymal invasion (P=0.001), lymph node metastasis (P=0.027), distant metastases (P=0.036), tumor differentiation (P=0.047), surgery (P=0.002), neutrophil-to-lymphocyte ratio (NLR) (P=0.011), CEA level (P=0.036), CA19-9 level (P<0.001), TLG (P=0.007), MTV (P<0.001), tTLG (P=0.003), and tMTV (P<0.001) were significant predictors of OS. In the multivariate analysis, higher CA19-9 levels >37 U/mL and a greater tMTV (HR =2.961; 95% CI: 1.092-8.024; P=0.033) were predictive of OS. Conclusions: Our study results suggest that pretreatment 2-[18F]FDG PET parameters can not only assist in the diagnosis of patients with GBA but may also serve as predictive factors for the prognosis of these patients and should thus be applied in their treatment.

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

Background: The objective of this study was to investigate the prognostic significance of total metabolic tumor volume (TMTV) derived from baseline 18F-2-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), in conjunction with epidermal growth factor receptor (EGFR) mutation status, among patients with lung adenocarcinoma (LUAD). Methods: We performed a retrospective analysis on 141 patients with LUAD (74 males, 67 females, median age 67 (range 34-86)) who underwent 18F-FDG PET/CT and had their EGFR mutation status determined. Optimal cutoff points for TMTV were determined using time-dependent receiver operating characteristic curve analysis. The survival difference was compared using Cox regression analysis and Kaplan‒Meier curves. Results: The EGFR mutant patients (n = 79, 56.0%) exhibited significantly higher 2-year progression-free survival (PFS) and overall survival (OS) rates compared to those with EGFR wild-type (n = 62, 44.0%), with rates of 74.2% vs 69.2% (P = 0.029) and 86.1% vs 67.7% (P = 0.009), respectively. The optimal cutoff values of TMTV were 36.42 cm3 for PFS and 37.51 cm3 for OS. Patients with high TMTV exhibited significantly inferior 2-year PFS and OS, with rates of 22.4% and 38.1%, respectively, compared to those with low TMTV, who had rates of 85.8% and 95.0% (both P < 0.001). In both the EGFR mutant and wild-type groups, patients exhibiting high TMTV demonstrated significantly inferior 2-year PFS and OS compared to those with low TMTV. In multivariate analysis, EGFR mutation status (hazard ratio, HR, 0.41, 95% confidence interval, CI [0.18-0.94], P = 0.034) and TMTV (HR 8.08, 95% CI [2.34-28.0], P < 0.001) were independent prognostic factors of OS, whereas TMTV was also an independent prognosticator of PFS (HR 2.59, 95% CI [1.30-5.13], P = 0.007). Conclusion: Our study demonstrates that the integration of TMTV on baseline 18F-FDG PET/CT with EGFR mutation status improves the accuracy of prognostic evaluation for patients with LUAD.

Metabolic tumor volume predicts outcome in patients with advanced stage follicular lymphoma from the RELEVANCE trial.

BACKGROUND: We investigated the prognostic value of baseline positron emission tomography (PET) parameters for patients with treatment-naïve follicular lymphoma (FL) in the phase III RELEVANCE trial, comparing the immunomodulatory combination of lenalidomide and rituximab (R2) versus R-chemotherapy (R-chemo), with both regimens followed by R maintenance therapy. PATIENTS AND METHODS: Baseline characteristics of the entire PET-evaluable population (n = 406/1032) were well balanced between treatment arms. The maximal standard uptake value (SUVmax) and the standardized maximal distance between tow lesions (SDmax) were extracted, the standardized distance between two lesions the furthest apart, were extracted. The total metabolic tumor volume (TMTV) was computed using the 41% SUVmax method. RESULTS: With a median follow-up of 6.5 years, the 6-year progression-free survival (PFS) was 57.8%, the median TMTV was 284 cm3, SUVmax was 11.3 and SDmax was 0.32 m-1, with no significant difference between arms. High TMTV (>510 cm3) and FLIPI were associated with an inferior PFS (P = 0.013 and P = 0.006, respectively), whereas SUVmax and SDmax were not (P = 0.08 and P = 0.12, respectively). In multivariable analysis, follicular lymphoma international prognostic index (FLIPI) and TMTV remained significantly associated with PFS (P = 0.0119 and P = 0.0379, respectively). These two adverse factors combined stratified the overall population into three risk groups: patients with no risk factors (40%), with one factor (44%), or with both (16%), with a 6-year PFS of 67.7%, 54.5%, and 41.0%, respectively. No significant interaction between treatment arms and TMTV or FLIPI (P = 0.31 or P = 0.59, respectively) was observed. The high-risk group (high TMTV and FLIPI 3-5) had a similar PFS in both arms (P = 0.45) with a median PFS of 68.4% in the R-chemo arm versus 71.4% in the R2 arm. CONCLUSIONS: Baseline TMTV is predictive of PFS, independently of FLIPI, in patients with advanced FL even in the context of antibody maintenance.

Impact of baseline and interim quantitative PET parameters on outcomes of classical Hodgkin Lymphoma.

Currently, analysis of interim PET (iPET) according to the Deauville score (DS) is the most important predictive factor in Hodgkin lymphoma (HL); however, there is room for improvement in its prognostic power. This study aimed to evaluate the prognostic value of quantitative PET analysis (maximum standard uptake value [SUVmax], total metabolic tumor volume [TMTV] and total lesion glicolysis [TLG]) at baseline (PET0) and iPET in a retrospective cohort of newly diagnosed classical HL. For positive iPET (+ iPET), the reduction of quantitative parameters in relation to PET0 (ΔSUVmax, ΔTMTV and ΔTLG) was calculated. Between 2011 and 2017, 234 patients treated with ABVD were analyzed. Median age was 30 years-old, 59% had advanced stage disease, 57% a bulky mass and 25% a + iPET (DS 4-5). At baseline, high TLG was associated with an increased cumulative incidence of failure (CIF) (p = 0.032) while neither SUVmax, TMTV or TLG were associated with overall survival (OS) or progression-free survival (PFS). In multivariate analysis, only iPET was associated with CIF (p < 0.001). Among ΔSUVmax, ΔTMTV and ΔTLG, only a ΔSUVmax ≥ 68.8 was significant for PFS (HR: 0.31, CI95%: 0.11-0.86, p = 0.024). A subset of patients with improved PFS amongst + iPET was identified by the quantitative (ΔSUVmax ≥ 68.8%) analysis. In this real-world Brazilian cohort, with prevalent high-risk patients, quantitative analysis of PET0 did not demonstrate to be prognostic, while a dynamic approach incorporating the ΔSUVmax to + iPET succeeded in refining a subset with better prognosis. These findings warrant validation in larger series and indicate that not all patients with + iPET might need treatment intensification.

A single-center, multi-factor, retrospective study to improve the diagnostic accuracy of primary prostate cancer using [68Ga]Ga-PSMA-11 total-body PET/CT imaging.

PURPOSE: To improve the diagnostic accuracy of initial detection in patients with suspected primary prostate cancer (PCa). METHODS: Eighty-four patients who underwent Gallium-68-labeled prostate-specific membrane antigen ([68Ga]Ga-PSMA-11) total-body positron emission tomography/computed tomography (PET/CT) imaging before treatment in our department were enrolled. The maximum standard uptake value (SUVmax) of the prostate (SUVmax-PSMA), liver (SUVmax-PSMA-L), and mediastinal blood pool (SUVmax-PSMA-M) was measured using [68Ga]Ga-PSMA-11 total-body PET/CT imaging. The [68Ga]Ga-PSMA-11 derived metabolic tumor volume (MTV), the total lesion (TLP), and the cross-sectional areas of focal concentration in the prostate (CAP) were also determined. Besides, the prostate-specific antigen (PSA) levels and the above imaging characteristics were analyzed using receiver operating characteristic curves to identify the cutoff value to improve the diagnostic accuracy of suspected PCa. Finally, a multivariate regression analysis was conducted to discover the independent predictor to improve the diagnostic accuracy on [68Ga]Ga-PSMA-11 total-body imaging. RESULTS: There was no significant difference between the PCa and Non-PCa groups in age, height, weight, injected dose, except for the PSA levels, the SUVmax-PSMA, TLP, MTV, and CAP. Besides, the SUVmax-PSMA-T/L and SUVmax-PSMA-T/M derived from SUVmax-PSMA were both significantly different. In addition, the areas under the curve of PSA levels, SUVmax-PSMA, SUVmax-PSMA-T/L, SUVmax-PSMA-T/M, TLP, MTV, and CAP to predict PCa on [68Ga]Ga-PSMA-11 imaging were 0.620 (95% confidence interval (CI) 0.485-0.755), 0.864 (95% CI 0.757-0.972), 0.819 (95% CI 0.704-0.935), 0.876 (95% CI 0.771-0.980), 0.845 (95% CI 0.741-0.949), 0.820 (95% CI 0.702-0.938), 0.627 (95% CI 0.499-0.754), respectively. However, a multivariate regression analysis showed that SUVmax-PSMA was an independent predictor, with a cutoff value of 11.5 and an odds ratio of 1.221. CONCLUSION: The SUVmax-PSMA with a cutoff value of 11.5 was an independent predictor to improve the diagnostic accuracy of PCa on [68Ga]Ga-PSMA-11 total-body imaging.

A low total metabolic tumor volume independently predicts for a longer time to first treatment in initially observed, low tumor burden follicular lymphoma.

Watchful waiting is an acceptable management strategy for advanced-stage, low tumor burden (LTB) patients with follicular lymphoma (FL). However, the prediction of how long this treatment-free observation period will last remains imperfect. We explored whether total metabolic tumor volume (TMTV) and other positron emission tomography parameters were predictive of time to first treatment (TTFT). We analyzed 97 grade 1-3A advanced-stage LTB FL patients and found that a high TMTV was associated with other tumor burden features at diagnosis. Patients with a TMTV above our established cutoff of 50 mL had a significantly shorter median duration of observation (2.6 vs. 8.8 years; p = 0.001). At 5 years, 77% of patients with a high TMTV and 46% of patients with a low TMTV required treatment. In the multivariable analysis, a high TMTV was the only independent factor predicting TTFT (hazard ratio = 2.09; p = 0.017). Overall, TMTV is a strong predictor of the duration of observation in LTB FL patients. Upon validation of our cutoff in external series and standardization of the methodology, the TMTV could become an additional factor to consider deferring or initiating treatment in otherwise LTB patients.

Metabolic tumor volume and sites of organ involvement predict outcome in NSCLC immune-checkpoint inhibitor therapy.

PURPOSE: The purpose of this study was to assess the ability of pretreatment PET parameters and peripheral blood biomarkers to predict progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with ICIT. METHODS: We prospectively included 87 patients in this study who underwent pre-treatment [18F]-FDG PET/CT. Organ-specific and total metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured using a semiautomatic software. Sites of organ involvement (SOI) were assessed by PET/CT. The log-rank test and Cox-regression analysis were used to assess associations between clinical, laboratory, and imaging parameters with PFS and OS. Time dependent ROC were calculated and model performance was evaluated in terms of its clinical utility. RESULTS: MTV increased with the number of SOI and was correlated with neutrophil and lymphocyte cell count (Spearman's rho = 0.27 or 0.32; p =.02 or 0.003; respectively). Even after adjustment for known risk factors, such as PD-1 expression and neutrophil cell count, the MTV and the number of SOI were independent risk factors for progression (per 100 cm3; adjusted hazard ratio [aHR]: 1.13; 95% confidence interval [95%CI]: 1.01-1.28; p =.04; single SOI vs. ≥ 4 SOI: aHR: 2.26, 95%CI: 1.04-4.94; p =.04). MTV and the number of SOI were independent risk factors for overall survival (per 100 cm3 aHR: 1.11, 95%CI: 1.01-1.23; p =.03; single SOI vs. ≥ 4 SOI: aHR: 4.54, 95%CI: 1.64-12.58; p =.04). The combination of MTV and the number of SOI improved the risk stratification for PFS and OS (log-rank test p <.001; C-index: 0.64 and 0.67). CONCLUSION: The MTV and the number of SOI are simple imaging markers that provide complementary information to facilitate risk stratification in NSCLC patients scheduled for ICIT.

Retrospective analysis of the 18F-FDG PET/CT cutoff value for metabolic parameters was performed as a prediction model to evaluate risk factors for endometrial cancer.

PURPOSE: The study retrospectively analyzed the accuracy and predictive ability of preoperative integrated whole-body 18F-FDG PET/CT for the assessment of high-risk factors in patients with endometrial carcinoma (EC). MATERIALS AND METHODS: A total of 205 patients with endometrial cancer who underwent preoperative PET/CT at Shanghai General Hospital from January 2018 to December 2021 were retrospectively evaluated and last follow-up was June 2023. Our study evaluated the ability and optimal cutoff values of three metabolic and volumetric parameters-standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG)-to predict deep myometrial invasion (DMI), endocervical stroma invasion (ESI) and lymph node metastases (LNM) in endometrial cancer. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PET/CT were used to assess the diagnostic performance for the prediction. RESULTS: Our study demonstrated a significant relationship between SUVmax (11.29, 17.38, 9.47), SUVmean (5.20, 6.12, 4.49), MTV (38.15, 36.28, 33.79 ml), and TLG (199.30, 225.10, 156.40 g) on PET/CT and histologically confirmed DMI, ESI and LNM in endometrial carcinoma (EC), with sensitivity, specificity, accuracy, PPV, and NPV of 100%/100%/100%, 96.53%/98.89%/87.14%, 97.56%/99.02%/91.22%, 92.42%/92.85%/78.31%, and 100%/100%/100%, respectively. Our study showed a risk model based on optimal cutoff values for MTV and TLG of 19.6 ml/126.3 g, 20.54 ml/84.80 g and 24 ml/49.83 g to preoperatively predict DMI, ESI, and LNM, respectively, in endometrial carcinoma. The 4-year OS (HR) for Stage IA, IB, II, III and IV according to 2009 FIGO was 98.00% (0.22), 95.20% (0.04), 83.90% (0.18), 90.50% (0.09) and 60% (0.51). Accordingly, estimated 4-year DFS (HR) for the stage IA-III was 98% (0.02), 95.20% (0.05), 76.90% (0.27) and 76.30% (0.35), all the patients in stage IV occurred recurrence and progression. CONCLUSION: The present study showed patients with MTV > = 19.6 ml of MI and PET- positive LN with MTV cutoff > = 24 ml tended to predict poor OS and PFS in endometrial carcinoma. The cutoff of MTV and TLG in PET/CT assessment could be an independent prognostic factors to predict aggressive forms of EC.