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

Thoracic metabolic tumor volume predicts survival in advanced lung adenocarcinoma: a PET/computed tomography-based cohort study

INTRODUCTION

Advanced-stage lung adenocarcinoma is associated with poor survival, highlighting the need for improved prognostic tools. PET/computed tomography (CT) metrics and mutation profiling may enhance risk stratification when integrated with clinical parameters.

METHODS

This retrospective cohort study included 109 advanced-stage lung adenocarcinoma between 2018 and 2023. PET/CT metrics - standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) - were assessed for primary tumors and thoracic regions. ECOG performance status and mutation profiles were also recorded. Cox regression analysis was performed to identify independent predictors of overall survival (OS).

RESULTS

In univariate analysis, all PET/CT parameters were significantly associated with OS. In multivariate analysis, thoracic MTV emerged as the strongest independent prognostic factor (HR = 2.85, 95% CI: 1.69-4.81, P < 0.001), followed by ECOG ≥2 (HR = 2.31, 95% CI: 1.18-3.72, P = 0.004). Although KRAS mutations were associated with poorer OS in univariate analysis, they did not retain significance in the multivariate model.

CONCLUSION

Our findings emphasize the prognostic value of thoracic MTV as a robust, independent biomarker for advanced-stage lung adenocarcinoma. Integrating PET/CT metrics with clinical and molecular data may improve staging accuracy and inform treatment decisions, particularly in settings where mutational status alone is insufficient.

The value of 18F-FDG PET/CT combined with 3D quantitative technology and clinicopathological features in predicting prognosis of NSCLC

Objective

To investigate the value of Fluorine-18 Fluorodeoxyglucose (18F-FDG) Positron Emission Tomography/Computed Tomography (PET/CT) combined with 3D quantitative technology and clinicopathological features in predicting the prognosis of non-small cell lung cancer (NSCLC).

Methods

A retrospective review was performed for patients who underwent PET/CT and curative resection of NSCLC between January 2016 and June 2019 in our hospital. PET/CT data, clinical features, and pathology results were collected. Gross tumor volume (GTV) was delineated on CT images by ITK-SNAP software. The prognosis was followed up, and the study endpoint was progression-free survival (PFS). Receiver operating characteristic curve (ROC) was used to initially assess the relationship between each parameter and PFS, and parameters were grouped accordingly. Cox proportional hazards regression was used to develop models based on clinicopathological features to predict prognosis of NSCLC patients. Kaplan-Meier method was used to draw the survival curves.

Results

A total of 128 patients were enrolled in the study with PFS of 8-96 months. Univariate analysis demonstrated that age, SUVindex (the ratio of SUVmax of lesion to SUVmax of liver), metabolic tumor volume (MTV), Dmax (the largest diameter), GTV, lymph node metastasis (LNM), and TNM staging are significantly related to recurrence (all p<0.05). The multivariate analysis showed that only age, SUVindex, and LNM were independent prognostic factor for PFS (all p < 0.05).

Conclusions

Although 18F-FDG PET/CT combined with 3D quantitative technique were helpful in predicting PFS in NSCLC, only age, SUVindex, and LNM were independent predictors for PFS.

Prognostic significance of total metabolic tumor volume on baseline 18F-FDG PET/CT in patients with lung adenocarcinoma: further stratification of the ninth edition of TNM staging subgroups

BACKGROUND

This study aimed to investigate the prognostic value of baseline total metabolic tumor volume (TMTV) on 18F-fluorodeoxyglucose positron emission tomography/computed tomography and its potential for further stratification within the ninth tumor-node-metastasis (TNM) staging system in patients with lung adenocarcinoma (LUAD).

METHODS

A cohort of 384 patients with LUAD who had undergone pretreatment PET/CT were included in this retrospective study. The optimal cutoff value for TMTV was determined through analysis of time-dependent receiver operating characteristic curves. The analysis of overall survival (OS) was conducted utilizing Kaplan-Meier curves. Predictive capacity was evaluated using the C statistic.

RESULTS

The optimal cutoff value for TMTV was 40.13 ml. The survival rates of patients varied significantly across stages I (n = 164), II (n = 37), III (n = 46), and IV (n = 137); however, there was no statistically significant difference between stages II and III (P = 0.440). In stages II-IV, the 2-year OS rates for patients with TMTV less than 40.13 ml were significantly higher at 81.7 and 86.7%, respectively, compared with patients with TMTV greater than equal to 40.13 ml who had rates of only 56.5 and 42.5%. No patients with stage I presented TMTV greater than or equal to 40.13 ml, and the 2-year OS rate was 98.3%. The C index did not reveal a significant difference between TNM and TMTV in their predictive ability for OS (0.83 vs. 0.85, P = 0.159).

CONCLUSION

The TNM staging system demonstrates robust prognostic utility in patients with LUAD, while the incorporation of baseline TMTV may offer additional risk stratification within distinct TNM stages.

Prognostic Value of Tumor Dissemination (Dmax) Derived from Basal 18F-FDG Positron Emission Tomography/Computed Tomography in Patients with Advanced Non-Small-Cell Lung Cancer

Objectives: The aim of the present study was to test whether a parameter reflecting tumor dissemination (Dmax), derived from basal 18F-FDG PET/CT, may predict clinical outcome in patients with advanced non-small-cell lung cancer (NSCLC). Methods: A total of 78 patients (55 men, 23 women) with stage III and IV NSCLC who had undergone whole-body 18F-FDG PET/CT scan at diagnosis were included in this study. Imaging parameters of primary lung tumors along with total MTV (MTVTOT) and whole-body TLG (TLGWB) of all malignant lesions were determined. Moreover, the largest distance between two 18F-FDG avid lesions (Dmax) in each patient was measured. Univariate and multivariate analyses of clinical and imaging variables were performed followed by overall survival (OS) curves. Results: A total of 441 lesions were analyzed, including 78 primary tumors, 174 metastatic lymph nodes, and 189 distant metastases. In primary tumors, the average values of SUVmax, SUVmean, MTV, and TLG were 11.80 ± 5.73, 5.37 ± 2.09, 60.61 ± 102.57 mL, and 340.36 ± 558.40 g, respectively. The mean value of Dmax was 29.98 ± 20.98 cm, whereas the average values of MTVTOT and TLGWB were 155.90 ± 176.94 mL and 851.08 ± 1032.17 g, respectively. In the univariate analysis, OS was predicted by MTVTOT (p = 0.0145), TLGWB (p = 0.0518), Dmax (p = 0.0031), and stage (p = 0.0130), whereas in the multivariate analysis, only Dmax was retained in the model (χ2 = 7.3130, p = 0.0068). In particular, a high Dmax value indicates a worse prognosis. Moreover, the combination of Dmax with MTVTOT was able to improve the prognostic stratification of patients with advanced stages of NSCLC. Conclusions: Dmax, by reflecting tumor dissemination throughout the body, can predict overall survival in NSCLC patients.

Prognostic value of metabolic tumor volume on [18F]FDG PET/CT in addition to the TNM classification system of locally advanced non-small cell lung cancer

PURPOSE

Staging of non-small cell lung cancer (NSCLC) is commonly based on [18F]FDG PET/CT, in particular to exclude distant metastases and guide local therapy approaches like resection and radiotherapy. Although it is hoped that PET/CT will increase the value of primary staging compared to conventional imaging, it is generally limited to the characterization of TNM. The first aim of this study was to evaluate the PET parameter metabolic tumor volume (MTV) above liver background uptake as a prognostic marker in lung cancer. The second aim was to investigate the possibility of incorporating MTV into the TNM classification system for disease prognosis in locally advanced NSCLC treated with chemoradiotherapy.

METHODS

Retrospective evaluation of 235 patients with histologically proven, locally advanced NSCLC from the multi-centre randomized clinical PETPLAN trial and a clinical cohort from a hospital registry. The PET parameters SUVmax, SULpeak, MTV and TLG above liver background uptake were determined. Kaplan-Meier curves and stratified Cox proportional hazard regression models were used to investigate the prognostic value of PET parameters and TNM along with clinical variables. Subgroup analyses were performed to compare hazard ratios according to TNM, MTV, and the two variables combined.

RESULTS

In the multivariable Cox regression analysis, MTV was associated with significantly worse overall survival independent of stage and other prognostic variables. In locally advanced disease stages treated with chemoradiotherapy, higher MTV was significantly associated with worse survival (median 17 vs. 32 months). Using simple cut-off values (45 ml for stage IIIa, 48 ml for stage IIIb, and 105 ml for stage IIIc), MTV was able to further predict differences in survival for stages IIIa-c. The combination of TNM and MTV staging system showed better discrimination for overall survival in locally advanced disease stages, compared to TNM alone.

CONCLUSION

Higher metabolic tumor volume is significantly associated with worse overall survival and combined with TNM staging, it provides more precise information about the disease prognosis in locally advanced NSCLC treated with chemoradiotherapy compared to TNM alone. As a PET parameter with volumetric information, MTV represents a useful addition to TNM.

Coefficient of variation and texture analysis of 18F-FDG PET/CT images for the prediction of outcome in patients with multiple myeloma

In multiple myeloma (MM) bone marrow infiltration by monoclonal plasma cells can occur in both focal and diffuse manner, making staging and prognosis rather difficult. The aim of our study was to test whether texture analysis of 18 F-2-deoxy-d-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) images can predict survival in MM patients. Forty-six patients underwent 18 F-FDG-PET/CT before treatment. We used an automated contouring program for segmenting the hottest focal lesion (FL) and a lumbar vertebra for assessing diffuse bone marrow involvement (DI). Maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean) and texture features such as Coefficient of variation (CoV), were obtained from 46 FL and 46 DI. After a mean follow-up of 51 months, 24 patients died of myeloma and were compared to the 22 survivors. At univariate analysis, FL SUVmax (p = 0.0453), FL SUVmean (p = 0.0463), FL CoV (p = 0.0211) and DI SUVmax (p = 0.0538) predicted overall survival (OS). At multivariate analysis only FL CoV and DI SUVmax were retained in the model (p = 0.0154). By Kaplan-Meier method and log-rank testing, patients with FL CoV below the cut-off had significantly better OS than those with FL CoV above the cut-off (p = 0.0003), as well as patients with DI SUVmax below the threshold versus those with DI SUVmax above the threshold (p = 0.0006). Combining FL CoV and DI SUVmax by using their respective cut-off values, a statistically significant difference was found between the resulting four survival curves (p = 0.0001). Indeed, patients with both FL CoV and DI SUVmax below their respective cut-off values showed the best prognosis. Conventional and texture parameters derived from 18F-FDG PET/CT analysis can predict survival in MM patients by assessing the heterogeneity and aggressiveness of both focal and diffuse infiltration.

[18F]FDG PET-CT radiomics signature to predict pathological complete response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: a multicenter study

OBJECTIVES

This study aims to develop and validate a radiomics model based on 18F-fluorodeoxyglucose positron emission tomography-computed tomography ([18F]FDG PET-CT) images to predict pathological complete response (pCR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

One hundred eighty-five patients receiving neoadjuvant chemoimmunotherapy for NSCLC at 5 centers from January 2019 to December 2022 were included and divided into a training cohort and a validation cohort. Radiomics models were constructed via the least absolute shrinkage and selection operator (LASSO) method. The performances of models were evaluated by the area under the receiver operating characteristic curve (AUC). In addition, genetic analyses were conducted to reveal the underlying biological basis of the radiomics score.

RESULTS

After the LASSO process, 9 PET-CT radiomics features were selected for pCR prediction. In the validation cohort, the ability of PET-CT radiomics model to predict pCR was shown to have an AUC of 0.818 (95% confidence interval [CI], 0.711, 0.925), which was better than the PET radiomics model (0.728 [95% CI, 0.610, 0.846]), CT radiomics model (0.732 [95% CI, 0.607, 0.857]), and maximum standard uptake value (0.603 [95% CI, 0.473, 0.733]) (p < 0.05). Moreover, a high radiomics score was related to the upregulation of pathways suppressing tumor proliferation and the infiltration of antitumor immune cell.

CONCLUSION

The proposed PET-CT radiomics model was capable of predicting pCR to neoadjuvant chemoimmunotherapy in NSCLC patients.

CLINICAL RELEVANCE STATEMENT

This study indicated that the generated 18F-fluorodeoxyglucose positron emission tomography-computed tomography radiomics model could predict pathological complete response to neoadjuvant chemoimmunotherapy, implying the potential of our radiomics model to personalize the neoadjuvant chemoimmunotherapy in lung cancer patients.

KEY POINTS

• Recognizing patients potentially benefiting neoadjuvant chemoimmunotherapy is critical for individualized therapy of lung cancer. • [18F]FDG PET-CT radiomics could predict pathological complete response to neoadjuvant immunotherapy in non-small cell lung cancer. • [18F]FDG PET-CT radiomics model could personalize neoadjuvant chemoimmunotherapy in lung cancer patients.

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.

Coefficient of Variation in Metastatic Lymph Nodes Determined by 18F-FDG PET/CT in Patients with Advanced NSCLC: Combination with Coefficient of Variation in Primary Tumors

Purpose The aim of the present study was to test whether the coefficient of variation (CoV) of 18F-FDG PET/CT images of metastatic lymph nodes and primary tumors may predict clinical outcome in patients with advanced non-small cell lung cancer (NSCLC). Materials and Methods Fifty-eight NSCLC patients who had undergone 18F-FDG PET/CT at diagnosis were evaluated. SUVmax, SUVmean, CoV, MTV and TLG were determined in targeted lymph nodes and corresponding primary tumors along with Total MTV (MTVTOT) and Whole-Body TLG (TLGWB) of all malignant lesions. Univariate analysis was performed using Cox proportional hazards regression whereas the Kaplan-Meier method and log-rank tests were used for survival analysis. Results Fifty-eight metastatic lymph nodes were analyzed and average values of SUVmax, SUVmean, CoV, MTV and TLG were 11.89 ± 8.54, 4.85 ± 1.90, 0.37 ± 0.16, 46.16 ± 99.59 mL and 256.84 ± 548.27 g, respectively, whereas in primary tumors they were 11.92 ± 6.21, 5.47 ± 2.34, 0.36 ± 0.14, 48.03 ± 64.45 mL and 285.21 ± 397.95 g, respectively. At univariate analysis, overall survival (OS) was predicted by SUVmax (p = 0.0363), SUVmean (p = 0.0200) and CoV (p = 0.0139) of targeted lymph nodes as well as by CoV of primary tumors (p = 0.0173), MTVTOT (p = 0.0007), TLGWB (p = 0.0129) and stage (p = 0.0122). Using Kaplan-Meier analysis, OS was significantly better in patients with CoV of targeted lymph nodes ≤ 0.29 than those with CoV > 0.29 (p = 0.0147), meanwhile patients with CoV of primary tumors > 0.38 had a better prognosis compared to those with CoV ≤ 0.38 (p = 0.0137). Finally, we combined the CoV values of targeted lymph nodes and primary tumors in all possible arrangements and a statistically significant difference was found among the four survival curves (p = 0.0133). In particular, patients with CoV of targeted lymph nodes ≤ 0.29 and CoV of primary tumors > 0.38 had the best prognosis. Conclusions The CoV of targeted lymph nodes combined with the CoV of primary tumors can predict prognosis of NSCLC patients.

Metabolic Tumor Volume from 18F-FDG PET/CT in Combination with Radiologic Measurements to Predict Long-Term Survival Following Transplantation for Colorectal Liver Metastases

The aim of the present study is to report on the ability of metabolic tumor volume (MTV) of liver metastases from pre-transplant 18F-FDG PET/CT in combination with conventional radiological measurements from CT scans to predict long-term disease-free survival (DFS), overall survival (OS), and survival after relapse (SAR) after liver transplantation for colorectal liver metastases. The total liver MTV was obtained from the 18F-FDG PET/CT, and the size of the largest metastasis and the total number of metastases were obtained from the CT. DFS, OS, and SAR for patients with a low and high MTV, in combination with a low and high size, number, and tumor burden score, were compared using the Kaplan-Meier method and log-rank test. Patients with a low number of metastases and low MTV had a significantly longer OS than those with a high MTV, with a median survival of 151 vs. 26 months (p = 0.010). Patients with a high number of metastases and low MTV had significantly longer DFS, OS, and SAR than patients with a high MTV (p = 0.034, 0.006, and 0.026). The tumor burden score of group/zone 3, in combination with a low MTV, had a significantly improved DFS, OS, and SAR compared to those with a high MTV (p = 0.034, <0.001, and 0.006). Patients with a low MTV of liver metastases had a long DFS, OS, and SAR despite a high number of liver metastases and a high tumor burden score.

Potential biomarkers for predicting immune response and outcomes in lung cancer patients undergoing thermal ablation

Thermal ablation is a promising alternative treatment for lung cancer. It disintegrates cancer cells and releases antigens, followed by the remodeling of local tumor immune microenvironment and the activation of anti-tumor immune responses, enhancing the overall effectiveness of the treatment. Biomarkers can offer insights into the patient's immune response and outcomes, such as local tumor control, recurrence, overall survival, and progression-free survival. Identifying and validating such biomarkers can significantly impact clinical decision-making, leading to personalized treatment strategies and improved patient outcomes. This review provides a comprehensive overview of the current state of research on potential biomarkers for predicting immune response and outcomes in lung cancer patients undergoing thermal ablation, including their potential role in lung cancer management, and the challenges and future directions.

Heterogeneity of Glycolytic Phenotype Determined by 18F-FDG PET/CT Using Coefficient of Variation in Patients with Advanced Non-Small Cell Lung Cancer

We investigated the role of Coefficient of Variation (CoV), a first-order texture parameter derived from ¹⁸F-FDG PET/CT, in the prognosis of Non-Small Cell Lung Cancer (NSCLC) patients. Eighty-four patients with advanced NSCLC who underwent ¹⁸F-FDG PET/CT before therapy were retrospectively studied. SUVmax, SUVmean, CoV, total Metabolic Tumor Volume (MTV_TOT) and whole-body Total Lesion Glycolysis (TLG_WB) were determined by an automated contouring program (SUV threshold at 2.5). We analyzed 194 lesions: primary tumors (n = 84), regional (n = 48) and non-regional (n = 17) lymph nodes and metastases in liver (n = 9), bone (n = 23) and other sites (n = 13); average CoVs were 0.36 ± 0.13, 0.36 ± 0.14, 0.42 ± 0.18, 0.30 ± 0.14, 0.37 ± 0.17, 0.34 ± 0.13, respectively. No significant differences were found between the CoV values among the different lesion categories. Survival analysis included age, gender, histology, stage, MTV_TOT, TLG_WB and imaging parameters derived from primary tumors. At univariate analysis, CoV (p = 0.0184), MTV_TOT (p = 0.0050), TLG_WB (p = 0.0108) and stage (p = 0.0041) predicted Overall Survival (OS). At multivariate analysis, age, CoV, MTV_TOT and stage were retained in the model (p = 0.0001). Patients with CoV > 0.38 had significantly better OS than those with CoV ≤ 0.38 (p = 0.0143). Patients with MTV_TOT ≤ 89.5 mL had higher OS than those with MTV_TOT > 89.5 mL (p = 0.0063). Combining CoV and MTV_TOT, patients with CoV ≤ 0.38 and MTV_TOT > 89.5 mL had the worst prognosis. CoV, by reflecting the heterogeneity of glycolytic phenotype, can predict clinical outcomes in NSCLC patients.

Novel computational biology modeling system can accurately forecast response to neoadjuvant therapy in early breast cancer

BACKGROUND

Generalizable population-based studies are unable to account for individual tumor heterogeneity that contributes to variability in a patient's response to physician-chosen therapy. Although molecular characterization of tumors has advanced precision medicine, in early-stage and locally advanced breast cancer patients, predicting a patient's response to neoadjuvant therapy (NAT) remains a gap in current clinical practice. Here, we perform a study in an independent cohort of early-stage and locally advanced breast cancer patients to forecast tumor response to NAT and assess the stability of a previously validated biophysical simulation platform.

METHODS

A single-blinded study was performed using a retrospective database from a single institution (9/2014-12/2020). Patients included: ≥ 18 years with breast cancer who completed NAT, with pre-treatment dynamic contrast enhanced magnetic resonance imaging. Demographics, chemotherapy, baseline (pre-treatment) MRI and pathologic data were input into the TumorScope Predict (TS) biophysical simulation platform to generate predictions. Primary outcomes included predictions of pathological complete response (pCR) versus residual disease (RD) and final volume for each tumor. For validation, post-NAT predicted pCR and tumor volumes were compared to actual pathological assessment and MRI-assessed volumes. Predicted pCR was pre-defined as residual tumor volume ≤ 0.01 cm³ (≥ 99.9% reduction).

RESULTS

The cohort consisted of eighty patients; 36 Caucasian and 40 African American. Most tumors were high-grade (54.4% grade 3) invasive ductal carcinomas (90.0%). Receptor subtypes included hormone receptor positive (HR+)/human epidermal growth factor receptor 2 positive (HER2+, 30%), HR+/HER2- (35%), HR-/HER2+ (12.5%) and triple negative breast cancer (TNBC, 22.5%). Simulated tumor volume was significantly correlated with post-treatment radiographic MRI calculated volumes (r = 0.53, p = 1.3 × 10^-7, mean absolute error of 6.57%). TS prediction of pCR compared favorably to pathological assessment (pCR: TS n = 28; Path n = 27; RD: TS n = 52; Path n = 53), for an overall accuracy of 91.2% (95% CI: 82.8% - 96.4%; Clopper-Pearson interval). Five-year risk of recurrence demonstrated similar prognostic performance between TS predictions (Hazard ratio (HR): - 1.99; 95% CI [- 3.96, - 0.02]; p = 0.043) and clinically assessed pCR (HR: - 1.76; 95% CI [- 3.75, 0.23]; p = 0.054).

CONCLUSION

We demonstrated TS ability to simulate and model tumor in vivo conditions in silico and forecast volume response to NAT across breast tumor subtypes.

Volumetric parameters of the primary tumor and whole-body tumor burden derived from baseline 18F-FDG PET/CT can predict overall survival in non-small cell lung cancer patients: initial results from a single institution

BACKGROUND

Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are volumetric parameters derived from ¹⁸F-FDG PET/CT, suggested to have a prognostic value in cancer patients. Our study aimed to test whether these volumetric parameters of the primary tumor and whole-body tumor burden (WBTB) can predict overall survival (OS) in non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

Thirty biopsy-proven NSCLC patients who had not begun anti-tumor therapy were included in this prospective study. A baseline ¹⁸F-FDG PET/CT study was acquired. Scans were interpreted visually and semi-quantitatively by drawing a 3D volume of interest (VOI) over the primary tumor and all positive lesions to calculate metabolic, volumetric parameters, and WBTB. The PET parameters were used to stratify patients into high- and low-risk categories. The overall survival was estimated from the date of scanning until the date of death or last follow-up.

RESULTS

At a median follow-up of 22.73 months, the mean OS was shorter among patients with higher tu MTV and tu TLG and high WBTB. High WB TLG was independently associated with the risk of death (p < 0.025). Other parameters, e.g., SUV_max, SUV_peak, and SUV_mean, were not predictive of outcomes in these patients.

CONCLUSION

In patients with NSCLC, tu MTV, tu TLG, and WBTB determined on initial staging ¹⁸F-FDG PET/CT seems to be a strong, independent imaging biomarker to predict OS, superior to the clinical assessment of the primary tumor. The WB TLG was found to be the best predictor of OS.

Does [18F]F-FDG-PET/MRI add metabolic information to magnetic resonance image in childhood-onset Takayasu’s arteritis patients? A multicenter case series

Background

The observation that 2-deoxy-2[18F]fluoro-D-glucose-positron emission tomography/magnetic resonance imaging ([18F]F-FDG-PET/MRI) revealed high-grade arterial wall FDG uptake, without arterial wall thickening with contrast-enhancement, in a considerable number of c-TA patients in our previous study, encouraged us to compare patients with both PET and MR angiography (MRA) positives, with those with PET positive but MRA negative. Our aim was to evaluate the relevance of these two imaging modalities together.

Methods

A three-center cross-sectional study with 17 patients who fulfilled the EULAR/PRINTO/PReS criteria for c-TA and who underwent [18F]F-FDG-PET/MRI was previously performed. Herein we compared patients/vessels with positive PET (arterial wall 18F-FDG uptake higher than liver) and positive MRA (arterial wall thickening with contrast-enhancement)—group 1, with those with positive PET but negative MRA—group 2.

Results

Median disease duration of 17 c-TA patients was 10.4 years. Nine patients were classified as group 1 and six as group 2. Median of metabolic inflammatory volume (MIV) of all arterial segments was significantly higher in group 1 (2346 vs. 1177 cm3; p = 0.036). Fifty-four (19%) from 284 available arterial segments presented positive findings in vessel wall in one or both images. Positive findings were concordant between PET and MRA in only 13% arterial segments (group 1); most changes (28–59.6%) that were discordant between both images, were positive in PET and negative in MRA (group 2).

Conclusion

Our study demonstrated that [18F]F-FDG-PET/MRI added information about inflammation in vessel wall of c-TA patients. Prospective multicenter studies are needed in order to get solid data to guide immunosuppressive tapering and withdrawal.

Metabolic tumor volume predicts long-term survival after transplantation for unresectable colorectal liver metastases: 15 years of experience from the SECA study

OBJECTIVE

To report 15 years of experience with metabolic tumor volume (MTV) of liver metastases from the preoperative 18F-FDG PET/CT to predict long-term survival after liver transplantation (LT) for unresectable colorectal liver metastases (CRLM).

METHODS

The preoperative 18F-FDG PET/CT from all SECA 1 and 2 patients was evaluated. MTV was obtained from all liver metastases. The patients were divided into one group with low MTV (< 70 cm3) and one group with high MTV (> 70 cm3) based on a receiver operating characteristic analysis. Overall survival (OS), disease-free survival (DFS) and post recurrence survival (PRS) for patients with low versus high MTV were compared using the Kaplan-Meier method and log rank test. Clinopathological features between the two groups were compared by a nonparametric Mann-Whitney U test for continuous and Fishers exact test for categorical data.

RESULTS

At total of 40 patients were included. Patients with low MTV had significantly longer OS (p < 0.001), DFS (p < 0.001) and PRS (p = 0.006) compared to patients with high values. The patients with high MTV had higher CEA levels, number of liver metastases, size of the largest liver metastasis, N-stage, number of chemotherapy lines and more frequently progression of disease at LT compared to the patients with low MTV.

CONCLUSION

MTV of liver metastases is highly predictive of long-term OS, DFS and PRS after LT for unresectable CRLM and should be implemented in risk stratification prior to LT.

Radiomic and Volumetric Measurements as Clinical Trial Endpoints—A Comprehensive Review

Simple Summary

The extraction of quantitative data from standard-of-care imaging modalities offers opportunities to improve the relevance and salience of imaging biomarkers used in drug development. This review aims to identify the challenges and opportunities for discovering new imaging-based biomarkers based on radiomic and volumetric assessment in the single-site solid tumor sites: breast cancer, rectal cancer, lung cancer and glioblastoma. Developing approaches to harmonize three essential areas: segmentation, validation and data sharing may expedite regulatory approval and adoption of novel cancer imaging biomarkers.

Abstract

Clinical trials for oncology drug development have long relied on surrogate outcome biomarkers that assess changes in tumor burden to accelerate drug registration (i.e., Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) criteria). Drug-induced reduction in tumor size represents an imperfect surrogate marker for drug activity and yet a radiologically determined objective response rate is a widely used endpoint for Phase 2 trials. With the addition of therapies targeting complex biological systems such as immune system and DNA damage repair pathways, incorporation of integrative response and outcome biomarkers may add more predictive value. We performed a review of the relevant literature in four representative tumor types (breast cancer, rectal cancer, lung cancer and glioblastoma) to assess the preparedness of volumetric and radiomics metrics as clinical trial endpoints. We identified three key areas—segmentation, validation and data sharing strategies—where concerted efforts are required to enable progress of volumetric- and radiomics-based clinical trial endpoints for wider clinical implementation.

18F-FDG PET/CT-Based Prognostic Survival Model After Surgery for Head and Neck Cancer

The aims of this multicenter study were to identify clinical and preoperative PET/CT parameters predicting overall survival (OS) and distant metastasis-free survival (DMFS) in a cohort of head and neck squamous cell carcinoma patients treated with surgery, to generate a prognostic model of OS and DMFS, and to validate this prognostic model with an independent cohort. Methods: A total of 382 consecutive patients with head and neck squamous cell carcinoma, divided into training (n = 318) and validation (n = 64) cohorts, were retrospectively included. The following PET/CT parameters were analyzed: clinical parameters, SUV_max, SUV_mean, metabolic tumor volume (MTV), total lesion glycolysis, and distance parameters for the primary tumor and lymph nodes defined by 2 segmentation methods (relative SUV_max threshold and absolute SUV threshold). Cox analyses were performed for OS and DMFS in the training cohort. The concordance index (c-index) was used to identify highly prognostic parameters. These prognostic parameters were externally tested in the validation cohort. Results: In multivariable analysis, the significant parameters for OS were T stage and nodal MTV, with a c-index of 0.64 (P < 0.001). For DMFS, the significant parameters were T stage, nodal MTV, and maximal tumor-node distance, with a c-index of 0.76 (P < 0.001). These combinations of parameters were externally validated, with c-indices of 0.63 (P < 0.001) and 0.71 (P < 0.001) for OS and DMFS, respectively. Conclusion: The nodal MTV associated with the maximal tumor-node distance was significantly correlated with the risk of DMFS. Moreover, this parameter, in addition to clinical parameters, was associated with a higher risk of death. These prognostic factors may be used to tailor individualized treatment.

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

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

Clinical Perspectives for 18F-FDG PET Imaging in Pediatric Oncology: Μetabolic Tumor Volume and Radiomics

Pediatric cancer, although rare, requires the most optimized treatment approach to obtain high survival rates and minimize serious long-term side effects in early adulthood. 18F-FDG PET/CT is most helpful and widely used in staging, recurrence detection, and response assessment in pediatric oncology. The well-known 18F-FDG PET metabolic indices of metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) have already revealed an independent significant prognostic value for survival in oncologic patients, although the corresponding cut-off values remain study-dependent and not validated for use in clinical practice. Advanced tumor “radiomic” analysis sheds new light into these indices. Numerous patterns of texture 18F-FDG uptake features can be extracted from segmented PET tumor images due to new powerful computational systems supporting complex “deep learning” algorithms. This high number of “quantitative” tumor imaging data, although not decrypted in their majority and once standardized for the different imaging systems and segmentation methods, could be used for the development of new “clinical” models for specific cancer types and, more interestingly, for specific age groups. In addition, data from novel techniques of tumor genome analysis could reveal new genes as biomarkers for prognosis and/or targeted therapies in childhood malignancies. Therefore, this ever-growing information of “radiogenomics”, in which the underlying tumor “genetic profile” could be expressed in the tumor-imaging signature of “radiomics”, possibly represents the next model for precision medicine in pediatric cancer management. This paper reviews 18F-FDG PET image segmentation methods as applied to pediatric sarcomas and lymphomas and summarizes reported findings on the values of metabolic and radiomic features in the assessment of these pediatric tumors.

Progress and future prospective of FDG-PET/CT imaging combined with optimized procedures in lung cancer: toward precision medicine

With a 5-year overall survival of approximately 20%, lung cancer has always been the number one cancer-specific killer all over the world. As a fusion of positron emission computed tomography (PET) and computed tomography (CT), PET/CT has revolutionized cancer imaging over the past 20 years. In this review, we focused on the optimization of the function of 18F-flurodeoxyglucose (FDG)-PET/CT in diagnosis, prognostic prediction and therapy management of lung cancers by computer programs. FDG-PET/CT has demonstrated a surprising role in development of therapeutic biomarkers, prediction of therapeutic responses and long-term survival, which could be conducive to solving existing dilemmas. Meanwhile, novel tracers and optimized procedures are also developed to control the quality and improve the effect of PET/CT. With the continuous development of some new imaging agents and their clinical applications, application value of PET/CT has broad prospects in this area.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

18F-FDG PET/CT for primary staging of patients with testicular germ cell tumors: the predictors of 18F-FDG PET positivity and prognostic value of PET derived metabolic parameters

PURPOSE

The aim of this study was to investigate the role of histopathologic and biochemical parameters for predicting F-FDG PET positivity for primary staging in patients with newly diagnosed testicular germ cell tumors (TGCT). It was also aimed to evaluate the prognostic value of PET derived metabolic features in this patient group.

MATERIALS AND METHODS

The imaging findings of 51 patients who were diagnosed as TGCT and underwent F-FDG PET/CT for primary staging after surgery between 2009 and 2019 were evaluated retrospectively. In terms of the presence of F-FDG uptake consistent with metastasis, the patients were divided into two groups as 'PET-positive' and 'PET-negative'. In 'PET-positive' patients, highest maximum standardized uptake values of metastatic lesions, whole-body total metabolic tumor volumes (wb-TMTV) and total lesion glycolysis (wb-TLG) were extracted. Pathological tumor types, pathological T stages (pT), tumor marker (TM) levels (AFP, hCG, LDH) after orchiectomy and overall survival (OS) times in months were also recorded. The predictive value of variables for OS was evaluated using the Kaplan-Meier survival analysis.

RESULTS

PET positivity was observed in 28% of pT1 and in 83.3% in pT2-T3 tumors (P < 0.001). In the logistic regression analysis to predict 'PET positivity', pT stage and ≥2 elevated TMs were found as independent significant predictors. Survival analysis demonstrated that wb-TMTV, wb-TLG and TMs were significantly associated with prognosis for OS.

CONCLUSION

The likelihood of PET positivity was significantly higher in patients with elevated TMs and pT2-T3 stages compared to those with normal TMs and pT1 tumors. PET derived quantitative metabolic-volumetric parameters can be used as biomarkers to identify patients with poor prognosis in TGCT.

A novel model to assess disease activity in Takayasu arteritis based on 18F-FDG-PET/CT: a Chinese cohort study

OBJECTIVE

To investigate the utility of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) in assessing disease activity in Takayasu arteritis (TA).

METHODS

Ninety-one patients with TA, were recruited from a Chinese cohort. Clinical data, acute-phase reactants (APRs), and 18F-FDG-PET/CT findings were simultaneously recorded. The value of using 18F-FDG-PET/CT to identify active disease was evaluated, using erythrocyte sedimentation rate (ESR) as a reference. Disease activity assessment models were constructed and concordance index (C-index), net reclassification index (NRI), and integrated discrimination index (IDI) were evaluated to compare the benefits of the new modes with ESR and Kerr score.

RESULTS

In total, 64 (70.3%) cases showed active disease. Higher levels of ESR and CRP, and lower interleukin (IL)-2R levels, were observed in active cases. 18F-FDG-PET/CT parameters, including SUVmean, SUVratio1, SUVratio2, sum of SUVmean, and sum of SUVmax, were significantly higher in active disease groups. The C index threshold of ESR to indicate active disease was 0.78 (95% CI: 0.69-0.88). The new activity assessment model combining ESR, sum of SUVmean, and IL-2R showed significant improvement in C index over the ESR method (0.96 vs 0.78, p < 0.01; NRI 1.63, p < 0.01; and IDI 0.48, p < 0.01). The new model also demonstrated modest superiority to Kerr score assessment (0.96 vs 0.87, p = 0.03; NRI 1.19, p < 0.01; and IDI 0.33 p < 0.01).

CONCLUSIONS

A novel 18F-FDG-PET/CT-based method that involves combining the sum of SUVmean with ESR score and IL-2R levels demonstrated superiority in identifying active TA compared with conventional methods.

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

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

The Predictive Value of Baseline Volumetric PET/CT Parameters on Treatment Response and Prognosis in Locally Advanced Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy

PURPOSE

To investigate the prognostic effects of baseline volumetric PET/CT parameters including the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) on treatment response and prognosis in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (NACRT).

METHODS

Between 2015 and 2018, 51 patients with LARC treated with NACRT followed by surgery were included in this retrospective study. Patients were divided into 2 groups by tumor regression grade (TRG) as follows: group I = TRG 1 (no detectable cancer cells) + TRG 2 (single cells and/or small groups of cancer cells) and group II = TRG3 (residual tumor outgrown by fibrosis) + TRG 4 (remarkable fibrosis outgrown by tumor cells) + TRG 5 (no fibrosis with extensive residual cancer).

RESULTS

Of the 51 patients, 34 (66.7%) were male. The median age was 55 (range, 37-78) years. According to TRG status, 14 (27.4%) patients were in group I and 37 (72.6%) patients were in group II. The area under the curve (95% CI) was 0.749 (0.593-0.905) in the ROC curve plotted for MTV. The cut-off value for MTV was 12, with 70% sensitivity and 65% specificity. MTV was ≥ 12 in 32 (62.8%) patients. MTV and TLG values were significantly different between groups I and II, whereas there was no significant difference between the groups in terms of SUVmax values (p = 0.006, p = 0.033, and p = 0.673, respectively). The disease-free survival was not reached in patients with MTV < 12 vs. 20 months in those with MTV ≥ 12 (p = 0.323). In multivariate analysis, MTV (OR, 95% Cl, 5.00 [1.17-21.383]) was found to be the factor that affected pathological complete response.

CONCLUSION

In LARC treated with NACRT, MTV prior to treatment can help predict the response to treatment.

PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients

Despite the recent advances in lung cancer biology, molecular pathology, and treatment, this malignancy remains the leading cause of cancer-related death worldwide and non-small cell lung cancer (NSCLC) is the most common form found at diagnosis. Accurate staging of the disease is a fundamental prognostic factor that correctly predicts progression-free (PFS) and overall survival (OS) of NSCLC patients. However, outcome of patients within each TNM staging group can change widely highlighting the need to identify additional prognostic biomarkers to better stratify patients on the basis of risk. 18F-FDG PET/CT plays an essential role in staging, evaluation of treatment response, and tumoral target delineation in NSCLC patients. Moreover, a number of studies showed the prognostic role of imaging parameters derived from PET images, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). These parameters represent three-dimensional PET-based measurements providing information on both tumor volume and metabolic activity and previous studies reported their ability to predict OS and PFS of NSCLC patients. This review will primarily focus on the studies that showed the prognostic and predictive role of MTV and TLG in NSCLC patients, addressing also their potential utility in the new era of immunotherapy of NSCLC.

Utility of PET/CT in the diagnosis and staging of lung cancer after ecobronchoscopy in mining population

INTRODUCTION

Positron emission tomography (PET) with computerized axial tomography (CT) in a single device is known as PET/CT. It has been widely documented and validated, and it is currently a core part of the diagnosis and staging of lung cancer. However, its reliability has not been analysed in specific populations. The objective of this study is to determine the usefulness of PET/CT in patients exposed to mining activities in which an endobronchial ultrasound (EBUS) has been performed for the diagnosis and/or staging of lung cancer.

PATIENTS AND METHODS

With a prospective and real-time database, all the patients who had undergone an EBUS with suspicion of lung cancer and who had previously undergone a PET/CT were selected. The observation unit was the lymph node and, based on their history of exposure to mining activities, the sample was divided into two categories, group 1: not exposed; and group 2: exposed. In each group, and with the results from anatomical pathology as a dependent variable, logistic models were established to look for independent risk factors for malignancy.

RESULTS

In group 1, lymph nodes larger than 1 cm and PET/CT uptake with maximum standardized uptake value (SUVmax) over 2.5 were independent risk factors for malignancy. However, in group 2 (exposed patients), none of those factors were predictors for malignancy.

DISCUSSION

In the population of individuals with occupational exposure to mining, PET/CT is an imaging technique with diagnostic limitations for lung cancer.

COV is a readily available quantitative indicator of metabolic heterogeneity for predicting survival of patients with early and locally advanced NSCLC manifesting as central lung cancer

OBJECTIVES

The aim of our study was to investigate the value of a simple metabolic heterogeneity parameter, COV (coefficient of variation), by 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in the prognosis prediction of central lung cancer in early and locally advanced non-small-cell lung cancer (NSCLC).

METHODS

Seventy-three patients with NSCLC manifesting as central lung cancer were included retrospectively, and we used the COV to evaluate metabolic heterogeneity. Univariate and multivariate analyses were used to evaluate the predictive value in terms of overall survival (OS) and progression-free survival (PFS).

RESULT

For all 73 patients with pathologically confirmed NSCLC, 69.9 % had SCC, and 30.1 % had ADC or other types of NSCLC. The COV was a statistically significant factor in the univariate analysis for the OS rate. The optimal cut-off value was 23.1366, with sensitivity = 0.737 and specificity = 0.771. The COV values were dichotomized by this value and included with atelectasis in the Cox multivariate analysis. Both COV and atelectasis were independent risk factors for OS as follows: for COV (HR, 3.162, P = 0.0002), the 2-year OS rate was 62.5 % and 26.9 % in the low and high COV groups, respectively. For atelectasis (HR 2.047, P = 0.041), the 2-year OS rate was 30.6 % and 65.2 % in the groups with and without atelectasis, respectively (P = 0.017). For PFS, only COV (HR, 2.636, P = 0.001) was a significant predictor. The 2-year PFS rate was 29.7 % in the low COV group and 8% in the high COV group.

CONCLUSION

The pre-treatment metabolic heterogeneity parameter COV is a simple and easy way to predict the OS and PFS of patients with NSCLC manifesting as central lung cancer. Therefore, COV plays an important role in prognostic risk classification in NSCLC. The presence of atelectasis could also be a risk factor for poor prognosis of OS.