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

Volumetric Evaluation of Staging 18F-FDG PET/CT Images in Patients with Esophageal Cancer

Objectives

The aim of this study was to evaluate the metastatic potential of primary tumor and survival in esophageal cancer (EC) patients by using metabolic tumor volume (MTV) and total lesion glycolysis (TLG) from the staging 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images. Another aim is to determine a tumor volume-based cut-off value to predict long-term survival.

Methods

Medical records of EC patients were retrospectively evaluated. Sixty-two patients with staging 18F-FDG PET/CT and at least five years of follow-up were included in the study. The region of interest to the primary tumor and all metastatic sites was created and MTV and TLG values of the primary tumor (MTVp, TLGp) and total tumor volume (MTVt and TLGt) values were obtained. The relationship between the obtained MTV and TLG values and short-time (one-year) and long time (five-year) survival was investigated.

Results

Significant factors on survival were determined as lymph node or distant metastasis (p=0.024, 0.008, respectively) at the staging PET/CT. A significant relationship between volumetric parameters of the primary tumor and total tumor burden (MTVp, TLGp, MTVwb and TLGwb) between survivors and non-survivors for one-year and five-year was detected. In receiver operating characteristics analysis, the most significant volumetric parameter was MTVwb, with area under curve 0.771 in estimated five-year survival. The best cut-off value was detected as 36.1 mL with 78% sensitivity and 75% specificity for MTVwb in determining long-term survivors.

Conclusion

Tumor burden in 18F-FDG PET/CT images at the time of staging of patients with EC will contribute to the prediction of long-term survivors.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

Simple Summary

PET/CT is an important staging modality in the baseline assessment of locally advanced esophageal squamous cell carcinoma. Accurate staging and response prediction in these patients is essential for management. The aim of this retrospective study was to assess the usefulness of ¹⁸F-FDG PET/CT radiomics features in predicting outcomes such as tumor and nodal categories, PET-based response to induction chemotherapy, progression-free survival, and overall survival. In a final cohort of 74 patients, we found that the developed radiomics models can predict these clinical and prognostic outcomes with reasonable accuracy, similar or better than those derived from conventional imaging. Future studies with a larger cohort would be helpful in establishing the significance of these models.

Abstract

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category—70.4%, 70.4%, and 81.5%, respectively; cN category—69.0%, 86.2%, and 86.2%, respectively; PET response—60.0%, 66.7%, and 70.0%, respectively; PFS—60.7%, 75.0%, and 75.0%, respectively; and OS—51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of ¹⁸F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Relationship between 18F-FDG PET/CT Semi-Quantitative Parameters and International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society Classification in Lung Adenocarcinomas

Objective

To investigate the relationship between ¹⁸F-FDG PET/CT semi-quantitative parameters and the International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) histopathologic classification, including histological subtypes, proliferation activity, and somatic mutations.

Materials and Methods

This retrospective study included 419 patients (150 males, 269 females; median age, 59.0 years; age range, 23.0–84.0 years) who had undergone surgical removal of stage IA–IIIA lung adenocarcinoma and had preoperative PET/CT data of lung tumors. The maximum standardized uptake values (SUVmax), background-subtracted volume (BSV), and background-subtracted lesion activity (BSL) derived from PET/CT were measured. The IASLC/ATS/ERS subtypes, Ki67 score, and epidermal growth factor/anaplastic lymphoma kinase (EGFR/ALK) mutation status were evaluated. The PET/CT semi-quantitative parameters were compared between the tumor subtypes using the Mann–Whitney U test or the Kruskal–Wallis test. The optimum cutoff values of the PET/CT semi-quantitative parameters for distinguishing the IASLC/ATS/ERS subtypes were calculated using receiver operating characteristic curve analysis. The correlation between the PET/CT semi-quantitative parameters and pathological parameters was analyzed using Spearman’s correlation. Statistical significance was set at p < 0.05.

Results

SUVmax, BSV, and BSL values were significantly higher in invasive adenocarcinoma (IA) than in minimally IA (MIA), and the values were higher in MIA than in adenocarcinoma in situ (AIS) (all p < 0.05). Remarkably, an SUVmax of 0.90 and a BSL of 3.62 were shown to be the optimal cutoff values for differentiating MIA from AIS, manifesting as pure ground-glass nodules with 100% sensitivity and specificity. Metabolic-volumetric parameters (BSV and BSL) were better potential independent factors than metabolic parameters (SUVmax) in differentiating growth patterns. SUVmax and BSL, rather than BSV, were strongly or moderately correlated with Ki67 in most subtypes, except for the micropapillary and solid predominant groups. PET/CT parameters were not correlated with EGFR/ALK mutation status.

Conclusion

As noninvasive surrogates, preoperative PET/CT semi-quantitative parameters could imply IASLC/ATS/ERS subtypes and Ki67 index and thus may contribute to improved management of precise surgery and postoperative adjuvant therapy.