Evaluation of the effect of PET/CT Fluorodeoxyglucose inclusion on mortality and survival in operated thymoma patients.

PURPOSE: In recent years, the use of fluorodeoxyglucose PET-computed tomography (PET-CT) has become widespread to evaluate the diagnosis, metabolism, stage and distant metastases of thymoma. In this study, it was aimed to investigate the connection of malignancy potential, survival and maximum standardized uptake value (SUV max ) measured by PET-CT before surgery according to the histological classification of the WHO in patients operated for thymoma. In addition, the predictive value of the Glasgow prognostic score (GPS) generated by C-reactive protein (CRP) and albumin values on recurrence and survival was investigated and its potential as a prognostic biomarker was evaluated. METHODS: Forty-five patients who underwent surgical resection for thymoma and were examined with PET-CT in the preoperative period between January 2010 and January 2022 were included in the study. The relationship between WHO histological classification, tumor size and SUV max values on PET-CT according to TNM classification of retrospectively analyzed corticoafferents were evaluated. Preoperative albumin and CRP values were used to determine GPS. RESULTS: The cutoff value for SUV max was found to be 5.65 in the patients and the overall survival rate of low-risk (<5.65) and high-risk (>5.65) patients was compared according to the SUV max threshold value (5.65) and found to be statistically significant. In addition, the power of PET/CT SUV max value to predict mortality (according to receiver operating characteristics analysis) was statistically significant ( P  = 0.048). Survival expectancy was 127.6 months in patients with mild GPS (O points), 96.7 months in patients with moderate GPS (1 point), and 25.9 months in patients with severe GPS (2 points). CONCLUSION: PET/CT SUV max values can be used to predict histological sub-type in thymoma patients, and preoperative SUV max and GPS are parameters that can provide information about survival times and mortality in thymoma patients.

Comparison of Alectinib/Crizotinib Data in First-Line Therapy in Patients with Anaplastic LymphomakinasePositive Nonsmall Cell Lung Carcinoma with Poor Prognostic Features for Alectinib.

OBJECTIVE: Alectinib has a much better central nervous system transmission than crizotinib in patients diagnosed with anaplastic lymphoma kinase mutation-positive nonsmall cell lung carcinoma. We aimed to investigate alectinib's efficacy in the treatment and its place in the first-line treatment and report our real-life data. MATERIAL AND METHODS: The data of 38 patients who were diagnosed with anaplastic lymphoma kinase-positive nonsmall cell lung carcinoma in our clinic between 2016 and 2021, who did not receive any treatment before were retrospectively analyzed. RESULTS: Of the 19 patients who received alectinib, 14 had multiple, and 6 had pretreatment brain metastases. No newly emerging brain metastases were detected during the treatment period. The progression-free survival of patients was 23.5 ± 4.2 months, and overall survival was 24.6 ± 4.1 months. Progression was observed in 10 (52.6%) patients. Of the 19 patients who received crizotinib, 7 had multiple metastases, and brain metastases were detected in 1 patient before treatment and 6 patients during the treatment period. Progression-free survival of crizotinib patients was 17.1 ± 4.8 months and their overall survival was 26.5 ± 6.1 months. Progression was observed in 17 (89.5%) patients. The second line of alectinib could be given to 8 of these patients. Overall survival after second-line treatment of alectinib was 18.2 ± 7.0 months. Overall survival of the patients who could not receive second-line treatment of alectinib was 4.0 ± 2.0 months. CONCLUSION: The progression rate was lower in alectinib than the crizotinib patients, although there were more patients with multiple metastases and brain metastases in the alectinib arm.

Machine learning approach using 18 F-FDG PET-based radiomics in differentiation of lung adenocarcinoma with bronchoalveolar distribution and infection.

OBJECTIVE: In this study, we aimed to evaluate the role of 18F-fluorodeoxyglucose PET/computerized tomography ( 18 F-FDG PET/CT)-based radiomic features in the differentiation of infection and malignancy in consolidating pulmonary lesions and to develop a prediction model based on radiomic features. MATERIAL AND METHODS: The images of 106 patients who underwent 18 F-FDG PET/CT of consolidated lesions observed in the lung between January 2015 and July 2020 were evaluated using LIFEx software. The region of interest of the lung lesions was determined and volumetric and textural features were obtained. Clinical and radiomic data were evaluated with machine learning algorithms to build a model. RESULTS: There was a significant difference in all standardized uptake value (SUV) parameters and 26 texture features between the infection and cancer groups. The features with a correlation coefficient of less than 0.7 among the significant features were determined as SUV mean , GLZLM_SZE, GLZLM_LZE, GLZLM_SZLGE and GLZLM_ZLNU. These five features were analyzed in the Waikato Environment for Knowledge Analysis program to create a model that could distinguish infection and cancer groups, and the model performance was found to be the highest with logistic regression (area under curve, 0.813; accuracy, 75.7%). The sensitivity and specificity values of the model in distinguishing cancer patients were calculated as 80.6 and 70.6%, respectively. CONCLUSIONS: In our study, we created prediction models based on radiomic analysis of 18 F-FDG PET/CT images. Texture analysis with machine learning algorithms is a noninvasive method that can be useful in the differentiation of infection and malignancy in consolidating lung lesions in the clinical setting.

Volumetric and radiomics assessment of lesions with incidental [18F]FDG uptake in the colon: a retrospective radiomics study.

BACKGROUND: To evaluate the power of volumetric and radiomic tissue data obtained from the images of the lesions in predicting the histopathological diagnosis in patients with incidental colorectal focal FDG uptake detected by [18F]FDG PET/CT imaging. METHODS: Electronic records of patients who underwent [18F]FDG PET/CT for various malignancies between January 2016 and January 2020 were retrospectively reviewed. 98 lesions of 80 patients with colonoscopic and histopathological results were included in the study. The lesions were divided into 3 groups according to their histopathological diagnosis as benign, premalign and malign. [18F]FDG PET/CT images obtained from the patients were evaluated using LIFEx software. Volumetric and radiomic textural features were obtained by establishing the region of interest (ROI) of the primary tumor. The [18F]FDG PET/CT parameters of the lesions were compared between the groups. In order to evaluate the predictive power of the parameters obtained with [18F]FDG PET/CT, the area under the curve (AUC), sensitivity and selectivity values, negative and positive predictive values were calculated by ROC analysis. RESULTS: The volumetric and radiomic tissue analysis parameters of the lesions in the malignant group were significantly different when compared to the other groups. Our study showed that SUVmax value can be used as a marker in the diagnosis of pathological malignancy (AUC=0.737 and P=0.001 95% CI: 0.619-0.855). Contrast and entropy parameters of GLCM matrix, which are radiomic texture features, were found to be used in the prediction of malignancy (AUC=0.685 and AUC=0.692, P=0.041 and P=0.035, respectively. Similarly, parameters of NLGDM, GLRLM and GLZLM matrices were shown to have statistically significant diagnostic values in predicting malignancy. However, no superiority of these parameters over each other in predicting malignancy was observed. CONCLUSIONS: In our study, the parameters of radiomic textural analysis together with volumetric parameters have been shown to have diagnostic value in noninvasively determining lesion characterization and defining tissue in lesions with incidental colorectal focal FDG uptake detected by [18F]FDG PET/CT imaging.

Evaluation of survival of the patients with metastatic rectal cancer by staging 18F-FDG PET/CT radiomic and volumetric parameters.

OBJECTIVE: The aim of this study is to predict the prognosis in patients with metastatic rectal cancer (mRC) by obtaining a model with machine learning (ML) algorithms through volumetric and radiomic data obtained from baseline 18-Fluorine Fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) images. METHODS: Sixty-two patients with mRC who underwent 18F-FDG PET/CT imaging for staging between January 2015 and January 2021 were evaluated using LIFEx software. The volume of interest (VOI) of the primary tumor was generated and volumetric and textural features were obtained from this VOI. In addition, metabolic tumor volume (tMTV) and total lesion glycolysis (tTLG) values of tumor foci in the whole body. Clinical and radiomic data were evaluated with ML algorithms to create a model that predicts survival. Significant associations between these features and 1-year and 2-year survival were investigated. RESULTS: Random forest algorithm was the most successful algorithm in predicting 2-year survival (AUC: 0.843, PRC: 0.822, and MCC: 0.583). The model obtained with this algorithm was able to predict 49 patients with 79.03% accuracy. While tMTV and tTLG values were successful in predicting 1-year survival (p: 0.002 and 0.007, respectively), texture characteristics from the primary tumor did not show a significant relationship with 1-year survival. CONCLUSIONS: In addition to the important role of 18F-FDG PET/CT in staging patients with mRC, this study shows that it is possible to predict survival with ML methods, with parameters obtained using texture analysis from the primary tumor and whole body volumetric parameters.

The prognostic relationship of 18F-FDG PET/CT metabolic and volumetric parameters in metastatic ALK + NSCLC.

OBJECTIVE: The aim of this study is to determine the role of metabolic and volumetric parameters obtained from 18Fluorine-Fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) imaging on progression-free survival (PFS) and overall survival (OS) in patients with advanced nonsquamous cell lung carcinoma (NSCLC) with anaplastic lymphoma kinase (ALK) rearrangement. METHODS: Pre and post-treatment PET/CT images of the ALK + NSCLC patients between January 2015 and July 2020 were evaluated. The highest standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) values were obtained from pre-tyrosine kinase inhibitor (TKI) basal PET/CT (PETpre) and post-TKI PET/CT (PETpost) images. Total MTV (tMTV) and total TLG (tTLG) values were calculated by summing MTV and TLG values in all tumor foci. The change (Δ) in pSUVmax, pMTV, pTLG, tMTV and tTLG before and after treatment was calculated.The relationship of these parameters with OS and PFS was analyzed. RESULTS: tTLGpre, tMTVpre, pTLGpre, pMTVpre, ∆SUVmax, ∆tMTV and ∆tTLG values were found to be associated with OS; ∆tMTV, ∆tTLG, tTLGpre, tMTVpre, pTLGpre and pMTVpre were associated with PFS. The cutoff values in both predicting OS and PFS were calculated as -31.6 and 391.1 for ∆tMTV and tTLGpre, respectively. In Cox regression analysis, ∆tMTV and stage for OS and ∆tMTV and tTLGpre for PFS were obtained as prognostic factors. CONCLUSIONS: Metabolic and volumetric parameters, especially TLG values in the whole body before treatment and change in whole body MTV value, obtained from PET/CT may be useful in predicting prognosis and determining treatment strategies for patients with advanced ALK + NSCLC.

Comparison of 18 F-FDG PET/CT and 68 Ga-FAPI-04 PET/CT in patients with non-small cell lung cancer.

AIM: In this study, we aimed to compare the diagnostic accuracy of 18 F-fluorodeoxyglucose ( 18 F-FDG) and Gallium-68 labeled fibroblast activator protein inhibitor ( 68 Ga-FAPI)-04 PET/CT in the tumor-node-metastasis (TNM) staging of patients with nonsmall cell lung cancer (NSCLC) and investigate whether adenocarcinoma (ADC) and squamous cell cancer (SCC) exhibit different uptake patterns on 68 Ga-FAPI-04 PET/CT. MATERIALS AND METHOD: Twenty-nine patients with a histopathologically-confirmed diagnosis of NSCLC, who had no history of previous radiation therapy or chemotherapy and underwent 18 F-FDG PET/CT and 68 Ga-FAPI-04 PET/CT imaging between January 2021 and December 2021 were included in this retrospective study. Staging was performed using the 8th edition of the TNM staging system on both 18 F-FDG PET/CT and 68 Ga-FAPI-04 PET/CT images. Standardized uptake value (SUV) max and tumor-to-background ratios (TBR) were calculated on primary lesions and metastases. RESULTS: There was no statistically significant difference in primary lesions in terms of SUV max and TBR values. However, 68 Ga-FAPI-04 PET/CT was significantly superior to 18 F-FDG PET/CT in terms of the number of lymph nodes and bone metastases revealed. The SUV max and TBR values of lymph nodes, hepatic lesions and bone lesions were significantly higher on 68 Ga-FAPI-04 PET/CT than on 18 F-FDG PET/CT. 68 Ga-FAPI-04 PET/CT changed the disease stage of three patients (10.9%). The diagnostic accuracy of 68 Ga-FAPI-04 PET/CT was 100%, whereas the diagnostic accuracy of 18 F-FDG PET/CT was 89.6% ( P = 0.250). CONCLUSION: Although 68 Ga-FAPI-04 PET/CT detected more lesions and higher diagnostic accuracy than 18 F-FDG PET/CT in NSCLC, neither method was statistically superior to each other in terms of diagnostic accuracy in TNM staging.

IMPORTANCE of PRETREATMENT 18F-FDG PET/CT TEXTURE ANALYSIS in PREDICTING EGFR and ALK MUTATION in PATIENTS with NON-SMALL CELL LUNG CANCER.

OBJECTIVE: Identification of anaplastic lymphoma kinase (ALK) and epidermal growth factor receptor (EGFR) mutation types is of great importance before treatment with tyrosine kinase inhibitors (TKIs). Radiomics is a new strategy for noninvasively predicting the genetic status of cancer. We aimed to evaluate the predictive power of 18F-FDG PET/CT-based radiomic features for mutational status before treatment in non-small cell lung cancer (NSCLC) and to develop a predictive model based on radiomic features. METHODS: Images of patients who underwent 18F-FDG PET/CT for initial staging with the diagnosis of NSCLC between January 2015 and July 2020 were evaluated using LIFEx software. The region of interest (ROI) of the primary tumor was established and volumetric and textural features were obtained. Clinical data and radiomic data were evaluated with machine learning (ML) algorithms to create a model. RESULTS: For EGFR mutation prediction, the most successful machine learning algorithm obtained with GLZLM_GLNU and clinical data was Naive Bayes (AUC: 0.751, MCC: 0.347, acc: 71.4%). For ALK rearrangement prediction, the most successful machine learning algorithm obtained with GLCM_correlation, GLZLM_LZHGE and clinical data was evaluated as Naive Bayes (AUC: 0.682, MCC: 0.221, acc: 77.4%). CONCLUSIONS: In our study, we created prediction models based on radiomic analysis of 18F-FDG PET/CT images. Tissue analysis with ML algorithms are non-invasive methods for predicting ALK rearrangement and EGFR mutation status in NSCLC, which may be useful for targeted therapy selection in a clinical setting.

The Prognostic Value of 18F-FDG PET/CT Metabolic Parameters in Predicting Treatment Response Before EGFR TKI Treatment in Patients with Advanced Lung Adenocarcinoma.

Objectives: This study makes a retrospective examination of exploring the prognostic value of 18fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) related metabolic-volumetric variables, nutritional status, and immune and inflammatory markers on progression-free survival (PFS) and overall survival (OS) in advanced adenocarcinoma patients with positive epidermal growth factor receptor (EGFR) mutations undergoing EGFR tyrosine kinase inhibitor (TKI) therapy. Methods: A retrospective examination was made of patients diagnosed with lung adenocarcinoma who underwent 18F-FDG PET/CT imaging for staging maximum four weeks before starting treatment, between January 2015 and July 2020. Included in the study were 68 patients identified histopathologically to have locally advanced/metastatic EGFR mutation-positive adenocarcinoma, and who underwent EGFR TKI therapy. The laboratory data of the patients, obtained 15 days before imaging performed for PET/CT staging, were evaluated. Results: Metabolic tumor volume, modified Glasgow prognostic score and locally advanced disease were identified as independent prognostic parameters for PFS (p=0.004, p=0.029, p=0.016, respectively). A univariate Cox regression analysis revealed albumin/alkaline phosphatase and tumor size to be significant parameters for prognosis (p=0.033, p=0.043, respectively). A multivariate Cox regression analysis revealed that none of the parameters were predictive or OS. Conclusion: The parameters of 18F-FDG PET/CT, especially the volumetric parameters, were found to be strong prognostic factors with statistical significance for predicting PFS. We believe that these parameters are important prognostic markers that should be evaluated together in the management and follow-up of patients with EGFR mutation-positive adenocarcinoma.

The prognostic value of preoperative PET/CT evaluation of maximum standardized uptake value in renal cell carcinomas.

AIM: The use of positron emission tomography (PET/CT) in kidney tumors has increased greatly in recent years. There have been few studies on the effect of SUVmax values detected by PET/CT on the mortality and survival estimation in patients with kidney tumors. In this study, it is hoped to contribute to the literature of research on survival and mortality estimations of kidney tumour patients through an evaluation of SUVmax values measured with PET/CT scan. MATERIAL AND METHODS: A retrospective review was made of the files of 21 patients newly-diagnosed with kidney tumor and with disease staging determined with PET/CT in the Nuclear medicine Department of Saglik Bilimleri University Diyarbakir Gazi Yasargil Training and Research Hospital between August 2007 and April 2012. The largest tumor seen on CT was considered as the tumour size and was stated in cm. The survival time was defined as the time from the date of PET/CT Imaging, which was taken into consideration while calculating the survival, and the date of death received from MERNIS (The Central Civil Registration System) or the final application date if the patient was alive. RESULTS: The lower the SUVmax value in the kidney tumour, the longer the survival time. The mortality risk of male patients was 12-fold higher than females and mortality increased 4-fold when SUVmax values were ≥ 4.5.Patients with a tumour on the right kidney had a longer survival time. With increasedage,survival time decreased. The SUVmax values and tumor size measured in left kidney tumors were higher than those measured in right kidney tumors. CONCLUSIONS: In the present study, it was concluded that the lower the SUVmax values and the smaller the tumour size, the longer the survival time. Mortality rates increased when SUVmax values were ≥ 4.5 (p=0.001).The use of PET/CT scan can be considered to contribute to mortality and survival estimations in patients with kidney tumor. KEY WORD: FDG, Renal cell Carcinoma, SUVmax.