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Background: Cardiovascular management and risk stratification of patients is an important issue in clinics. Patients who have experienced an adverse cardiac event are concerned for their future and want to know the survival probability. Methods: We trained eight state-of-the-art CNN models using polar maps of myocardial perfusion imaging (MPI), gender, lung/heart ratio, and patient age for 5-year survival prediction after an adverse cardiac event based on a cohort of 862 patients who had experienced adverse cardiac events and stress/rest MPIs. The CNN model outcome is to predict a patient's survival 5 years after a cardiac event, i.e., two classes, either yes or no. Results: The best accuracy of all the CNN prediction models was 0.70 (median value), which resulted from ResNet-50V2, using image as the input in the baseline experiment. All the CNN models had better performance after using frequency spectra as the input. The accuracy increment was about 7~9%. Conclusions: This is the first trial to use pure rest/stress MPI polar maps and limited clinical data to predict patients' 5-year survival based on CNN models and deep learning. The study shows the feasibility of using frequency spectra rather than images, which might increase the performance of CNNs. [ABSTRACT FROM AUTHOR]

ABSTRACT BACKGROUND The current study aimed to evaluate whether therapy-related changes occurred in brain metabolism at an earlier stage during the course of anticancer therapy. METHODS We recruited 14 non-diabetic male patients with newly diagnosed pharyngeal squamous cell carcinoma. We analyzed the patients' serial brain FDG PET/CT scans by SPM8 to establish whether any therapy-related changes had occurred in brain FDG metabolism, either during or after the course of therapy. RESULTS Decreased metabolism was noted during the anticancer therapy, displaying a symmetric pattern involving bilateral basal ganglia and bilateral occipital lobes. The decrease in FDG metabolism in these regions persisted after the anticancer therapy had terminated. However, relative recovery of the metabolism was noted in the bilateral occipital lobes, whereas further deterioration was noted in bilateral basal ganglia. CONCLUSIONS The current study revealed that unappreciable changes in brain metabolism can occur during the early course of anticancer therapy, and persist even after therapy has terminated. Although the exact mechanism remains unclear, these changes may be related to the systemic effects of chemotherapy or radiotherapy as well as subclinical cancer-related depressive or adjustment mood disorder. [ABSTRACT FROM AUTHOR]

This study aimed to explore efficient ways to diagnose bone metastasis early using bone scintigraphy images through negative mining, pre-training, the convolutional neural network, and deep learning. We studied 205 prostate cancer patients and 371 breast cancer patients and used bone scintigraphy data from breast cancer patients to pre-train a YOLO v4 with a false-positive reduction strategy. With the pre-trained model, transferred learning was applied to prostate cancer patients to build a model to detect and identify metastasis locations using bone scintigraphy. Ten-fold cross validation was conducted. The mean sensitivity and precision rates for bone metastasis location detection and classification (lesion-based) in the chests of prostate patients were 0.72 ± 0.04 and 0.90 ± 0.04, respectively. The mean sensitivity and specificity rates for bone metastasis classification (patient-based) in the chests of prostate patients were 0.94 ± 0.09 and 0.92 ± 0.09, respectively. The developed system has the potential to provide pre-diagnostic reports to aid in physicians' final decisions. [ABSTRACT FROM AUTHOR]

Objectives: To predict KRAS mutation in rectal cancer (RC) through computer vision of [18F]fluorodeoxyglucose (18F‐FDG) positron emission tomography (PET)/computed tomography (CT) by using metric learning (ML). Methods: This study included 160 patients with RC who had undergone preoperative PET/CT. KRAS mutation was identified through polymerase chain reaction analysis. This model combined ML with the deep‐learning framework to analyze PET data with or without CT images. The Batch Balance Wrapper framework and K‐fold cross‐validation were employed during the learning process. A receiver operating characteristic (ROC) curve analysis was performed to assess the model's predictive performance. Results: Genetic alterations in KRAS were identified in 82 (51%) tumors. Both PET and CT images were used, and the proposed model had an area under the ROC curve of 0.836 for its ability to predict a mutation status. The sensitivity, specificity, and accuracy were 75.3%, 79.3%, and 77.5%, respectively. When PET images alone were used, the area under the curve was 0.817, whereas the sensitivity, specificity, and accuracy were 73.2%, 79.6%, and 76.2%, respectively. Conclusions: The ML model presented herein revealed that baseline 18F‐FDG PET/CT images could provide supplemental information to determine KRAS mutation in RC. Additional studies are required to maximize the predictive accuracy. Advances in knowledge: The results of the ML model presented herein indicate that baseline 18F‐FDG PET/CT images could provide supplemental information for determining KRAS mutation in RC. The predictive accuracy of the model was 77.5% when both image types were used and 76.2% when PET images alone were used. Additional studies are required to maximize the predictive accuracy. [ABSTRACT FROM AUTHOR]

Background: We designed a deep learning model for assessing 18F-FDG PET/CT for early prediction of local and distant failures for patients with locally advanced cervical cancer.Methods: All 142 patients with cervical cancer underwent 18F-FDG PET/CT for pretreatment staging and received allocated treatment. To augment the amount of image data, each tumor was represented as 11 slice sets each of which contains 3 2D orthogonal slices to acquire a total of 1562 slice sets. In each round of k-fold cross-validation, a well-trained proposed model and a slice-based optimal threshold were derived from a training set and used to classify each slice set in the test set into the categories of with or without local or distant failure. The classification results of each tumor were aggregated to summarize a tumor-based prediction result.Results: In total, 21 and 26 patients experienced local and distant failures, respectively. Regarding local recurrence, the tumor-based prediction result summarized from all test sets demonstrated that the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 71%, 93%, 63%, 95%, and 89%, respectively. The corresponding values for distant metastasis were 77%, 90%, 63%, 95%, and 87%, respectively.Conclusion: This is the first study to use deep learning model for assessing 18F-FDG PET/CT images which is capable of predicting treatment outcomes in cervical cancer patients.Key Points: • This is the first study to use deep learning model for assessing 18 F-FDG PET/CT images which is capable of predicting treatment outcomes in cervical cancer patients. • All 142 patients with cervical cancer underwent 18 F-FDG PET/CT for pretreatment staging and received allocated treatment. To augment the amount of image data, each tumor was represented as 11 slice sets each of which contains 3 2D orthogonal slices to acquire a total of 1562 slice sets. • For local recurrence, all test sets demonstrated that the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 71%, 93%, 63%, 95%, and 89%, respectively. The corresponding values for distant metastasis were 77%, 90%, 63%, 95%, and 87%, respectively. [ABSTRACT FROM AUTHOR]

Purpose: To understand the association between genetic mutations and radiomics of 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET)/x-ray computed tomography (CT) in patients with colorectal cancer (CRC).Procedures: This study included 74 CRC patients who had undergone preoperative [18F]FDG PET/CT. A total of 65 PET/CT-related features including intensity, volume-based, histogram, and textural features were calculated. High-resolution melting methods were used for genetic mutation analysis.Results: Genetic mutants were found in 21 KRAS tumors (28 %), 31 TP53 tumors (42 %), and 17 APC tumors (23 %). Tumors with a mutated KRAS had an increased value at the 25th percentile of maximal standardized uptake value (SUVmax) within their metabolic tumor volume (MTV) (P < .0001; odds ratio [OR] 1.99; 95 % confidence interval [CI] 1.37-2.90) and their contrast from the gray-level cooccurrence matrix (P = .005; OR 1.52; 95 % CI 1.14-2.04). A mutated TP53 was associated with an increased value of short-run low gray-level emphasis derived from the gray-level run length matrix (P = .001; OR 243006.0; 95 % CI 59.2-996,872,313). APC mutants exhibited lower low gray-level zone emphasis derived from the gray-level zone length matrix (P = .006; OR < .0001; 95 % CI 0.000-0.22).Conclusion: PET/CT-derived radiomics can provide supplemental information to determine KRAS, TP53, and APC genetic alterations in CRC. [ABSTRACT FROM AUTHOR]

Background: In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on F-fluorodeoxyglucose positron emission tomography/computed tomography. Methods: We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann-Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis. Results: Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV, the risk of pelvic LN metastasis can be scored accordingly. The TLG was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM). Conclusion: This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology. [ABSTRACT FROM AUTHOR]

Purpose: This study investigated the correlation of the matrix heterogeneity of tumors on F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) with gene-expression profiling in patients with pharyngeal cancer and determined the prognostic factors for radiotherapy-based treatment outcomes. Methods: We retrospectively reviewed the records of 57 patients with stage III-IV oropharyngeal or hypopharyngeal cancer who had completed definitive therapy. Four groups of the textural features as well as 31 indices were studied in addition to maximum standard uptake value, metastatic tumor volume, and total lesion glycolysis. Immunohistochemical data from pretreatment biopsy specimens ( Glut1, CAIX, VEGF, HIF-1α, EGFR, Ki-67, Bcl-2, CLAUDIN-4, YAP-1, c-Met, and p16) were analyzed. The relationships between the indices and genomic expression were studied, and the robustness of various textural features relative to cause-specific survival and primary relapse-free survival was analyzed. Results: The overexpression of VEGF was positively associated with the increased values of the matrix heterogeneity obtained using gray-level nonuniformity for zone (GLNUz) and run-length nonuniformity (RLNU). Advanced T stage ( p = 0.01, hazard ratio [HR] = 3.38), a VEGF immunoreactive score of >2 ( p = 0.03, HR = 2.79), and a higher GLNUz value ( p = 0.04, HR = 2.51) were prognostic factors for low cause-specific survival, whereas advanced T stage, a HIF-1α staining percentage of ≥80%, and a higher GLNUz value were prognostic factors for low primary-relapse free survival. Conclusions: The overexpression of VEGF was associated with the increased matrix index of GLNUz and RLNU. For patients with pharyngeal cancer requiring radiotherapy, the treatment outcome can be stratified according to the textural features, T stage, and biomarkers. [ABSTRACT FROM AUTHOR]

Background: This study examined genomic factors associated with a reduction in fluoro-2-deoxy- D-glucose (FDG) uptake during positron emission tomography-computed tomography (PET-CT) for definitive chemoradiotherapy (CRT) in patients with pharyngeal cancer. Methods: The pretreatment and interim PET-CT images of 25 patients with advanced pharyngeal cancers receiving definitive CRT were prospectively evaluated. The maximum standardized uptake value (SUV) of the interim PET-CT and the reduction ratio of the SUV (SRR) between the two images were measured. Genomic data from pretreatment incisional biopsy specimens ( SLC2A1, CAIX, VEGF, HIF1A, BCL2, Claudin-4, YAP1, MET, MKI67, and EGFR) were analyzed using tissue microarrays. Differences in FDG uptake and SRRs between tumors with low and high gene expression were examined using the Mann-Whitney test. Cox regression analysis was performed to examine the effects of variables on local control. Results: The SRR of the primary tumors (SRR-P) was 0.59 ± 0.31, whereas the SRR of metastatic lymph nodes (SRR-N) was 0.54 ± 0.32. Overexpression of HIF1A was associated with a high iSUV of the primary tumor ( P < 0.001) and neck lymph node ( P = 0.04) and a low SRR-P ( P = 0.02). Multivariate analysis revealed that patients who had tumors with low SRR-P or high HIF1A expression levels showed inferior local control. Conclusion: In patients with pharyngeal cancer requiring CRT, HIF1A overexpression was positively associated with high interim SUV or a slow reduction in FDG uptake. Prospective trials are needed to determine whether the local control rate can be stratified using the HIF1A level as a biomarker and SRR-P. [ABSTRACT FROM AUTHOR]

Simple Summary: Neoadjuvant chemoradiotherapy (NCRT) before surgery is the mainstay of treatment for patients with locally advanced rectal cancer. Based on baseline 18F-fluorodeoxyglucose ([18F]-FDG)-positron emission tomography (PET)/computed tomography (CT), a new artificial intelligence model was introduced to predict responses to NCRT. The model employed metric learning combined with the Uniform Manifold Approximation and Projection for dimensionality reduction. The treatment response was scored by Dworak tumor regression grade (TRG); TRG3 and TRG4 indicated favorable responses. Using this model, the area under the receiver operating characteristic curve was 0.96 for predicting a favorable response. The sensitivity, specificity, and accuracy were 98.3%, 96.5%, and 97.5%, respectively. After further external validation, oncologists may use the proposed model to advise patients on the relative suitability of treatment options, including the therapeutic decision between NCRT and neoadjuvant chemotherapy. Integrating this approach would have a notable effect on counseling patients about treatment alternatives or prognoses. Objectives: Neoadjuvant chemoradiotherapy (NCRT) followed by surgery is the mainstay of treatment for patients with locally advanced rectal cancer. Based on baseline 18F-fluorodeoxyglucose ([18F]-FDG)-positron emission tomography (PET)/computed tomography (CT), a new artificial intelligence model using metric learning (ML) was introduced to predict responses to NCRT. Patients and Methods: This study used the data of 236 patients with newly diagnosed rectal cancer; the data of 202 and 34 patients were for training and validation, respectively. All patients received pretreatment [18F]FDG-PET/CT, NCRT, and surgery. The treatment response was scored by Dworak tumor regression grade (TRG); TRG3 and TRG4 indicated favorable responses. The model employed ML combined with the Uniform Manifold Approximation and Projection for dimensionality reduction. A receiver operating characteristic (ROC) curve analysis was performed to assess the model's predictive performance. Results: In the training cohort, 115 patients (57%) achieved TRG3 or TRG4 responses. The area under the ROC curve was 0.96 for the prediction of a favorable response. The sensitivity, specificity, and accuracy were 98.3%, 96.5%, and 97.5%, respectively. The sensitivity, specificity, and accuracy for the validation cohort were 95.0%, 100%, and 98.8%, respectively. Conclusions: The new ML model presented herein was used to determined that baseline 18F[FDG]-PET/CT images could predict a favorable response to NCRT in patients with rectal cancer. External validation is required to verify the model's predictive value. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the study was to investigate the predictive role of pretreatment metabolic volume (MTV) in pharyngeal cancer (PC) patients treated with definitive (chemo) radiotherapy. Methods: This retrospective analysis enrolled 64 patients with PC treated with (chemo) radiotherapy. All patients received pretreatment fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT. Four PET segmentation methods were used, namely applying an isocontour at a standardized uptake value (SUV) of either 2.5 or 3.0 (MTV2.5 and MTV3.0) or using fixed thresholds of either 40 or 50 % (MTV40 %, MTV50 %) of the maximum intratumoural FDG activity. Disease-free survival (DFS) and primary relapse-free survival (PRFS) were examined according to cutoffs of the median values for each MTV and the gross tumour volume (GTVp). Independent prognosticators were identified by Cox regression analysis. Results: With a median follow-up of 24 months, 19 patients died, and 26 patients experienced tumour relapse at primary sites. Multivariate analysis of the DFS showed that MTV2.5 > 13.6 ml was the only predictor of relapse [ p = 0.011, hazard ratio = 2.69, 95 % confidence interval (CI) 1.25-5.76]. The independent predictor for PRFS was MTV2.5 > 13.6 ml ( p = 0.003, hazard ratio = 3.76, 95 % CI 1.57-8.92), whereas GTVp > 15.5 ml had a marginal impact on PRFS ( p = 0.06, hazard ratio = 3.54, 95 % CI 0.97-11.85). Patients having tumours with MTV2.5 > 13.6 ml had a significantly inferior 2-year PRFS compared with patients who had lower MTV2.5 tumours (39 vs 72 %, respectively, p = 0.001). Conclusion: For PC patients treated with definitive (chemo)radiotherapy, pretreatment MTV2.5 volume achieved the best predictive value for primary recurrence, and the same value was also a prognosticator for DFS. [ABSTRACT FROM AUTHOR]

ABSTRACT BACKGROUND AND PURPOSE The purpose of our study was aimed to analyze the sex- and age-related differences of brain metabolism in healthy individuals. METHODS Consecutive 100 healthy subjects, 50 males and 50 females, undergoing routine 2-[18F]-fluoro-2-deoxy-d-glucose positron emission tomography (FDG PET) for health checkup in our hospital were retrospectively enrolled in this study. Statistical parametric mapping (SPM) was used for analyses of the FDG PET images to disclose the possible effects of age on brain metabolism in males and females as well as the differences of brain metabolism between male and female groups. RESULTS In males and females, decreased brain metabolism with aging is found in bilateral lateral orbital prefrontal and right anterior cingulate cortices. In comparisons between sexes, males are found to have more brain metabolism than females in bilateral visual cortices and cerebellum. CONCLUSIONS Our report discloses different sex- and age-related brain metabolism. Decreased brain metabolism with aging in males and females is similar to findings reported in previous literatures. However, whether declined brain function or volume with aging causing metabolic changes is unknown and should be further evaluated. Nevertheless, the sex-related differences are possibly compatible with the historical observation of better performance in visual-spatial tasks in males than females. [ABSTRACT FROM AUTHOR]

We retrospectively reviewed the records of 142 patients with stage IB-IIIB cervical cancer who underwent 18F-FDG-PET/CT before external beam radiotherapy plus intracavitary brachytherapy and concurrent chemotherapy. The patients were divided into training and validation cohorts to confirm the reliability of predictors for recurrence. Kaplan-Meier analysis was performed and a Cox regression model was used to examine the effects of variables on overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and pelvic relapse-free survival (PRFS). High gray-level run emphasis (HGRE) derived from gray-level run-length matrix most accurately and consistently predicted the presence of pelvic residual or recurrent tumors for both cohorts. In multivariate analysis, stages IIIA-IIIB (P = 0.001, hazard ratio [HR] = 4.07) and a low HGRE (P < 0.0001, HR = 4.34) were prognostic factors for low OS, whereas a low HGRE (P = 0.001, HR = 2.86) and nonsquamous cell histology (P = 0.003, HR = 2.76) were prognostic factors for inferior PFS. The nonsquamous cell histology (P < 0.0001, HR = 9.19) and a low HGRE (P = 0.001, HR = 4.69) were predictors for low PRFS. In cervical cancer patients receiving definitive chemoradiotherapy, pretreatment textural features on 18F-FDG-PET/CT can supplement the prognostic information. [ABSTRACT FROM AUTHOR]

Abstract: Background To compare 18F-fluoro-2-deoxdeoxyglucose (FDG) positron emission tomography (PET) related parameters of primary colon or sigmoid cancer (CSC) with pathological findings. Methods Seventy-seven CSC patients who have undergone preoperative PET computed tomograms (PET/CT) are included in this study. Maximum PET-based tumor length (TL) and tumor width (TW) are determined using several auto-segmentation methods, and various thresholds of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are measured. The PET-based TL and TW are compared with maximum pathological length and width on the pathological specimen. Results Using a 30% threshold level for maximum uptake of TL (TL30%) and TW (TW30%) yield results that provide an optimal match with maximum pathological length (R =0.81, p <0.001) and width (R =0.70, p <0.001). TW30% was an independent factor for predicting pathological T3 or T4 stages (OR=1.26, 95% CI=1.07–1.47, p =0.01). The receiver-operating characteristic curves show MTV at a fixed threshold of 40% maximum uptake (MTV40%), and TW30% achieved better correlation with the advanced pathological T stage. No associations with positive N stage were observed. Conclusion Pretreatment PET/CT is a useful tool for predicting the final pathological findings for CSC patients requiring surgical procedures. [Copyright &y& Elsevier]

Purpose: We found several cases with unexpected pulmonary abnormalities on the 18F-FDG PET scan after the gastrointestinal endoscopy with sedation during a compact health check-up course, interfering the interpretations of 18F-FDG PET scan for cancer screening. The current studies aimed to analyze the incidence and the clinical relevance of this pulmonary finding. Materials and Methods: From June to December 2009, 127 subjects undergoing the sequential gastrointestinal endoscopy with sedation and 18F-FDG PET scan within 48 h as part of routine health check-up were retrospectively enrolled in this study. The incidence of abnormal pulmonary findings and their SUVmax of FDG were calculated and correlated with the clinical manifestations. Results: Five subjects had abnormal 18F-FDG PET findings but pulmonary symptoms were only found in 2. The SUVmax did not seem to reflect the severity of pulmonary symptoms or the need of intervention. Although the incidence of unrecognized pulmonary aspiration featuring inflammation detected by the 18F-FDG PET scan was high (3.94%, 5/127), the incidence of events needed intervention remained low (0.79%, 1/127), similar to those previously reported literatures. Conclusions: Although higher incidence of pulmonary aspiration in this study, it probably reflects the better sensitivity of 18F-FDG PET for inflammation. The low incidence of clinical events needed intervention may still reflect the safety of sedation used for gastrointestinal endoscopy. Proper arrangement of the sequential examinations if subjects need both gastrointestinal endoscopy with sedation and 18F-FDG PET is important to reduce the interference degrading the performance of 18F-FDG PET in cancer screening, diagnosis or staging. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: We found several cases with unexpected pulmonary abnormalities on the 18F-FDG PET scan after the gastrointestinal endoscopy with sedation during a compact health check-up course, interfering the interpretations of 18F-FDG PET scan for cancer screening. The current studies aimed to analyze the incidence and the clinical relevance of this pulmonary finding. Materials and methods: From June to December 2009, 127 subjects undergoing the sequential gastrointestinal endoscopy with sedation and 18F-FDG PET scan within 48h as part of routine health check-up were retrospectively enrolled in this study. The incidence of abnormal pulmonary findings and their SUVmax of FDG were calculated and correlated with the clinical manifestations. Results: Five subjects had abnormal 18F-FDG PET findings but pulmonary symptoms were only found in 2. The SUVmax did not seem to reflect the severity of pulmonary symptoms or the need of intervention. Although the incidence of unrecognized pulmonary aspiration featuring inflammation detected by the 18F-FDG PET scan was high (3.94%, 5/127), the incidence of events needed intervention remained low (0.79%, 1/127), similar to those previously reported literatures. Conclusions: Although higher incidence of pulmonary aspiration in this study, it probably reflects the better sensitivity of 18F-FDG PET for inflammation. The low incidence of clinical events needed intervention may still reflect the safety of sedation used for gastrointestinal endoscopy. Proper arrangement of the sequential examinations if subjects need both gastrointestinal endoscopy with sedation and 18F-FDG PET is important to reduce the interference degrading the performance of 18F-FDG PET in cancer screening, diagnosis or staging. [Copyright &y& Elsevier]

Background: To define a suitable threshold setting for gross tumor volume (GTV) when using 18Fluoro-deoxyglucose positron emission tomography and computed tomogram (PET/CT) for radiotherapy planning in head and neck cancer (HNC).Methods: Fifteen HNC patients prospectively received PET/CT simulation for their radiation treatment planning. Biological target volume (BTV) was derived from PET/CT-based GTV of the primary tumor. The BTVs were defined as the isodensity volumes when adjusting different percentage of the maximal standardized uptake value (SUVmax), excluding any artifact from surrounding normal tissues. CT-based primary GTV (C-pGTV) that had been previously defined by radiation oncologists was compared with the BTV. Suitable threshold level (sTL) could be determined when BTV value and its morphology using a certain threshold level was observed to be the best fitness of the C-pGTV. Suitable standardized uptake value (sSUV) was calculated as the sTL multiplied by the SUVmax.Results: Our result demonstrated no single sTL or sSUV method could achieve an optimized volumetric match with the C-pGTV. The sTL was 13% to 27% (mean, 19%), whereas the sSUV was 1.64 to 3.98 (mean, 2.46). The sTL was inversely correlated with the SUVmax [sTL = -0.1004 Ln (SUVmax) + 0.4464; R2 = 0.81]. The sSUV showed a linear correlation with the SUVmax (sSUV = 0.0842 SUVmax + 1.248; R2 = 0.89). The sTL was not associated with the value of C-pGTVs.Conclusion: In PET/CT-based BTV for HNC, a suitable threshold or SUV level can be established by correlating with SUVmax rather than using a fixed threshold. [ABSTRACT FROM AUTHOR]