Liver Standardized Uptake Value Research Articles

Quantitative analysis of liver standardized uptake value repeatability in SPECT/CT implications for clinical practice

Purpose. The aim of this study was to assess the repeatability of the SUV normalized by liver volume (SUVL) between two liver receptor SPECT/CT studies performed on different days in patients with ICG-R15 values within normal range. Methods. 935 patients who underwent liver receptor scintigraphy between January 2010 and August 2018 were included. Patients who underwent liver resection, hepatic arterial embolization or had ICG-R15 >10% between scans were excluded, and 38 patients were finally included in the analysis. The repeatability of SUVL between scans was assessed using the intraclass correlation coefficient (ICC) (1.1) between SUVLmax, SUVLpeak and SUVLmean at the first and second scan and the additive and proportional errors from the Bland-Altman analysis. Results. In ICC (1,1), SUVLmax, SUVLpeak and SUVLmean were all greater than 0.8, indicating almost perfect repeatability; neither additive nor proportional errors were observed in the Bland-Altman analysis. Conclusions. In patients with ICG-R15 values within the normal range, the SUV Liver (SUVL) between two liver receptor SPECT/CT studies performed on different days was repeatability over time. It was suggested that the SUVL of liver receptor scintigraphy could be an indicator that could be used for follow-up over time in the assessment of liver fibrosis.

Potential Added Value of 18F-FDG PET Metabolic Parameters in Predicting Disease Relapse in Type 1 Autoimmune Pancreatitis

BackgroundThe predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters for predicting AIP relapse is currently unknown. This study firstly explored the value of 18F-FDG PET/CT parameters as predictors of type 1 AIP relapse.MethodsThis multicenter retrospective cohort study analyzed 51 patients who received 18F-FDG PET/CT prior to treatment and did not receive maintenance therapy after remission. The study collected baseline characteristics and clinical data and conducted qualitative and semi-quantitative analysis of pancreatic lesions and extrapancreatic organs. The study used three thresholds to select the boundaries of pancreatic lesions to evaluate metabolic parameters, including the maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), metabolic tumor volume (MTV), and tumor-to-normal liver standard uptake value ratio (SUVR). Univariate and multivariate analyses were performed to identify independent predictors and build a recurrence prediction model. The model was internally validated using the bootstrap method and a nomogram was created for clinical application.ResultsIn the univariable analysis, the relapsed group showed higher levels of SUVmax (6.0 ± 1.6 vs. 5.2 ± 1.1; P = 0.047), SUVR (2.3 [2.0–3.0] vs. 2.0 [1.6–2.4]; P = 0.026), and TLG2.5 (234.5 ± 149.1 vs. 139.6 ± 102.5; P = 0.020) among the 18F-FDG PET metabolic parameters compared to the non-relapsed group. In the multivariable analysis, serum IgG4 (OR, 1.001; 95% CI, 1.000–1.002; P = 0.014) and TLG2.5 (OR, 1.007; 95% CI, 1.002–1.013; P = 0.012) were independent predictors associated with relapse of type 1 AIP. A receiver-operating characteristic curve of the predictive model with these two predictors demonstrated an area under the curve of 0.806.Conclusion18F-FDG PET/CT metabolic parameters, particularly TLG2.5, are potential predictors for relapse in patients with type 1 AIP. A multiparameter model that includes IgG4 and TLG2.5 can enhance the ability to predict AIP relapse.

Improved identification of tumors in 18F-FDG-PET examination by normalizing the standard uptake in the liver based on blood test data

PurposeStandardized uptake values (SUVs) derived from 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography are a crucial parameter for identifying tumors or abnormalities in an organ. Moreover, exploring ways to improve the identification of tumors or abnormalities using a statistical measurement tool is important in clinical research. Therefore, we developed a fully automatic method to create a personally normalized Z-score map of the liver SUV.MethodsThe normalized Z-score map for each patient was created using the SUV mean and standard deviation estimated from blood-test-derived variables, such as alanine aminotransferase and aspartate aminotransferase, as well as other demographic information. This was performed using the least absolute shrinkage and selection operator (LASSO)-based estimation formula. We also used receiver operating characteristic (ROC) to analyze the results of people with and without hepatic tumors and compared them to the ROC curve of normal SUV.ResultsA total of 7757 people were selected for this study. Of these, 7744 were healthy, while 13 had abnormalities. The area under the ROC curve results indicated that the anomaly detection approach (0.91) outperformed only the maximum SUV (0.89). To build the LASSO regression, sets of covariates, including sex, weight, body mass index, blood glucose level, triglyceride, total cholesterol, γ-glutamyl transpeptidase, total protein, creatinine, insulin, albumin, and cholinesterase, were used to determine the SUV mean, whereas weight was used to determine the SUV standard deviation.ConclusionThe Z-score normalizes the mean and standard deviation. It is effective in ROC curve analysis and increases the clarity of the abnormality. This normalization is a key technique for effective measurement of maximum glucose consumption by tumors in the liver.

Baseline 18f-Fluorodeoxyglucose PET/CT Radiomics Predicts Outcome in Newly Diagnosed Intravascular Large B-Cell Lymphoma

[Introduction] Treatment outcomes of intravascular large B-cell lymphoma (IVLBCL), a rare subtype of extra-nodal diffuse large B-cell lymphoma (DLBCL), have dramatically improved in recent years. However, prognostic factors for IVLBCL are largely unknown. Several studies have explored the potential of the baseline 18F-fluorodeoxyglucose (FDG) PET/CT radiomics features to identify patients with poor prognosis. For example, metabolic tumor volume (MTV) reflects the FDG-avid tumor burden, and the maximum distance between the largest lesion and any other lesion quantifies the dissemination of the tumor, and both factors are inversely related to overall survival (OS) and progression-survival (PFS) in DLBCL. In this study, we explored prognostic impact of FDG PET/CT radiomics features in newly diagnosed IVLBCL. [Methods] We retrospectively evaluated patients with histopathologically proven newly diagnosed IVLBCL according to the 2008 World Health Organization criteria between January 2010 through February 2022 from hospitals participating in the North Japan Hematology Study Group (NJHSG). Quantitative analysis of all FDG PET/CT was performed using Metavol (Hokkaido University, Sapporo, Japan), with exclusion of physiological accumulation. MTV was defined as the volume of lymphoma lesions visualized on PET/CT scans with standardized uptake value (SUV) peaks greater than or equal to hepatic SUV peak. To quantify the dissemination of the tumor, we calculated the number of the body areas (head-neck, chest, abdomen, upper-extremities, lower-extremities) having BM lesions with a higher SUV peak than liver SUV peak. Patients with BM lesions spread across 4-5 areas were defined as cases having widely disseminated lesions (WDL). Progression-free survival (PFS) was defined as the time from the start of treatment to the first of progression, relapse, or death from any cause. Patients undergoing upfront autologous stem-cell transplantation (auto-SCT) were censored at the time of transplantation. [Results] We identified fifty-two IVLBCL patients (age 30-89 years, median 65 years; 57.7% male) who performed FDG PET/CT at diagnosis. Twenty-eight patients (54.9%) had poor performance status (ECOG PS ≥2), and 49 patients (94.2%) showed stage III-IV. Forty-nine patients (94.2%) had 2 or more extranodal involvement. Elevated serum LDH level was observed in 49 cases (94.2%) (median, 623.5 IU/L; range, 147-4907 IU/L). The median serum levels of soluble IL-2 receptor (sIL-2R), ferritin, and C-reactive protein (CRP) were 4496.5 IU/mL (range, 321-19900 IU/mL), 655.15 ng/mL (range, 50-6657 ng/mL), and 6.905 mg/dL (range, 0.11-25.86 mg/dL), respectively. The median MTV was 415.527 cm 3 (range, 0-3000 cm 3). ROC analysis revealed that the cutoff value of the MTV > 388 cm 3 could predict progression events within 2 years. Area under curve was 0.71 (95% CI: 0.564-0.857). Twenty-nine patients (55.8%) were classified as having MTV > 388 cm 3 (high MTV). Twenty-three patients (44.2%) had WDL. Fifty-one (98.1%) patients received chemotherapy, all of which was rituximab-containing regimen. Three patients (5.8%) received upfront auto-SCT. Median follow-up duration was 48.8 months (range, 5.8-140.5 months) in survivors. Age, LDH level, number of extranodal lesions, clinical stage, and PS did not affect OS and PFS. Although the high MTV and WDL did not significantly affect OS ( P = 0.095, P = 0.173, respectively; Log-rank), these findings did correlate significantly with poor PFS ( P = 0.011, P = 0.042, respectively; Log-rank). Thus, we defined a high MTV or a WDL as poor PET findings. Thirty-two patients had poor PET findings. Importantly, patients with poor PET findings showed significantly poor OS and PFS compared to patients without (2-year OS: 71.2% vs. 93.3%, P = 0.015, 2-year PFS: 45.5% vs. 93.8%, P = 0.001; Log-rank, Fig. 1, 2). [Conclusion] This is the largest study to assess prognostic impact of FDG PET/CT radiomics features on newly diagnosed IVLBCL. Poor PET findings were significantly correlated with worse OS and PFS.

18F-FDG-PET/CT-based machine learning model evaluates indeterminate adrenal nodules in patients with extra-adrenal malignancies

BackgroundTo assess the value of an 18F-FDG-positron emission tomography/computed tomography (PET/CT)-based machine learning model for distinguishing between adrenal benign nodules (ABNs) and adrenal metastases (AMs) in patients with indeterminate adrenal nodules and extra-adrenal malignancies.MethodsA total of 303 patients who underwent 18F-FDG-PET/CT with indeterminate adrenal nodules and extra-adrenal malignancies from March 2015 to June 2021 were included in this retrospective study (training dataset (n = 182): AMs (n = 97), ABNs (n = 85); testing dataset (n = 121): AMs (n = 68), ABNs (n = 55)). The clinical and PET/CT imaging features of the two groups were analyzed. The predictive model and simplified scoring system for distinguishing between AMs and ABNs were built based on clinical and PET/CT risk factors using multivariable logistic regression in the training cohort. The performances of the predictive model and simplified scoring system in both the training and testing cohorts were evaluated by the areas under the receiver operating characteristic curves (AUCs) and calibration curves. The comparison of AUCs was evaluated by the DeLong test.ResultsThe predictive model included four risk factors: sex, the ratio of the maximum standardized uptake value (SUVmax) of adrenal lesions to the mean liver standardized uptake value, the value on unenhanced CT (CTU), and the clinical stage of extra-adrenal malignancies. The model achieved an AUC of 0.936 with a specificity, sensitivity and accuracy of 0.918, 0.835, and 0.874 in the training dataset, respectively, while it yielded an AUC of 0.931 with a specificity, sensitivity, and accuracy of 1.00, 0.735, and 0.851 in the testing dataset, respectively. The simplified scoring system had comparable diagnostic value to the predictive model in both the training (AUC 0.938, sensitivity: 0.825, specificity 0.953, accuracy 0.885; P = 0.5733) and testing (AUC 0.931, sensitivity 0.735, specificity 1.000, accuracy 0.851; P = 1.00) datasets.ConclusionsOur study showed the potential ability of a machine learning model and a simplified scoring system based on clinical and 18F-FDG-PET/CT imaging features to predict AMs in patients with indeterminate adrenal nodules and extra-adrenal malignancies. The simplified scoring system is simple, convenient, and easy to popularize.

The baseline metabolism parameters of 18F‑FDG PET/CT as promising prognostic biomarkers in pediatric Langerhans cell histiocytosis.

Langerhans cell histiocytosis (LCH) is a rare myeloid precursor cell inflammatory neoplasia, which agonizes, maims, and even kills patients. Although clinical outcomes have steadily improved over the past decades, the progression/relapse rate of LCH remains high. The purpose of this study was to evaluate the prognostic value of the pre-treatment metabolism parameters of baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F‑FDG PET/CT) in children with LCH. This cross-sectional study retrospectively and consecutively included 37 children (24 males and 13 females; median age, 5.1 years; range, 2.4-7.8 years) with pre-treatment 18F-FDG PET/CT from September 2020 to September 2022 in Nuclear Medicine Department, Beijing friendship hospital, Capital Medical University, Beijing, China. These patients were then all admitted to the hospital and diagnosed with LCH by biopsy, in Hematology Center, Beijing Children's Hospital, Capital Medical University, Beijing, China. Five metabolism parameters of 18F-FDG PET/CT were analyzed, including maximum standardized uptake, tumor-to-normal liver standard uptake value ratio, tumor-to-normal bone marrow standard uptake value ratio, sum of metabolic tumor volume (sMTV), and sum of total lesion glycolysis (sTLG) of all lesions. Patients were followed up for at least 1 year or until disease progression/relapse. Univariate and multivariate analyses of progression-free survival was performed. During follow-up, 11 (29.7%) patients had disease progression/relapse. Univariate analysis revealed that the risk organ involvement, the treatment response at the 5th or 11th week, pre-treatment sMTV, and sTLG were significantly associated with progression-free survival (P=0.024, 0.018, 0.006, 0.006, and 0.042, respectively). Multivariate COX analysis revealed that non-response at the 11th week, pre-treatment sMTV >32.55 g/cm3, and sTLG >98.86 g (P=0.002, 0.020, 0.026, respectively) were risk factors for progression-free survival. The baseline metabolism parameters of 18F-FDG PET/CT could be promising imaging biomarkers for predicting prognosis in children with LCH.

The role of 18F-FDG PET in predicting the pathological response and prognosis to unresectable HCC patients treated with lenvatinib and PD-1 inhibitors as a conversion therapy.

To investigate the diagnostic value of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), as an imaging biomarker, for predicting pathological response and prognosis of unresectable hepatocellular carcinoma (HCC) patients treated with Lenvatinib and programmed cell death protein 1 (PD-1) inhibitors as a conversion therapy. A total of 28 unresectable HCC patients with BCLC stage B or C were treated with Lenvatinib and PD-1 inhibitors before surgery. The 18F-FDG PET/CT scans were acquired before pre- (scan-1) and post-conversion therapy (scan-2). The maximum standardized uptake value (SUVmax), TLR (tumor-to-normal liver standardized uptake value ratio), and the percentages of post-treatment changes in metabolic parameters (ΔSUVmax [%] and ΔTLR [%]) were calculated. Major pathological response (MPR) was identified based on the residual viable tumor in the resected primary tumor specimen (≤10%). Differences in the progression-free survival (PFS) and overall survival (OS) stratified by ΔTLR were examined by the Kaplan-Meier method. 11 (11/28, 39.3%) patients were considered as MPR responders and 17 (17/28, 60.7%) patients as non-MPR responders after conversion therapy. ΔSUVmax (-70.0 [-78.8, -48.8] vs. -21.7 [-38.8, 5.7], respectively; P<0.001) and ΔTLR (-67.6 [-78.1, -56.8] vs. -18.6 [-27.9, 4.0], respectively; P<0.001) were reduced in the responder group than those in the non-responder group. According to the results of the receiver operating characteristic curve analysis, ΔTLR showed an excellent predictive value for the MPR of primary HCC lesions (area under curve=0.989, with the optimal diagnostic threshold of -46.15). When using ΔTLR of -21.36% as a threshold, patients with ΔTLR-based metabolic response had superior PFS (log-rank test, P=0.001) and OS (log-rank test, P=0.016) compared with those without ΔTLR-based metabolic response. 18F-FDG PET is a valuable tool for predicting pathological response and prognosis of unresectable HCC patients treated by Lenvatinib combined with PD-1 as a conversion therapy.

FDG PET/CT in Aseptic Splenic Abscess

HomeRadiologyRecently Published PreviousNext Reviews and CommentaryFree AccessImages in RadiologyFDG PET/CT in Aseptic Splenic AbscessWeiting Liu, Xiaohong Ou Weiting Liu, Xiaohong Ou Author AffiliationsFrom the Department of Nuclear Medicine, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, People’s Republic of China.Address correspondence to X.O. (email: [email protected]).Weiting LiuXiaohong Ou Published Online:Mar 28 2023https://doi.org/10.1148/radiol.222955MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In A 32-year-old woman presented with fever and arthralgia for 1 month. She had a past medical history of rheumatoid arthritis with 2 years of glucocorticoid treatment. At physical examination, splenomegaly was found. Her laboratory data showed leukocytosis (15.86 × 109/L; reference range, 3.5–9.5 × 109/L) and a high erythrocyte sedimentation rate. Serial blood cultures were negative. Intravenous antibiotics and corticosteroid therapy did not relieve her symptoms. Fluorodeoxyglucose (FDG)-PET/CT examination was performed, showing abnormal standardized uptake values in the spleen (Figure). Primary splenic lymphoma was suspected, and the patient underwent laparoscopic splenectomy. At pathologic examination (Figure), the diagnosis of aseptic splenic abscesses as a complication of rheumatoid arthritis was made. Corticosteroids and supportive treatment were then initiated, and her clinical condition gradually improved.Images in a 32-year-old woman presenting with fever and arthralgia for 1 month. She had a past medical history of rheumatoid arthritis with 2 years of glucocorticoid treatment. A fluorodeoxyglucose (FDG)-PET examination was performed. (A) Maximum intensity projection whole body image shows intense diffuse splenic uptake and moderate bone marrow uptake. (B) Axial-fused PET/CT abdominal image shows an enlarged spleen with heterogeneously increased FDG standardized maximum uptake value (standardized maximum uptake value,13.94; liver standardized maximum uptake value, 3.76). At pathologic examination, macroscopic examination of the spleen showed many nonconfluent white nodules (not shown). (C) With use of hematoxylin and eosin, a photomicrograph with 400× magnification shows numerous areas of necrosis surrounded by intense polymorphonuclear cell infiltration (arrows) and fibroblastic proliferation at the periphery of the splenic nodules.Download as PowerPointOpen in Image Viewer Splenic abscesses generally occur in patients with immune dysfunction (1), presenting as solitary or multifocal lesions. Aseptic abscesses are most commonly associated with nonspecific inflammatory bowel disease and other autoimmune diseases (spondyloarthropathy, rheumatoid arthritis, lupus erythematosus, and nodular arteritis), or autoinflammatory (synovitis, acne, pustulosis, hyperostosis, and osteitis) and neoplastic ones (myeloma, monoclonal gammopathy) (2). Histopathologic examination helps to exclude other conditions. The cornerstones of aseptic abscesses are mature polymorphonuclear neutrophils in the center of the splenic nodules, with histiocytes and single giant cells present at the periphery (2). It is unclear whether glucocorticoids could be a factor that promotes the formation of aseptic splenic abscesses. The presence of disseminated sterile splenic microabscesses with intense FDG uptake related to rheumatoid arthritis is rare.Disclosures of conflicts of interest: W.L. No relevant relationships. X.O. No relevant relationships.

Multiparameter diagnostic model based on 18F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis

ObjectiveTo evaluate the diagnostic value of a multiparameter model based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis.Patients and methodsIn total, 122 patients (88 GBC nonmetastatic patients and 34 cholecystitis patients) with gallbladder space-occupying lesions who underwent 18F-FDG PET/CT were included. All patients received surgery and pathology, and baseline characteristics and clinical data were also collected. The metabolic parameters of 18F-FDG PET, including SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), SUVpeak (peak standard uptake value), MTV (metabolic tumour volume), TLG (total lesion glycolysis) and SUVR (tumour-to-normal liver standard uptake value ratio), were evaluated. The differential diagnostic efficacy of each independent parameter and multiparameter combination model was evaluated using the receiver operating characteristic (ROC) curve. The improvement in diagnostic efficacy using a combination of the above multiple parameters was evaluated by integrated discriminatory improvement (IDI), net reclassification improvement (NRI) and bootstrap test. Decision curve analysis (DCA) was used to evaluate clinical efficacy.ResultsThe ROC curve showed that SUVR had the highest diagnostic ability among the 18F-FDG PET metabolic parameters (area under the curve [AUC] = 0.698; sensitivity = 0.341; specificity = 0.971; positive predictive value [PPV] = 0.968; negative predictive value [NPV] = 0.363). The combined diagnostic model of cholecystolithiasis, fever, CEA > 5 ng/ml and SUVR showed an AUC of 0.899 (sensitivity = 0.909, specificity = 0.735, PPV = 0.899, NPV = 0.758). The diagnostic efficiency of the model was improved significantly compared with SUVR. The clinical efficacy of the model was confirmed by DCA.ConclusionsThe multiparameter diagnostic model composed of 18F-FDG PET metabolic parameters (SUVR) and clinical variables, including patient signs (fever), medical history (cholecystolithiasis) and laboratory examination (CEA > 5 ng/ml), has good diagnostic efficacy in the differential diagnosis of nonmetastatic GBC and cholecystitis.

Tumor metabolism derived from 18F-FDG PET/CT in predicting the macrotrabecular-massive subtype of hepatocellular carcinoma

The recently described pathological subtype of hepatocellular carcinoma (HCC), named macrotrabecular massive (MTM), is associated with an unfavorable prognosis. This study aimed to evaluate the potential for tumor metabolism obtained by β-2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) to be used as a preoperative imaging indicator for predicting MTM-HCCs. This study was designed to be cross-sectional. Patients who underwent preoperative 18F-FDG PET/CT and who had surgically-diagnosed HCC between June 2015 and June 2021 were retrospectively included. Tumor metabolism was determined by the tumor-to-normal liver standardized uptake value ratio (TLR) of the primary tumor as shown on 18F-FDG PET/CT. Clinical, pathological, and PET/CT characteristics were compared between non-MTM-HCCs and MTM-HCCs. Univariate analyses were used to screen the predictive factors of MTM-HCCs, then multivariate binary logistic regression analyses were performed. A regression-based diagnostic model was then established. Substantial necrosis was assessed to compare the predictive performance between traditional imaging and TLR measured on 18F-FDG PET/CT. The receiver operating characteristic (ROC) curve analyses and the DeLong test were used to assess the predictive performance. A total of 93 patients (mean age, 52.6±11.3 years; 81 male) with 36 MTM-HCCs were included. Multivariate binary logistic regression analyses identified higher platelet count [PLT; ≥118.5×103/µL; odds ratio (OR), 3.63; 95% confidence interval (CI), 1.13-12.87; P=0.035], higher aspartate transaminase (AST; ≥52 IU/L; OR, 4.15; 95% CI: 1.34-14.33; P=0.017), and larger TLR (≥2.2; OR, 5.55; 95% CI: 1.90-17.56; P=0.002) as independent predictors of MTM-HCCs. A TLR ≥2.2 helped to identify 72.2% of the MTM-HCCs with a specificity of 75.4%. The AUC of the regression-based diagnostic model for predicting MTM-HCCs was 0.835 (95% CI: 0.746-0.923), with a sensitivity of 80.6% and a specificity of 78.9%. Substantial necrosis enabled the identification of MTM-HCCs with 52.8% sensitivity and 87.7% specificity, with an AUC of 0.702 (95% CI: 0.588-0.817). There was no statistical difference between TLR and substantial necrosis in predicting MTM-HCCs using the DeLong test (P>0.05). Tumor metabolism determined by TLR on 18F-FDG PET/CT is a valuable imaging indicator for MTM-HCCs. Noninvasive prediction of this subtype can achieve good sensitivity and excellent predictive performance based on the regression model of AST, PLT, and TLR.

Variable Relative Biological Effectiveness of Proton Therapy Increases PET-Visible Mucosal Injury in Head and Neck Cancer Patients

Despite dosimetric advantages of proton therapy in head and neck cancers, there is concern for increased end of range relative biologic effectiveness (RBE) and subsequent dose enhancement and mucosal toxicity with proton therapy. Herein, we evaluated differences in mucosal PET avidity on post-treatment scans as a surrogate for mucosal injury between proton and photon therapy patients. We further assessed the relationship between PET changes and RBE. The cohort comprised 9 proton and 10 photon patients who received ≥50 Gy adjuvant radiotherapy to oropharyngeal mucosa who remained loco-regional disease free ≥6 months post-treatment. All patients underwent follow-up fluorodeoxyglucose (FDG) PET-CT scans 3 months post-radiotherapy. PET-CTs were fused to planning CTs using deformable registration. High- and low-uptake regions were auto-contoured using a ≥150% mean liver standard uptake value (SUV) threshold and intersected with mucosal targets with/without a 5mm margin. SUV maximum (SUVMAX) values, linear energy transfer (LET) statistics, and RBE statistics based on McNamara, Jones, and linear LET models were extracted and compared. The mucosal target SUVMAX values on post-treatment PET-CTs for proton patients averaged 6.78 compared to 4.83 for photon patients (p=0.0267). Near maximum (LETd1%) LET for mucosal targets with a 5mm margin averaged 5.232 keV/µm. RBE in high-uptake regions exceeded that of low-uptake regions (p=0.0039), with mean biologic dose exceeding clinical dose by 11.05%, 18.67%, and 15.65%, respectively, using different RBE models. Post-radiotherapy PET avidity was more commonly observed in proton patients. Within proton patient mucosal targets, the location of increased PET avidity corresponded to areas with higher RBE. This is the first report of differential PET findings based on RBE. These results suggest that elevated RBE was associated with PET avidity and mucosal injury.

Multiparameter diagnostic model based on 18F-FDG PET and clinical characteristics can differentiate thymic epithelial tumors from thymic lymphomas

ObjectiveTo evaluate the diagnostic performance of combined multiparametric 18F-fluorodeoxyglucose positron emission tomography (18FDG PET) with clinical characteristics in differentiating thymic epithelial tumors (TETs) from thymic lymphomas.Patients and methodsA total of 173 patients with 80 TETs and 93 thymic lymphomas who underwent 18F-FDG PET/CT before treatment were enrolled in this retrospective study. All patients were confirmed by pathology, and baseline characteristics and clinical data were also collected. The semi-parameters of 18F-FDG PET/CT, including lesion size, SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), TLG (total lesion glycolysis), MTV (metabolic tumor volume) and SUVR (tumor-to-normal liver standard uptake value ratio) were evaluated. The differential diagnostic efficacy was evaluated using the receiver operating characteristic (ROC) curve. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI), and Delong test were used to evaluate the improvement in diagnostic efficacy. The clinical efficacy was evaluated by decision curve analysis (DCA).ResultsAge, clinical symptoms, and metabolic parameters differed significantly between patients with TETs and thymic lymphomas. The ROC curve analysis of SUVR showed the highest differentiating diagnostic value (sensitivity = 0.763; specificity = 0.888; area under the curve [AUC] = 0.881). The combined diagnostics model of age, clinical symptoms and SUVR resulted in the highest AUC of 0.964 (sensitivity = 0.882, specificity = 0.963). Compared with SUVR, the diagnostic efficiency of the model was improved significantly. The DCA also confirmed the clinical efficacy of the model.ConclusionsThe multiparameter diagnosis model based on 18F-FDG PET and clinical characteristics had excellent value in the differential diagnosis of TETs and thymic lymphomas.

Pretreatment Metabolic Parameters Measured by 18F-FDG PET to Predict the Pathological Treatment Response of HCC Patients Treated With PD-1 Inhibitors and Lenvatinib as a Conversion Therapy in BCLC Stage C.

ObjectivesThis study aimed to assess the pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) as a predictor of the pathological treatment response (PTR) of hepatocellular carcinoma (HCC) patients treated with PD-1 inhibitors and lenvatinib as a conversion therapy in BCLC stage C.MethodsAll patients (n=20) underwent pretreatment 18F-FDG PET/CT and were treated with conversion therapy and surgery. Patients were categorized into responders (n=9) and non-responders (n=11) according to PTR. The parameters of PET/CT, including lesion size, SUVmean (mean standard uptake value), MTV (metabolic tumor volume), TLG (total lesion glycolysis), SUVpeak (peak standard uptake value), and TLR (tumor-to-normal liver standardized uptake value ratio), were calculated. The diagnostic efficacy was evaluated by receiver operating characteristic analysis (ROC). PTR was compared with pretreatment PET/CT parameters by using Spearman correlation analysis. The patients were followed up.ResultsThere was significant difference in TLR (5.59 ± 1.90 vs. 2.84 ± 1.70, respectively; P=0.003) between responders and non-responders, with the largest area under the curve (sensitivity=100%, specificity=72.7%, AUC=0.899, 95%CI: 0.759-1.000, optimal diagnostic threshold of 3.09). The relationship between 18F-FDG PET/CT parameters and PTR indicated TLR was moderately and positively correlated with pathological treatment response, with correlation coefficients (rs) of 0.69 (P<0.01). During the follow-up, no patients died, and tumor recurrence was found in one of the responders (11.1%). In all 11 non-responders, tumor recurrence was found in six patients (54.5%) and four patients (36.4%) died.ConclusionsTLR may be a powerful marker to predict PTR of HCC patients with BCLC stage C who were treated with conversion therapy.

The value of pretreatment 18F-FDG PET/CT to predict the pathological treatment response of hepatocellular carcinoma patients treated with PD-1 inhibitors and lenvatinib as a conversion therapy in BCLC stage C.

e16130 Background: Current systemic therapy for patients with hepatocellular carcinoma (HCC) in BCLC stage C consists of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). This study aimed to assess the parameters of pretreatment 18F-FDG PET/CT as a predictor of the pathological treatment response (PTR) of HCC patients treated with PD-1 inhibitors and lenvatinib as a conversion therapy in BCLC stage C. Methods: We retrospective analyzed 20 consecutive patients with HCC in BCLC stage C. All patients underwent pretreatment 18F-FDG PET/CT and treated with PD-1 inhibitors and lenvatinib as a conversion therapy and surgery. Patients were categorized into responders (n=9) and non-responders (n=11) according to PTR. The PTR was classified based on the primary tumor cellularity (responder, defined as &lt;10% cellularity). The parameters of PET/CT including lesion size, SUVmax (max standardized uptake value), SUVmean (mean standard uptake value), MTV2.5 (metabolic tumor volume2.5), TLG2.5 (total lesion glycolysis2.5), SUVpeak (peak standard uptake value), and TLR (tumor-to-normal liver standardized uptake value ratio, SUVmax of the tumor/SUVmean of the normal liver parenchyma) were calculated and compared between two groups. The diagnostic efficacy was evaluated by ROC. PTR was compared with pretreatment 18F-FDG PET/CT parameters by using Spearman correlation analysis. The prognosis was followed up. Results: TLR (5.59±1.90 vs. 2.84±1.70, respectively; P=0.003) showed significant difference in responders and non-responders and the largest area under the curve (sensitivity: 1.000, specificity: 0.727, positive predictive value: 0.750, negative predictive value: 1.000, AUC=0.899, 95%CI: 0.759-1.000), and optimal diagnostic threshold of 3.09. The relationship between 18F-FDG PET/CT parameters and PTR showed TLR had moderate positive correlation with pathological treatment response, with correlation coefficients (rs) of 0.69 ( P＜0.05). During the follow-up, no patients died, and 1 patient (11.1%) showed tumor recurrence in responders. In all 11 non-responders, 5 patients (45.5%) had tumor recurrence and 4 patients (36.4%) died. Conclusions: The TLR may be a powerful marker to predict the PTR of HCC patients with BCLC stage C who treated with PD-1 inhibitors and lenvatinib as a conversion therapy.[Table: see text]

Impact of metabolic indices of 18F-fluorodeoxyglucose positron emission tomography/computed tomography on post transplantation recurrence of hepatocellular carcinoma

BackgroundTumor recurrence is the leading cause of death after liver transplantation in patients with hepatocellular carcinoma. There is an ongoing debate as to whether metabolic indices such as tumor to liver standardized uptake value ratio in 18F-fluorodeoxyglucose positron emission tomography/computed tomography of the primary tumor can identify patients outside the Milan criteria with as low recurrence rates as patients inside Milan and thus should be added to the established prognostic factors.MethodsThis retrospective study analyzes 103 consecutive patients who underwent 18F-fluorodeoxyglucose positron emission tomography/computed tomography before liver transplantation for hepatocellular carcinoma using data of clinical tumor registry. Primary endpoints were overall survival and 10-year cumulative recurrence rates.ResultsTumor to liver standardized uptake value ratio of the primary tumor was statistically significant higher in Milan out tumors, “up-to-seven” out tumors, grade 3 tumors, α- fetoprotein level >400 ng/ml and lesions > 5cm in diameter. Factors with statistically significant influence on the 10- year overall survival in the univariate analysis were Milan, up-to-seven” criteria, number of lesions and pT-category. COX regression analysis did not show independently statistically significant factors for 10-year overall survival. Milan, “up-to-seven” criteria, grade, pV, number of lesions, size of lesion, pT-category, tumor to liver standardized uptake value ratio influenced 10-year cumulative recurrence rates statistically significant. Tumor to liver standardized uptake value ratio, grade and pT-category proved to be independently statistically significant factors for 10-year cumulative recurrence rates.ConclusionsOur study suggests that tumor to liver standardized uptake value standardized uptake value ratio in 18F-fluorodeoxyglucose positron emission tomography/computed tomography is an independent prognostic factor in transplanted patients with hepatocellular carcinoma. If we focus on preoperative findings, such as tumor size, tumor number and AFP value adding the information given by TLR of 18F-FDG PET/CT allows to estimate the risk of tumor recurrence more accurate than the established classifications Milan and UTS. Therefore, it may add valuable information to other preoperative findings, such as tumor size, tumor number and AFP level.

The Value of Diffuse Splenic and Hepatic 18F-FDG Uptake on PET/CT in Diagnosing Patients with Anemia.

Objective Anemia is a disease with a negative impact on the progression and prognosis of tumor diseases and usually diagnosed by blood tests. Imaging examination has been used as an alternative method to diagnose anemia in addition to blood tests for patients who cannot tolerate blood draw (such as those with severe coagulopathy). The purpose of this study was to investigate the role of diffuse splenic and hepatic 18F-FDG uptake on PET/CT in anemia, by analyzing the correlation between the hemoglobin level and diffuse splenic and hepatic as well as marrow 18F-FDG uptakes in patients who underwent PET/CT. Materials and Methods Forty four patients who underwent a peripheral blood examination within 2 days of a 18F-FDG-PET/CT in our hospital from March 2020 to March 2021 were included. The standardized uptake value (SUV) of the spleen, liver, and marrow were measured, including the maximum value (SUVmax) and the mean value (SUVmean), and the CT value (CTV) of the left ventricular (LV) cavity was measured, including the maximum value (CTVmax) and the mean value (CTVmean). The relation between these measurements and the blood hemoglobin level were analyzed. Results Our analysis revealed that the hemoglobin level was negatively correlated with the SUVmax of the spleen (P ≤ 0.01, R = −0.385), SUVmean of the spleen (P ≤ 0.01, R = −0.395), SUVmax of the liver (P ≤ 0.05, R = −0.365), and SUVmean of the liver (P ≤ 0.05, R = −0.315). The hemoglobin level was positively correlated with CTVmax of the LV cavity (P ≤ 0.05, R = 0.33) and CTVmean of the LV cavity (P ≤ 0.05, R = 0.382), while no statistically significant correlation between the hemoglobin level and the SUV of marrow was observed (P > 0.05). Conclusion Our study revealed a negative correlation between the hemoglobin level and spleen SUV as well as liver SUV, and a positive correlation between the hemoglobin level and CTV of the LV cavity. These findings may provide potential indictors for the imaging diagnosis of anemia, which has important clinical significance in certain clinical scenarios including the evaluation of anemia status in patients who cannot tolerate blood draws and retrospective clinical studies based on patient imaging data.

18F-FDG PET/CT image findings of a dog with adrenocortical carcinoma

BackgroundIn human medicine, 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has been used to differentiate between benign and malignant adrenal tumors and to identify metastases. However, canine adrenocortical carcinomas identified by 18F-FDG PET/computed tomography (CT) have not been reported.Case presentationA 13-year-old, castrated male, Cocker Spaniel dog with severe systolic hypertension exhibited an adrenal mass approximately 3.6 cm in diameter on ultrasonography. There was no evidence of pulmonary metastasis or vascular invasion on thoracic radiography and abdominal ultrasonography, respectively. 18F-FDG PET/CT was performed to identify the characteristics of the adrenal mass and the state of metastasis. One hour after injection of 5.46 MBq/kg 18F-FDG intravenously, the peripheral region of the adrenal mass visually revealed an increased 18F-FDG uptake, which was higher than that of the liver, and the central region of the mass exhibited necrosis. The maximal standardized uptake value (SUV) of the adrenal mass was 3.24; and relative SUV, calculated by dividing the maximal SUV of the adrenal tumor by the mean SUV of the normal liver, was 5.23. Adrenocortical carcinoma was tentatively diagnosed and surgical adrenalectomy was performed. Histopathologic examination of the resected adrenal mass revealed the characteristics of an adrenocortical carcinoma. After adrenalectomy, systolic blood pressure reduced to below 150 mmHg without any medication.ConclusionThis is the first case report of 18F-FDG PET/CT findings in a dog with suspected adrenocortical carcinoma and may provide valuable diagnostic information for adrenocortical carcinoma in dogs.

Radiomic Phenotypes of High and Low Lesion SUV Components for the Prediction of Refractory Disease in Hodgkin's Lymphoma Patients Treated with ABVD Based Therapy

Background: Hodgkin's lymphoma (HL) is a curable malignancy. However, some patients are refractory to frontline therapy. Early prediction of response to frontline therapy could identify patients who may benefit from more intensive therapy. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) has an established role in the management of HL. Radiomic features provide a way of quantifying imaging phenotypes and have shown promising results as predictors of outcomes in different lymphomas. Furthermore, great interest has been focused on the heterogeneity of standardized uptake value (SUV) within a single lesion. Since high SUV component (HSc) and low-SUV component (LSc) regions within a single lesion may be associated with different phenotypical characteristics, the radiomic analysis for each regional SUV component may provide a more complete description of lesions. Therefore, we proposed and evaluated new descriptors to quantify the image phenotypes based on HSc and LSc of lesions in HL.Methods: A total of 61 patients with HL of all stages who were seen at MD Anderson Cancer Center between 2016 and 2020 and had analyzable pre-treatment PET/CT were selected. All patients received standard of care ABVD or AVD regimens with or without radiation (Table 1A). Pre-treatment PET/CT scans were analyzed, and HL lesions were semi-automatically segmented using MIM 7 (Cleveland, OH) based on a SUV max threshold of 2.5. Manual edits were made and reviewed by a nuclear medicine physician and a lymphoma specialist. A total of 110 radiomic features were extracted from the segmented lesions in CT and PET using the open-source package of ‘PyRadiomics’ (Table 1B).Detailed description and algorithms of the extracted radiomics features are available at https://pyradiomics.readthedocs.io/en/latest/features.html. Additionally, each lesion was partitioned into HSc and LSc based on a cutoff value of 3 times the liver SUV mean (Figure A). The ratio of features between SUV components (HSc, LSc) and the lesion area was calculated. Furthermore, the feature difference between HSc and LSc was obtained.The maximum, minimum, average, and standard deviation of the radiomic features within multiple lesions were computed to reveal the distribution of features. A sequential forward feature selection was applied to select the significant features for building a logistic regression model, to predict refractory disease according to Lugano criteria. Two logistic regression models were constructed for early and advanced stage patients. Quantitative measures, namely metabolic tumor volume (MTV), total lesion glycolysis (TLG), and SUV max were measured for comparison. The leave-one-out-cross-validation (LOOCV) was applied to yield the receiver-operator-characteristics curve; the area under the curve (AUC) was then computed to evaluate the performance of the proposed model compared to quantitative measurements using DeLong's test.Results: The average of small dependence high gray level emphasis (GLDM) from PET, the difference of major axis length between high- and low- SUV component from PET, and the difference of 10th Percentile (histogram) between high- and low- SUV component from PET were selected for identifying the refractory disease in early stage lesions; the maximum of correlation (GLCM) from PET, SD of small dependence emphasis (GLDM) from PET, and SD of the inverse difference moment normalized (GLCM) from PET were selected for identifying refractory disease in advanced stage lesions. Based on LOOCV, the proposed radiomics model achieved an AUC of 0.93 for refractory disease prediction, which was significantly superior to MTV (AUC, 0.66; P = 0.01), TLG (AUC, 0.64; P = 0.01), and SUV max (AUC, 0.61; P = 0.01) (Figure B)Conclusion: High and low SUV components-based radiomic model of PET/CT was potentially useful for upfront prediction of refractory HL. Validation in a larger cohort using different segmentation methods, inclusion of additional treatment subgroups, comparison to other predictors, and correlation with survival outcomes are underway. [Display omitted] DisclosuresAhmed: Seagen: Research Funding; Merck: Research Funding; Tessa Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Xencor: Research Funding. Steiner: BMS: Research Funding; Seattle Genetics: Research Funding; Rafael Pharmaceuticals: Research Funding. Pinnix: Merck Inc: Research Funding. Wang: Molecular Templates: Research Funding; The First Afflicted Hospital of Zhejiang University: Honoraria; Hebei Cancer Prevention Federation: Honoraria; Bayer Healthcare: Consultancy; Mumbai Hematology Group: Honoraria; Pharmacyclics: Consultancy, Research Funding; BioInvent: Research Funding; Celgene: Research Funding; Physicians Education Resources (PER): Honoraria; Miltenyi Biomedicine GmbH: Consultancy, Honoraria; Scripps: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Imedex: Honoraria; Dava Oncology: Honoraria; Epizyme: Consultancy, Honoraria; Clinical Care Options: Honoraria; BGICS: Honoraria; CAHON: Honoraria; VelosBio: Consultancy, Research Funding; Loxo Oncology: Consultancy, Research Funding; InnoCare: Consultancy, Research Funding; BeiGene: Consultancy, Honoraria, Research Funding; Anticancer Association: Honoraria; Genentech: Consultancy; AstraZeneca: Consultancy, Honoraria, Research Funding; CStone: Consultancy; Newbridge Pharmaceuticals: Honoraria; Juno: Consultancy, Research Funding; Acerta Pharma: Consultancy, Honoraria, Research Funding; Chinese Medical Association: Honoraria; Kite Pharma: Consultancy, Honoraria, Research Funding; Oncternal: Consultancy, Research Funding; DTRM Biopharma (Cayman) Limited: Consultancy; OMI: Honoraria; Moffit Cancer Center: Honoraria; Lilly: Research Funding.

Validation of Deep Learning-based Augmentation for Reduced 18F-FDG Dose for PET/MRI in Children and Young Adults with Lymphoma.

To investigate if a deep learning convolutional neural network (CNN) could enable low-dose fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/MRI for correct treatment response assessment of children and young adults with lymphoma. In this secondary analysis of prospectively collected data (ClinicalTrials.gov identifier: NCT01542879), 20 patients with lymphoma (mean age, 16.4 years ± 6.4 [standard deviation]) underwent 18F-FDG PET/MRI between July 2015 and August 2019 at baseline and after induction chemotherapy. Full-dose 18F-FDG PET data (3 MBq/kg) were simulated to lower 18F-FDG doses based on the percentage of coincidence events (representing simulated 75%, 50%, 25%, 12.5%, and 6.25% 18F-FDG dose [hereafter referred to as 75%Sim, 50%Sim, 25%Sim, 12.5%Sim, and 6.25%Sim, respectively]). A U.S. Food and Drug Administration-approved CNN was used to augment input simulated low-dose scans to full-dose scans. For each follow-up scan after induction chemotherapy, the standardized uptake value (SUV) response score was calculated as the maximum SUV (SUVmax) of the tumor normalized to the mean liver SUV; tumor response was classified as adequate or inadequate. Sensitivity and specificity in the detection of correct response status were computed using full-dose PET as the reference standard. With decreasing simulated radiotracer doses, tumor SUVmax increased. A dose below 75%Sim of the full dose led to erroneous upstaging of adequate responders to inadequate responders (43% [six of 14 patients] for 75%Sim; 93% [13 of 14 patients] for 50%Sim; and 100% [14 of 14 patients] below 50%Sim; P < .05 for all). CNN-enhanced low-dose PET/MRI scans at 75%Sim and 50%Sim enabled correct response assessments for all patients. Use of the CNN augmentation for assessing adequate and inadequate responses resulted in identical sensitivities (100%) and specificities (100%) between the assessment of 100% full-dose PET, augmented 75%Sim, and augmented 50%Sim images. CNN enhancement of PET/MRI scans may enable 50% 18F-FDG dose reduction with correct treatment response assessment of children and young adults with lymphoma.Keywords: Pediatrics, PET/MRI, Computer Applications Detection/Diagnosis, Lymphoma, Tumor Response, Whole-Body Imaging, Technology AssessmentClinical trial registration no: NCT01542879 Supplemental material is available for this article. © RSNA, 2021.

Intensity of bone involvement: a quantitative 18F-FDG PET/CT evaluation for monitoring outcome of multiple myeloma.

The parameter intensity of bone involvement (IBI) was recently proposed to quantitatively assess patients with multiple myeloma using 18F-fluorodeoxyglucose-PET combined with computed tomography (18F-FDG PET/CT) images. Here, we aimed to calculate IBI variation (ΔIBI) between two consecutive PET/CT of the same patient and verified its relationship with a subjective visual analysis of the images and with clinical outcome. Consecutive whole-body 18F-FDG PET/CT performed to assess the outcomes of 29 patients diagnosed with multiple myeloma were retrospectively evaluated. ΔIBI was calculated after bone segmentation, using liver standardized uptake value as a threshold to determine metabolically active volumes in the skeleton. For each pair of consecutive PET/CTs, two nuclear medicine physicians classified visually the most recent image as PET-remission, PET-progression or PET-stable when compared to the previous examination. The lowest ΔIBI was -1.27 and the highest was 0.29. PET-remission was related to ΔIBI <0 (median = -0.10; -1.27 to +0.03), while PET-progression was related to ΔIBI >0 (median = 0.02; -0.07 to +0.29). ΔIBI around zero was found in images classified as PET-stable (median = 0.00; -0.08 to +0.06). Significant difference in ΔIBI was found between the three groups. Multivariate stepwise analysis showed that IBI value at diagnostic PET/CT, serum calcium and percentage of plasma cells in the bone marrow are independent prognostic factors. Delta IBI provides quantitative data for variations of 18F-FDG uptake in the bone marrow during the follow-up of the patients. In addition, higher IBI values at diagnosis are associated with a higher risk of patient's death.