Value of 18F-FDG PET/CT-based radiomics features for differentiating primary lung cancer and solitary lung metastasis in patients with colorectal adenocarcinoma.

OBJECTIVE: To investigate the value and applicability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomics in differentiating primary lung cancer (PLC) from solitary lung metastasis (SLM) in patients with colorectal cancer (CRC). MATERIALS AND METHODS: This retrospective study included 103 patients with CRC and solitary pulmonary nodules (SPNs). The least absolute shrinkage and selection operator (LASSO) was used to screen for optimal radiomics features and establish a PET/CT radiomics model. PET/CT Visual and complex models (combining radiomics with PET/CT visual features) were developed. The area under the receiver operating characteristic (ROC) curve (AUC) was used to determine the predictive value and diagnostic efficiency of the models. RESULTS: The AUC of the PET/CT radiomics model for differentiating PLC from SLM was 0.872 (95% CI: 0.806-0.939), which was not different from that of the visual (0.829 [95% CI: 0.749-0.908; p = .352]). However, the AUC of the complex model (0.936 [95% CI:0.892-0.981]) was significantly higher than that of the PET/CT radiomics (p = .005) and visual model (p = .001). The sensitivity (SEN), specificity (SPE), accuracy (ACC), positive predictive value (PPV), and negative predictive value (NPV) of PET/CT radiomics for differentiating PLC from SLM were 0.720, 0.887, 0.806, 0.857, and 0.770, respectively. CONCLUSION: PET/CT radiomics can effectively distinguish PLC and SLM in patients with CRC and SPNs and guide the implementation of personalized treatment.

Baseline 18F-FDG PET Radiomics Predicting Therapeutic Efficacy of Diffuse Large B-Cell Lymphoma after R-CHOP (-Like) Therapy.

Objective: This study aimed to predict therapeutic efficacy among diffuse large B-cell lymphoma (DLBCL) after R-CHOP (-like) therapy using baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) radiomics. Methods: A total of 239 patients with DLBCL were enrolled in this study, with 82 patients having refractory/relapsed disease. The radiomics signatures were developed using a stacking ensemble approach. The efficacy of the radiomics signatures, the National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI), conventional PET parameters model, and their combinations in assessing refractory/relapse risk were evaluated using receiver operating characteristic (ROC) curves, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and decision curve analysis. Results: The stacking model, along with the integrated model that combines stacking with the NCCN-IPI and SDmax (the distance between the two lesions farthest apart, normalized to the patient's body surface area), showed remarkable predictive capabilities with a high area under the curve (AUC), sensitivity, specificity, PPV, NPV, accuracy, and significant net benefit of the AUC (NB-AUC). Although no significant differences were observed between the combined and stacking models in terms of the AUC in either the training cohort (AUC: 0.992 vs. 0.985, p = 0.139) or the testing cohort (AUC: 0.768 vs. 0.781, p = 0.668), the integrated model exhibited higher values for sensitivity, PPV, NPV, accuracy, and NB-AUC than the stacking model. Conclusion: Baseline PET radiomics could predict therapeutic efficacy in DLBCL after R-CHOP (-like) therapy, with improved predictive performance when incorporating clinical features and SDmax.

Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma with extranodal involvement.

PURPOSE: The objective of this investigation is to explore the capability of baseline 18F-FDG PET/CT radiomics to predict the prognosis of diffuse large B-cell lymphoma (DLBCL) with extranodal involvement (ENI). METHODS: 126 patients diagnosed with DLBCL with ENI were included in the cohort. The least absolute shrinkage and selection operator (LASSO) Cox regression was utilized to refine the optimum subset from the 1328 features. Cox regression analyses were employed to discern significant clinical variables and conventional PET parameters, which were then employed with radiomics score to develop combined model for predicting both progression-free survival (PFS) and overall survival (OS). The fitness and the predictive capability of the models were assessed via the Akaike information criterion (AIC) and concordance index (C-index). RESULTS: 62 patients experienced disease recurrence or progression and 28 patients ultimately died. The combined model exhibited a lower AIC value compared to the radiomics model and SDmax/clinical variables for both PFS (507.101 vs. 510.658 vs. 525.506) and OS (215.667 vs. 230.556 vs. 219.313), respectively. The C-indices of the combined model, radiomics model, and SDmax/clinical variables were 0.724, 0.704, and 0.615 for PFS, and 0.842, 0.744, and 0.792 for OS, respectively. Kaplan--Meier curves showed significantly higher rates of relapse and mortality among patients classified as high-risk compared to those classified as low-risk (all P < 0.05). CONCLUSIONS: The combined model of clinical variables, conventional PET parameters, and baseline PET/CT radiomics features demonstrates a higher accuracy in predicting the prognosis of DLBCL with ENI.

Human Biodistribution and Radiation Dosimetry of the Targeting Fibroblast Growth Factor Receptor 1-Positive Tumors Tracer [68Ga]Ga-DOTA-FGFR1-Peptide.

Objective: [68Ga]Ga-DOTA-FGFR1-peptide is a novel positron emission tomography (PET) radiotracer targeting fibroblast growth factor receptor 1 (FGFR1). This study aimed to evaluate the safety, biodistribution, radiation dosimetry, and imaging potential of [68Ga]Ga-DOTA-FGFR1-peptide. Methods: The FGFR1-targeting peptide DOTA-(PEG2)-KAEWKSLGEEAWHSK was synthesized by manual solid-phase peptide synthesis and high-performance liquid chromatography purification, and labeled with 68Ga with DOTA as chelating agent. We recruited 14 participants and calculated the radiation dose of 4 of these pathologically confirmed nontumor subjects using OLINDA/EXM 2.2.0 software. At the same time, the imaging potential in 10 of these lung cancer patients was evaluated. Results: The biodistribution of [68Ga]Ga-DOTA-FGFR1-peptide in 4 subjects showed the highest uptake in the bladder and kidney. Dosimetry analysis indicated that the bladder wall received the highest effective dose (3.73E-02 mSv/MBq), followed by the lungs (2.36E-03 mSv/MBq) and red bone marrow (2.09E-03 mSv/MBq). No normal organs were found to have excess specific absorbed doses. The average systemic effective dose was 4.97E-02 mSv/MBq. The primary and metastatic tumor lesions were clearly visible on PET/computed tomography (CT) images in 10 patients. Conclusion: Our results indicate that [68Ga]Ga-DOTA-FGFR1-peptide has a good dosimetry profile and can be used safely in humans, and it has significant potential value for clinical PET/CT imaging.

Comparison of Measurement and Prognostic Power of SUV Between High-Definition and Standard PET Imaging in Non-Small Cell Lung Cancer Patients.

This study aimed to evaluate the measurement and prognostic ability of the SUVmax of whole-body tumors (SUVmaxwb) in non-small cell lung cancer (NSCLC) patients, comparing high-definition (HD) PET imaging with standard-definition (SD) PET imaging. Methods: The study included 242 consecutive NSCLC patients who underwent baseline 18F-FDG PET/CT from April 2018 to January 2021. Two imaging techniques were used: HD PET (using ordered-subsets expectation maximization with point-spread function modeling and time-of-flight techniques and smaller voxels) and SD PET (with ordered-subsets expectation maximization and time-of-flight techniques). SUVmaxwb was determined by measuring all the tumor lesions in the whole body, and tumor-to-background ratio (TBR) was calculated using the background SUVmean of various body parts. Results: The patient cohort had an average age of 68.3 y, with 59.1% being female. During a median follow-up of 29.6 mo, 83 deaths occurred. SUVmaxwb was significantly higher in HD PET than SD PET, with respective medians of 17.4 and 11.8. The TBR of 1,125 tumoral lesions was also higher in HD PET. Univariate Cox regression analysis showed that SUVmaxwb from both HD and SD PET were significantly associated with overall survival. However, after adjusting for TNM (tumor, node, metastasis) stage, only SUVmaxwb from SD PET remained significantly associated with survival. Conclusion: HD PET imaging in NSCLC patients yields higher SUVmaxwb and TBR, enhancing tumor visibility. Despite this, its prognostic value is less significant than SD PET after adjusting clinical TNM stage. Thus, consideration should be given to using HD PET reconstruction to increase tumor visibility, and SD PET is recommended for NSCLC patient prognostication and therapeutic evaluation, as well as for the classification of lung nodules.

Brain Nocardiosis Mimicking Intracerebral Invasion on 68 Ga-Pentixafor PET/CT in a Patient With Multiple Myeloma.

ABSTRACT: Brain nocardiosis is an uncommon but severe disease associated with high mortality. We present a case of brain nocardiosis with elevated tracer uptake on both 68 Ga-pentixafor and 18 F-FDG PET/CT, mimicking intracerebral invasion of multiple myeloma. This case demonstrates that nocardiosis should be considered in the differential diagnosis of brain lesions found on PET/CT with increased tracer accumulation in immunocompromised patients.

Comparison of 68Ga-FAPI-04 and 18F-FDG PET/CT in diagnosing ovarian cancer.

PURPOSE: This study assesses the diagnostic performance of 68Ga-FAPI-04 PET/CT compared to 18F-FDG PET/CT in primary, recurrent, and metastatic ovarian cancer. METHODS: Seventy-nine ovarian cancer patients who performed 68Ga-FAPI-04 and 18F-FDG PET/CT were recruited. The target-to-background ratio (TBR), maximum standardized uptake value (SUVmax), the number of positive lesions, visual assessment, the peritoneal cancer index (PCI) score, staging/restaging, and treatment strategies were compared from the corresponding PET/CT. Additionally, we analyzed and contrasted the diagnostic efficacy in both scans. RESULTS: Among all patients, 6 were assessed for initial assessment and 73 for recurrence and metastasis detection. For all lesions, 68Ga-FAPI-04 PET/CT demonstrated greater TBR than 18F-FDG PET/CT. 68Ga-FAPI-04 PET/CT demonstrated higher sensitivity for peritoneal metastases including patient-based and lesion-based analysis (95.00% vs. 83.33%, P = 0.065; 90.16% vs. 60.66%, P < 0.001) and a higher PCI score [median PCI: 6 (4, 12) vs. 4 (2, 8), P < 0.001]. According to the visual assessment, 68Ga-FAPI-04 PET revealed larger extent metastases in 55.93% (33/59) of the patients with peritoneal metastases. 68Ga-FAPI-04 was upstaged in 7 patients (8.86%, 7/79) and discrepancies in both scans caused treatment strategies to change in 11 patients (13.92%, 11/79). CONCLUSION: 68Ga-FAPI-04 PET/CT outperforms 18F-FDG PET/CT in identifying metastases and can be a potential supplement for managing ovarian cancer patients.

Value of Semi-Quantitative Parameters of 68Ga-FAPI-04 PET/CT in Primary Malignant and Benign Diseases: A Comparison with 18F-FDG.

Objectives: We aimed to compare the value of the semiquantitative parameters of 68Ga-labeled FAP inhibitor (68Ga-FAPI)-04 positron emission tomography/computed tomography (PET/CT) and 18F-fluorodeoxyglucose (18F-FDG) in diagnosing primary malignant and benign diseases. Materials and Methods: 18F-FDG and 68Ga-FAPI-04 PET/CT images of 80 patients were compared. Semiquantitative parameters, including maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), peak SUV by lean body mass (SULpeak), metabolic tumor volume (or tumor volume of FAPI; FAPI-TV), and TLG (or total lesion activity of FAPI; FAPI-TLA), were automatically obtained using the IntelliSpace Portal image processing workstation with a threshold of 40% SUVmax. The liver blood pool was measured as the background, and the tumor-to-background ratio (TBRliver) was calculated. Results: In all malignant lesions, FAPI-TV and FAPI-TLA were higher in 68Ga-FAPI-04 PET/CT than in 18F-FDG. In the subgroup analysis, 68Ga-FAPI-04 had higher FAPI-TV and FAPI-TLA and lower SUVmax than 18F-FDG had in group A, including gynecological tumor, esophageal, and colorectal cancers. However, six semiquantitative parameters were higher in group B (the other malignant tumors). For the benign diseases, SUVmax, SUVmean, SUVpeak, and SULpeak were lower in 68Ga-FAPI-04 PET/CT than in 18F-FDG. 68Ga-FAPI-04 PET/CT showed a lower liver background and a higher TBRliver than 18F-FDG did. 68Ga-FAPI-04 PET/CT had higher accuracy, sensitivity, and specificity than 18F-FDG had. Conclusion: More accurate semiquantitative parameters and lower abdominal background in 68Ga-FAPI-04 PET/CT make it more competitive in the differential diagnosis of malignant and benign diseases than in 18F-FDG.

Noninvasive Assessment of HER2 Expression Status in Gastric Cancer Using 18F-FDG Positron Emission Tomography/Computed Tomography-Based Radiomics: A Pilot Study.

Purpose: Immunohistochemistry (IHC) is the main method to detect human epidermal growth factor receptor 2 (HER2) expression levels. However, IHC is invasive and cannot reflect HER2 expression status in real time. The aim of this study was to construct and verify three types of radiomics models based on 18F-fuorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging and to evaluate the predictive ability of these radiomics models for the expression status of HER2 in patients with gastric cancer (GC). Patients and Methods: A total of 118 patients with GC were enrolled in this study. 18F-FDG PET/CT imaging was performed prior to surgery. The LIFEx software package was applied to extract PET and CT radiomics features. The minimum absolute contraction and selection operator (least absolute shrinkage and selection operator [LASSO]) algorithm was used to select the best radiomics features. Three machine learning methods, logistic regression (LR), support vector machine (SVM), and random forest (RF) models, were constructed and verified. The Synthetic Minority Oversampling Technique (SMOTE) was applied to address data imbalance. Results: In the training and test sets, the area under the curve (AUC) values of the LR, SVM, and RF models were 0.809, 0.761, 0.861 and 0.628, 0.993, 0.717, respectively, and the Brier scores were 0.118, 0.214, and 0.143, respectively. Among the three models, the LR and RF models exhibited extremely good prediction performance. The AUC values of the three models significantly improved after SMOTE balanced the data. Conclusions: 18F-FDG PET/CT-based radiomics models, especially LR and RF models, demonstrate good performance in predicting HER2 expression status in patients with GC and can be used to preselect patients who may benefit from HER2-targeted therapy.

Feasibility of One-Day PET/CT Scanning Protocol with 68Ga-DOTA-FAPI-04 and 18F-FDG for the Detection of Ovarian Cancer Recurrence and Metastasis.

Objective: The objective of this study was to investigate the feasibility of 1-d 68Ga-DOTA-FAPI-04 and 18F-FDG (2-deoxy-2[18F]fluoro-d-glucose) positron emission tomography/computed tomography (PET/CT) for detecting ovarian cancer recurrence and metastasis. Materials and Methods: Fifty-two patients who underwent 18F-FDG and 68Ga-DOTA-FAPI-04 PET/CT were divided into 1- and 2-d groups. Image acquisition, injection time, and total waiting time were compared. For the 68Ga-DOTA-FAPI-04 PET/CT scans, low-dose CT scans and low injection dosages were employed, and total radiation dose was assessed for both protocols. The comparative analysis included assessment of patient-based detection rates and lesion-based diagnostic efficacy. Results: The total waiting time was significantly shorter in the 1-d group than in the 2-d group (p = 0.000). The radiation doses stemming from internal radiation and external radiation between the groups showed no differences (p = 0.151 vs. 0.716). In the patient-based analysis, the detection rates for local recurrence, peritoneal, lymph node, and other metastases were not significantly different in both protocols (p ∈ [0.351, 1.000]). For the lesion-based analysis, no differences were noted in terms of sensitivity, specificity, positive predictive value, negative predictive value, and accuracy (p ∈ [0.371, 1.000]). Conclusions: The 1-d PET/CT protocol reduced waiting time and exhibited equivalent detectability compared with the 2-d protocol, suggesting its clinical value.

Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults. Standard treatment includes chemoimmunotherapy with R-CHOP or similar regimens. Despite treatment advancements, many patients with DLBCL experience refractory disease or relapse. While baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) parameters have shown promise in predicting survival, they may not fully capture lesion heterogeneity. This study aimed to assess the prognostic value of baseline 18F-FDG PET radiomics features in comparison with clinical factors and metabolic parameters for assessing 2-year progression-free survival (PFS) and 5-year overall survival (OS) in patients with DLBCL. RESULTS: A total of 201 patients with DLBCL were enrolled in this study, and 1328 radiomics features were extracted. The radiomics signatures, clinical factors, and metabolic parameters showed significant prognostic value for individualized prognosis prediction in patients with DLBCL. Radiomics signatures showed the lowest Akaike information criterion (AIC) value and highest Harrell's concordance index (C-index) value in comparison with clinical factors and metabolic parameters for both PFS (AIC: 571.688 vs. 596.040 vs. 576.481; C-index: 0.732 vs. 0.658 vs. 0.702, respectively) and OS (AIC: 339.843 vs. 363.671 vs. 358.412; C-index: 0.759 vs. 0.667 vs. 0.659, respectively). Statistically significant differences were observed in the area under the curve (AUC) values between the radiomics signatures and clinical factors for both PFS (AUC: 0.768 vs. 0.681, P = 0.017) and OS (AUC: 0.767 vs. 0.667, P = 0.023). For OS, the AUC of the radiomics signatures were significantly higher than those of metabolic parameters (AUC: 0.767 vs. 0.688, P = 0.007). However, for PFS, no significant difference was observed between the radiomics signatures and metabolic parameters (AUC: 0.768 vs. 0.756, P = 0.654). The combined model and the best-performing individual model (radiomics signatures) alone showed no significant difference for both PFS (AUC: 0.784 vs. 0.768, P = 0.163) or OS (AUC: 0.772 vs. 0.767, P = 0.403). CONCLUSIONS: Radiomics signatures derived from PET images showed the high predictive power for progression in patients with DLBCL. The combination of radiomics signatures, clinical factors, and metabolic parameters may not significantly improve predictive value beyond that of radiomics signatures alone.

Multiple Intrahepatic Inflammatory Myofibroblastic Tumor on 68 Ga-FAPI and 18 F-FDG PET/CT.

ABSTRACT: A 31-year-old man with multiple intrahepatic inflammatory myofibroblastoma tumor was referred to nuclear medicine department to assess its malignant potential. Multiple lesions in the liver exhibited 68 Ga-FAPI uptake at different degrees. Instead, there was no abnormal 18 F-FDG activity in the other hepatic lesions under the normal liver background except for the puncture site. This case reflects tumor heterogeneity of the disease and shows the potential value of 68 Ga-FAPI PET/CT for the evaluation of hepatic inflammatory myofibroblastoma tumor.

18F-labeled FGFR1 peptide: a new PET probe for subtype FGFR1 receptor imaging.

Introduction: The fibroblast growth factor receptor (FGFR) family is highly expressed in a variety of tumor types and represents a new target for cancer therapy. Different FGFR subtype aberrations have been found to exhibit highly variable sensitivity and efficacy to FGFR inhibitors. Methods: The present study is the first to suggest an imaging method for assessing FGFR1 expression. The FGFR1-targeting peptide NOTA-PEG2-KAEWKSLGEEAWHSK was synthesized by manual solid-phase peptide synthesis and high-pressure liquid chromatography (HPLC) purification and then labeled with fluorine-18 using NOTA as a chelator. In vitro and in vivo experiments were conducted to evaluate the stability, affinity and specificity of the probe. Tumor targeting efficacy and biodistribution were evaluated by micro-PET/CT imaging in RT-112, A549, SNU-16 and Calu-3 xenografts. Results: The radiochemical purity of [18F]F-FGFR1 was 98.66% ± 0.30% (n = 3) with excellent stability. The cellular uptake rate of [18F]F-FGFR1 in the RT-112 cell line (FGFR1 overexpression) was higher than that in the other cell lines and could be blocked by the presence of excess unlabeled FGFR1 peptide. Micro-PET/CT imaging revealed a significant concentration of [18F]F-FGFR1 in RT-112 xenografts with no or very low uptake in nontargeted organs and tissues, which demonstrated that [18F]F-FGFR1 was selectively taken up by FGFR1-positive tumors. Conclusion: [18F]F-FGFR1 showed high stability, affinity, specificity and good imaging capacity for FGFR1-overexpressing tumors in vivo, which provides new application potential in the visualization of FGFR1 expression in solid tumors.

Value of pre-treatment 18F-FDG PET/CT radiomics in predicting the prognosis of stage III-IV colorectal cancer.

Background and purpose: To investigate the value of radiomics features extracted from pre-treatment 18F-FDG PET/CT in predicting the outcomes of stage III-IV colorectal cancer (CRC), which may assist in clinical management strategies and precise treatment of stage III-IV CRC. Materials and methods: 124 patients with pathologically confirmed stage III-IV CRC who underwent pre-treatment 18F-FDG PET/CT scans were enrolled in this study. The least absolute shrinkage and selection operator Cox regression (LASSO-Cox) was used to select radiomics features, and the radiomics scores (Rad-scores) were calculated to build radiomics models. The performance of radiomics models was represented by the concordance index (C-index) and compared with clinical models and complex model. The bootstrap resampling method was used to create validation sets. Additionally, nomograms were developed based on complex models. Results: The C-indices of the radiomics model for predicting PFS and OS were 0.712 (95%CI: 0.680-0.744) and 0.758 (0.728-0.789), respectively. In the clinical model, these values were 0.690 (0.664-0.0.717) and 0.738 (0.709-0.767), respectively. However, in the complex model were 0.734 (0.705-0.762) and 0.780 (0.754-0.807), respectively. The Kaplan-Meier curves demonstrated that the radiomics model could effectively separate patients with stage III-IV stage CRC into high- and low-risk groups (p < 0.001). Multivariate Cox regression analysis confirmed the independent prognostic value of Rad-scores. Conclusion: Pre-treatment 18F-FDG PET/CT radiomics features can stratify the risk of patients with stage III-IV CRC and accurately predict their outcomes. These findings could be clinically valuable for precision treatment and management decisions in stage III-IV CRC.

Predicting PD-L1 expression status in patients with non-small cell lung cancer using [18F]FDG PET/CT radiomics.

BACKGROUND: In recent years, immune checkpoint inhibitor (ICI) therapy has greatly changed the treatment prospects of patients with non-small cell lung cancer (NSCLC). Among the available ICI therapy strategies, programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitors are the most widely used worldwide. At present, immunohistochemistry (IHC) is the main method to detect PD-L1 expression levels in clinical practice. However, given that IHC is invasive and cannot reflect the expression of PD-L1 dynamically and in real time, it is of great clinical significance to develop a new noninvasive, accurate radiomics method to evaluate PD-L1 expression levels and predict and filter patients who will benefit from immunotherapy. Therefore, the aim of our study was to assess the predictive power of pretherapy [18F]-fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT)-based radiomics features for PD-L1 expression status in patients with NSCLC. METHODS: A total of 334 patients with NSCLC who underwent [18F]FDG PET/CT imaging prior to treatment were analyzed retrospectively from September 2016 to July 2021. The LIFEx7.0.0 package was applied to extract 63 PET and 61 CT radiomics features. In the training group, the least absolute shrinkage and selection operator (LASSO) regression model was employed to select the most predictive radiomics features. We constructed and validated a radiomics model, clinical model and combined model. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to evaluate the predictive performance of the three models in the training group and validation group. In addition, a radiomics nomogram to predict PD-L1 expression status was established based on the optimal predictive model. RESULTS: Patients were randomly assigned to a training group (n = 233) and a validation group (n = 101). Two radiomics features were selected to construct the radiomics signature model. Multivariate analysis showed that the clinical stage (odds ratio [OR] 1.579, 95% confidence interval [CI] 0.220-0.703, P < 0.001) was a significant predictor of different PD-L1 expression statuses. The AUC of the radiomics model was higher than that of the clinical model in the training group (0.706 vs. 0.638) and the validation group (0.761 vs. 0.640). The AUCs in the training group and validation group of the combined model were 0.718 and 0.769, respectively. CONCLUSION: PET/CT-based radiomics features demonstrated strong potential in predicting PD-L1 expression status and thus could be used to preselect patients who may benefit from PD-1/PD-L1-based immunotherapy.

Case Report: 68Ga-FAPI PET/CT, a more advantageous detection mean of gastric, peritoneal, and ovarian metastases from breast cancer.

Breast cancer is the most common malignant tumor in adult women. Its common metastatic sites are lymph nodes, bones, lungs, the liver, and the brain. It is so rare for a patient with breast cancer to have metastases of the gastrointestinal tract, peritoneum, and ovary at the same time that the clinical reporting rate is low. We present a case of a 61-year-old woman who underwent right mastectomy and chemoradiotherapy 3 years ago because of mixed invasive ductal-lobular breast cancer. This time, she came to the hospital due to the symptom of stomach discomfort for 2 weeks. The gastroscopy biopsy result showed gastric metastasis from breast cancer. Then, 18F-FDG imaging and 68Ga-FAPI PET/CT imaging were performed for further diagnosis; 68Ga-FAPI PET/CT demonstrated a significantly elevated FAPI activity in the thickened gastric wall, peritoneum, and bilateral adnexal areas, which was superior to that of 18F-FDG. Finally, a biopsy of suspicious lesions was taken for pathological and histochemical examination, which confirmed that, in addition to the gastric metastasis, the peritoneum and bilateral ovaries were all consistent with metastatic breast cancer.