Cancer Biotherapy and Radiopharmaceuticals最新文献

{"title":"Skin Cancer Detection Using Deep Learning Approaches.","authors":"Shafiul Haque, Faraz Ahmad, Vineeta Singh, Darin Mansor Mathkor, Ashjan Babegi","doi":"10.1089/cbr.2024.0161","DOIUrl":"https://doi.org/10.1089/cbr.2024.0161","url":null,"abstract":"<p><p><i><b>Aim:</b></i> This review examined multiple deep learning (DL) methods, including artificial neural networks (ANNs), convolutional neural networks (CNNs), k-nearest neighbors (KNNs), as well as generative adversarial networks (GANs), relying on their abilities to differentially extract key features for the identification and classification of skin lesions. <i><b>Background:</b></i> Skin cancer is among the most prevalent cancer types in humans and is associated with tremendous socioeconomic and psychological burdens for patients and caregivers alike. Incidences of skin cancers have progressively increased during the last decades. Early diagnoses of skin cancers may aid in the implementation of more effective treatment and therapeutic regimens. Indeed, several recent studies have focused on early detection strategies for skin cancer. Among the lesion features that can aid the recognition and characterization of skin cancers are symmetry, color, size, and shape. <i><b>Results:</b></i> Our assessment indicates that CNNs delivered maximum accuracy in visual lesion recognition, yet GANs have surfaced as a strong tool for training augmentation through simulated image creation. However, there were significant limitations associated with existing datasets, such as provision of insufficient skin tone variability, demanding computational needs, and unequal lesion representations, which may hamper efficiency, inclusivity, and generalizability of DL models. Researchers must combine diverse high-resolution datasets within a structural framework to develop efficient computational models with unsupervised learning methods to enhance noninvasive and precise skin cancer detection. <i><b>Conclusion:</b></i> The breakthroughs in image-based computational skin cancer detection may be crucial in reducing the requirement of invasive diagnostic tests and expanding the scope of skin cancer screening toward broad demographics, thereby aiding early cancer detection in a time- and cost-efficient manner.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An LNM-Associated Gene Signature for Prognostic Prediction and Immune Profiling in Head and Neck Squamous Cell Carcinoma.","authors":"Zhenzhen Wang, Zhenhua Wu, Lixin Cheng, Qi Huang, Jian Zhang, Yuan Ren, Juntao Huang, Yi Shen","doi":"10.1089/cbr.2024.0147","DOIUrl":"https://doi.org/10.1089/cbr.2024.0147","url":null,"abstract":"<p><p>Lymph node metastasis (LNM) plays a critical role in the prognosis of head and neck squamous cell carcinoma (HNSCC). To enhance prognostic predictions and investigate the molecular interplay between LNM and HNSCC, we developed an LNM-associated gene signature. Data was sourced from The Cancer Genome Atlas (TCGA), encompassing RNA-sequencing and clinical profiles. We stratified patients based on LNM status and identified differentially expressed genes (DEGs) between lymph node-negative (N0) and lymph node-positive (N1-3) groups. A prognostic model was then constructed while employing Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses. Patients were randomly allocated into training (70%) and internal validation (30%) cohorts, with an additional external dataset used for validation. The predictive model's performance was assessed through receiver operating characteristic curves and survival analyses. We identified 79 LNM-related prognostic DEGs that formed the basis of our LNM-related risk score (LNMRS). This score stratified patients into low- and high-risk categories, with those having lower LNMRS exhibiting improved survival outcomes, increased immune cell infiltration, and enhanced responses to immunotherapy (PD-1/CTLA4 inhibitors) and chemotherapy. In contrast, patients with high LNMRS showed poorer prognosis and reduced immune responsiveness. Our LNM-related model provides insights into the molecular mechanisms linking LNM and HNSCC and offers a promising tool for personalized treatment strategies. This approach underscores the potential of integrating LNM status with gene expression profiles to refine prognosis and optimize therapeutic interventions in HNSCC.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on \"IL-21 and IL-33 May Be Effective Biomarkers to Predict the Efficacy of PD-1 Monoclonal Antibody for Advanced Cholangiocarcinoma\".","authors":"Hinpetch Daungsupawong, Viroj Wiwanitkit","doi":"10.1089/cbr.2025.0039","DOIUrl":"https://doi.org/10.1089/cbr.2025.0039","url":null,"abstract":"","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Value of 99mTc-Ubiquicidin Scintigraphy in Differentiating Bacterial from Nonbacterial Pneumonia.","authors":"Sepideh Khoshbakht, Saba Zare, Mahdi Khatuni, Mohammadali Ghodsirad, Mohadeseh Bayat, Fateme Sadat Mirabootalebi, Elahe Pirayesh, Mahasti Amoui, Ghazal Norouzi","doi":"10.1089/cbr.2024.0202","DOIUrl":"https://doi.org/10.1089/cbr.2024.0202","url":null,"abstract":"<p><p><b><i>Purpose:</i></b> Differentiating purely viral from bacterial etiologies continues to be a challenging yet key step in the management of community-acquired pneumonia (CAP), further highlighted since the COVID-19 pandemic. This study aims to evaluate the utility of 99mTc-ubiquicidin (UBI) in the differentiation of bacterial from nonbacterial pneumonia. <b><i>Methods:</i></b> A total of 30 patients with CAP were allocated into groups A, bacterial (<i>n</i> = 15), and B, viral pneumonia (<i>n</i> = 15). All patients underwent 99mTc-UBI scan with planar and single-photon emission computed tomography (SPECT) images of thorax acquired at 30 and 180 min postinjection. Target-to-background (T/B) ratios were calculated with values >1.4 interpreted as positive for bacterial infection. Correlation was made with computed tomography (CT) scan and polymerase chain reaction (PCR) results. <b><i>Results:</i></b> UBI scan was positive in 43.3% (<i>n</i> = 13) of patients, with sensitivity, specificity, and accuracy of 86.7%, 100%, and 93.3%, respectively, and close correlation with chest CT scan and PCR results (<i>p</i>-value = 0.000). Planar images were generally not helpful. Receiver operating characteristic curve analysis indicated similar diagnostic performance for 30-min and 3-h SPECT images by implementing T/B thresholds of 1.2 and 1.33, respectively. <b><i>Conclusions:</i></b> 99mTc-UBI SPECT is a promising modality for differentiating purely viral from bacterial or superimposed bacterial pneumonia and provides reliable evidence either to mandate or withhold administration of antibiotics in patients with CAP.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143558885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Baseline ¹⁸F-FDG PET Radiomics Predicting Therapeutic Efficacy of Diffuse Large B-Cell Lymphoma after R-CHOP (-Like) Therapy.","authors":"Fenglian Jing, Xinchao Zhang, Yunuan Liu, Xiaolin Chen, Xinming Zhao, Xiaoshan Chen, Huiqing Yuan, Meng Dai, Na Wang, Jingya Han, Jingmian Zhang","doi":"10.1089/cbr.2024.0115","DOIUrl":"10.1089/cbr.2024.0115","url":null,"abstract":"<p><p><b><i>Objective:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> The stacking model, along with the integrated model that combines stacking with the NCCN-IPI and SD_max (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, <i>p</i> = 0.139) or the testing cohort (AUC: 0.768 vs. 0.781, <i>p</i> = 0.668), the integrated model exhibited higher values for sensitivity, PPV, NPV, accuracy, and NB-AUC than the stacking model. <b><i>Conclusion:</i></b> Baseline PET radiomics could predict therapeutic efficacy in DLBCL after R-CHOP (-like) therapy, with improved predictive performance when incorporating clinical features and SD_max.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"114-121"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of Radiosynthesis and First in-Human Dosimetry of ⁶⁸Ga-NOTA-UBI-29-41: A Proof of Concept Study.","authors":"Parul Thakral, Nishant Rana, Navneet Singh, Subha Shankar Das, Mrinalini Koley, Jatin Gupta, Dharmender Malik, Ishita Sen","doi":"10.1089/cbr.2024.0082","DOIUrl":"10.1089/cbr.2024.0082","url":null,"abstract":"<p><p><b><i>Background:</i></b> Antimicrobial peptides (AMPs) such as UBI-29-41 offer a distinctive approach for precise detection due to their unique interactions with bacteria and makes them promising candidates for specific and selective imaging. The study was aimed to corroborate the in-house manual synthesis of ⁶⁸Ga-NOTA-UBI-29-41, evaluate its uptake in patients with suspected infection, and estimate of patient-specific dosimetry to ensure optimal clinical application. <b><i>Materials and Methods:</i></b> ⁶⁸Ga-NOTA-UBI-29-41 was synthesized by using a variable amount of UBI-29-41 (60-90 μg) to 555 MBq of ⁶⁸Ga in 0.05 M hydrochloric acid (HCl) and heating the reaction sample for 12 min at 90°C at pH: 3.5-4 to obtain the radiopeptide with high yield and high radiochemical purity (RCP). ⁶⁸Ga-NOTA-UBI-29-41 positron emission tomography/computed tomography (PET/CT) scans at variable timepoints were done to evaluate its biodistribution and maximum uptake time. Furthermore, patient-specific dosimetric estimation was done using the HERMES software. <b><i>Results:</i></b> A total of 5 μg/37 MBq (5 μg/mCi) of NOTA-UBI-29-41 for 12 min at 90°C were the optimal parameters to obtain 88%-90% of yield and 98%-99 % of RCP. ⁶⁸Ga-NOTA-UBI-29-41 showed expeditious blood clearance and high renal excretion. The optimal time for imaging of infection with ⁶⁸Ga-NOTA-UBI-29-41 was found to be at 60 min postinjection (<i>n</i> = 8). The critical organ was the urinary bladder, receiving an average dose of 138.02 ± 45.92 µSv/MBq, followed by 53.81 ± 13.72 µSv/MBq for kidneys with a mean effective dose of 1.52 ± 0.64 mSv. <b><i>Conclusion:</i></b> The protocol for in-house manual labeling of ⁶⁸Ga-NOTA-UBI-29-41 was reproducible, providing high yield and RCP. ⁶⁸Ga-NOTA-UBI-29-41 administration was found to be safe and nontoxic. The favorable biodistribution and the first-in-human patient-specific dosimetry ensure optimal clinical application.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"104-113"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-Artificial Intelligence Symbiotic Reporting for Theranostic Cancer Care.","authors":"J Harvey Turner","doi":"10.1089/cbr.2024.0216","DOIUrl":"10.1089/cbr.2024.0216","url":null,"abstract":"<p><p>Reporting of diagnostic nuclear images in clinical cancer management is generally qualitative. Theranostic treatment with ¹⁷⁷Lu radioligands for prostate cancer and neuroendocrine tumors is routinely given as the same arbitrary fixed administered activity to every patient. Nuclear oncology, as currently practiced with ¹⁷⁷Lu-prostate-specific membrane antigen and ¹⁷⁷Lu peptide receptor radionuclide therapy, cannot, therefore, be characterized as personalized precision medicine. The evolution of artificial intelligence (AI) could change this \"one-size-fits-all\" approach to theranostics, through development of a symbiotic relationship with physicians. Combining quantitative data collection, collation, and analytic computing power of AI algorithms with the clinical expertise, empathy, and personal care of patients by their physician envisions a new paradigm in theranostic reporting for molecular imaging and radioligand treatment of cancer. Human-AI interaction will facilitate the compilation of a comprehensive, integrated nuclear medicine report. This holistic report would incorporate radiomics to quantitatively analyze diagnostic digital imaging and prospectively calculate the radiation absorbed dose to tumor and critical normal organs. The therapy activity could then be accurately prescribed to deliver a preordained, effective, tumoricidal radiation absorbed dose to tumor, while minimizing toxicity in the particular patient. Post-therapy quantitative imaging would then validate the actual dose delivered and sequential pre- and post-treatment dosimetry each cycle would allow individual dose prescription and monitoring over the entire course of theranostic treatment. Furthermore, the nuclear medicine report would use AI analysis to predict likely clinical outcome, predicated upon AI definition of tumor molecular biology, pathology, and genomics, correlated with clinical history and laboratory data. Such synergistic comprehensive reporting will enable self-assurance of the nuclear physician who will necessarily be deemed personally responsible and accountable for the theranostic clinical outcome. Paradoxically, AI may thus be expected to enhance the practice of phronesis by the nuclear physician and foster a truly empathic trusting relationship with the cancer patient.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"89-95"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[⁶⁸Ga]Ga-FAPI04 Outperforms [¹⁸F]FDG PET/CT for Detecting Nodal Metastasis of Head and Neck Squamous Cell Carcinoma: A Single-Center Experience.","authors":"Serkan Kuyumcu, Emine Göknur Isik, Cömert Şen, Duygu Has-Şimsek, Bora Başaran, Zeynep Gözde Özkan, Fikret Büyükkaya, Yasemin Şanlı","doi":"10.1089/cbr.2024.0112","DOIUrl":"10.1089/cbr.2024.0112","url":null,"abstract":"<p><p>This study assesses fibroblast activated protein inhibitor (FAPI) targeted PET/CT imaging against [¹⁸F]FDG PET/CT (FDG PET) for detecting nodal involvement in head and neck squamous cell carcinoma (HNSCC), intending to improve diagnostic precision for metastatic lymph nodes and lay the groundwork for future investigations. <b><i>Methods:</i></b> Patients diagnosed with HNSCC were retrospectively enrolled. All patients underwent [⁶⁸Ga]Ga-FAPI04 PET/CT (FAPI PET) and FDG PET within 6 d. Primary tumor, lymph nodes, and tracer uptake were visually and quantitatively compared. The metastatic lymph nodes were evaluated using patient-and lesion-based analyses, with biopsy or postoperative histopathological examination as the reference. <b><i>Results:</i></b> The cohort includes 24 patients (17 men, 7 women; mean age 60 ± 11.8 years) who underwent FDG and FAPI PET for preoperative diagnostic workup or restaging due to known recurrence of HNSCC. Lesions included 24 primary tumors, 54 cervical lymph nodes, and 5 metastases. Primary tumors exhibited significant uptake on both PET modalities (median maximum standardized uptake value [SUV_max]: FDG 19.4 ± 11.6, FAPI 16.9 ± 4.6), with no statistically significant difference (<i>p</i> > 0.5). For lymph nodes, FAPI and FDG PET showed median SUV_max of 9.18 ± 6.77 and 9.67 ± 6.5, respectively. The patient-based analysis found FDG PET sensitivity at 88.2% and FAPI PET at 94.1%, with FAPI PET specificity significantly higher (85.7% vs. 42.8% for FDG PET). Lesion-based analysis revealed FAPI PET sensitivity and specificity at 84.2% and 93.7%, respectively, contrasting FDG PET's at 81.5% and 25%, respectively. <b><i>Conclusion:</i></b> This study underscores the efficacy of FAPI PET in detecting primary tumors in HNSCC. Furthermore, FAPI PET shows improved specificity over FDG PET for metastatic lymph nodes advocating further investigations for integrating FAPI PET into HNSCC clinical protocols for its enhanced precision in detecting metastatic lymph nodes.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"122-129"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acknowledgment of Reviewers 2024.","authors":"","doi":"10.1089/cbr.2024.48720.revack","DOIUrl":"https://doi.org/10.1089/cbr.2024.48720.revack","url":null,"abstract":"","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":"40 2","pages":"151-152"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Same-Day Positron Emission Tomography/Computed Tomography with ⁶⁸Ga-Radiolabeled Fibroblast Activation Protein Inhibitors and ¹⁸F-Fluorodeoxyglucose Imaging for Gastrointestinal Cancers.","authors":"Xiaoshan Chen, Yunuan Liu, Xinming Zhao, Fenglian Jing, Bin Wang, Xiaolin Chen, Xiao Pang, Jingmian Zhang, Jianfang Wang, Zhaoqi Zhang, Jingya Han, Mengjiao Wang","doi":"10.1089/cbr.2024.0182","DOIUrl":"10.1089/cbr.2024.0182","url":null,"abstract":"<p><p><b><i>Objective:</i></b> We investigated the clinical practicability of same-day ⁶⁸Ga-radiolabeled fibroblast activation protein inhibitors (⁶⁸Ga-FAPI)-first and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) imaging and compared it with same-day ¹⁸F-FDG-first or 2-day procedures in diagnosing gastrointestinal cancers. <b><i>Materials and Methods:</i></b> Sixty-five patients with confirmed gastrointestinal cancers were divided into same-day ⁶⁸Ga-FAPI-first group (Group A), same-day ¹⁸F-FDG-first group (Group B), and 2-day group (Group C). Low-dose CT and low injection activity were performed on ⁶⁸Ga-FAPI positron emission tomography/computed tomography (PET/CT). Interval times, radiation dose, diagnostic performance, and detectability were assessed among groups. Additionally, the uptake, tumor-to-liver ratio (TLR), diagnostic efficacy, and TNM stage were compared between the two modalities. <b><i>Results:</i></b> The total waiting time for Group C was significantly longer than that for Group A or B (both <i>p</i> < 0.001). The total dose-length product and effective dose decreased in all groups. There were comparable detectability and diagnostic performance among groups (all <i>p</i> > 0.05). The within-group analysis in Group B indicated that ⁶⁸Ga-FAPI PET/CT had higher uptake in the primary and recurrent lesions than ¹⁸F-FDG without differences in TLR, due to higher liver background on ⁶⁸Ga-FAPI PET than Group A or C (both <i>p</i> < 0.001).⁶⁸Ga-FAPI PET/CT possessed higher accuracy than ¹⁸F-FDG and changed staging in 14 patients (14/65, 21.54%). <b><i>Conclusions:</i></b> The same-day ⁶⁸Ga-FAPI-first and ¹⁸F-FDG imaging reduced examination waiting time without increased radiation dose, simultaneously achieving excellent diagnostic performance and improving clinical staging in diagnosing gastrointestinal cancers.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"130-138"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}