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Zhao Y, Ren J. 18F-FAPI-04 PET/CT parameters predict PD-L1 expression in esophageal squamous cell carcinoma. Front Immunol 2023; 14:1266843. [PMID: 38035081 PMCID: PMC10684668 DOI: 10.3389/fimmu.2023.1266843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 10/25/2023] [Indexed: 12/02/2023] Open
Abstract
Purpose This prospective study examined whether metabolism parameters obtained using the tracer 18F-AlFNOTA-fibroblast activation protein inhibitor (FAPI)-04 (denoted as 18F-FAPI-04) in positron emission tomography/computed tomography (PET/CT) can predict programmed death ligand-1 (PD-L1) expression in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC). Patients and methods The 24 enrolled LA-ESCC patients underwent an 18F-FAPI-04 PET/CT scan. The maximum, mean, peak and standard deviation standard uptake values (SUVmax, SUVmean, SUVpeak and SUVsd), metabolic tumor volume (MTV), and total lesion FAP (TLF) expression of the primary tumor were collected. Additionally, we evaluated PD-L1 expression on cancer cells by immunohistochemistry and immunofluorescence methods. Patients were divided into negative and positive expressions according to the expression of PD-L1 (CPS < 10 and CPS ≥ 10), and the variables were compared between the two groups. Results The SUVmax, SUVmean, SUVpeak and SUVsd were significantly higher in patients with positive expression than in negative expression (all p < 0.05). Receiver operating characteristic curve analysis identified SUVmean (area under the curve [AUC] = 0.882, p = 0.004), SUVsd (AUC = 0.874, p = 0.005), SUVpeak (AUC = 0.840, p = 0.010) and SUVmax (AUC = 0.765, p = 0.045) as significant predictors of the PD-L1 positive expression, with cutoff values of 9.67, 1.90, 9.67 and 13.71, respectively. On univariate logistic regression analysis, SUVmean (p = 0.045), SUVsd (p = 0.024), and SUVpeak (p = 0.031) were significantly correlated with the PD-L1 positive expression. On multivariable logistic regression analysis, SUVsd (p = 0.035) was an optimum predictor factor for PD-L1 positive expression. Conclusion 18F-FAPI-04 PET/CT parameters, including SUVmean, SUVpeak, and SUVsd, correlated with PD-L1 expression in patients with LA-ESCC, and thus SUVsd was an optimum predictor for PD-L1 positive expression, which could help to explore the existence of immune checkpoints and select ESCC candidates for immunotherapy.
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Affiliation(s)
- Yaqing Zhao
- Department of General Affairs Section, The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Jiazhong Ren
- Department of Medical Imaging, PET-CT Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
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Yano H, Miwa K, Nakayama N, Maruyama T, Ohe N, Ikuta S, Ikegame Y, Yamada T, Takei H, Owashi E, Ohmura K, Yokoyama K, Kumagai M, Muragaki Y, Iwama T, Shinoda J. Differentiation of astrocytoma between grades II and III using a combination of methionine positron emission tomography and magnetic resonance spectroscopy. World Neurosurg X 2023; 19:100193. [PMID: 37123626 PMCID: PMC10141501 DOI: 10.1016/j.wnsx.2023.100193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 04/04/2023] [Indexed: 05/02/2023] Open
Abstract
Objective This study aimed to establish a method for differentiating between grades II and III astrocytomas using preoperative imaging. Methods We retrospectively analyzed astrocytic tumors, including 18 grade II astrocytomas (isocitrate dehydrogenase (IDH)-mutant: IDH-wildtype = 8:10) and 56 grade III anaplastic astrocytomas (37:19). We recorded the maximum methionine (MET) uptake ratios (tumor-to-normal: T/N) on positron emission tomography (PET) and three MRS peak ratios: choline (Cho)/creatine (Cr), N-acetyl aspartate (NAA)/Cr, and Cho/NAA, between June 2015 and June 2020. We then evaluated the cut-off values to differentiate between grades II and III. We compared the grading results between contrast enhancement effects on MR and combinational diagnostic methods (CDM) on a scatter chart using the cutoff values of the T/N ratio and MRS parameters. Results The IDH-mutant group showed significant differences in the Cho/NAA ratio between grades II and III using univariate analysis; however, multiple regression analysis results negated this. The IDH-wildtype group showed no significant differences between the groups. Contrast enhancement effects also showed no significant differences in IDH status. Accordingly, regardless of the IDH status, no statistically independent factors differentiated between grades II and III. However, CDMs showed higher sensitivity and negative predictive value in distinguishing them than MRI contrast examinations for both IDH statuses. We demonstrated a significantly higher diagnostic rate of grade III than of grade II with CDM, which was more striking in the IDH-mutant group than in the wild-type group. Conclusions CDM could be valuable in differentiating between grade II and III astrocytic tumors.
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Affiliation(s)
- Hirohito Yano
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
- Department of Clinical Brain Science, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
- Corresponding author. Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan.
| | - Kazuhiro Miwa
- Department of Neurosurgery, Central Japan International Medical Center, 1-1 Kenkou-no-machi, Minokamo City, 505-8510, Japan
| | - Noriyuki Nakayama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Takashi Maruyama
- Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Naoyuki Ohe
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Soko Ikuta
- Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Yuka Ikegame
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
- Department of Clinical Brain Science, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Tetsuya Yamada
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Hiroaki Takei
- Department of Neurosurgery, Central Japan International Medical Center, 1-1 Kenkou-no-machi, Minokamo City, 505-8510, Japan
| | - Etsuko Owashi
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
| | - Kazufumi Ohmura
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
| | - Kazutoshi Yokoyama
- Department of Neurosurgery, Central Japan International Medical Center, 1-1 Kenkou-no-machi, Minokamo City, 505-8510, Japan
| | - Morio Kumagai
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
| | - Yoshihiro Muragaki
- Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Toru Iwama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Jun Shinoda
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
- Department of Clinical Brain Science, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
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Pulumati A, Pulumati A, Dwarakanath BS, Verma A, Papineni RVL. Technological advancements in cancer diagnostics: Improvements and limitations. Cancer Rep (Hoboken) 2023; 6:e1764. [PMID: 36607830 PMCID: PMC9940009 DOI: 10.1002/cnr2.1764] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 10/20/2022] [Accepted: 11/27/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Cancer is characterized by the rampant proliferation, growth, and infiltration of malignantly transformed cancer cells past their normal boundaries into adjacent tissues. It is the leading cause of death worldwide, responsible for approximately 19.3 million new diagnoses and 10 million deaths globally in 2020. In the United States alone, the estimated number of new diagnoses and deaths is 1.9 million and 609 360, respectively. Implementation of currently existing cancer diagnostic techniques such as positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance spectroscopy (MRS), and molecular diagnostic techniques, have enabled early detection rates and are instrumental not only for the therapeutic management of cancer patients, but also for early detection of the cancer itself. The effectiveness of these cancer screening programs are heavily dependent on the rate of accurate precursor lesion identification; an increased rate of identification allows for earlier onset treatment, thus decreasing the incidence of invasive cancer in the long-term, and improving the overall prognosis. Although these diagnostic techniques are advantageous due to lack of invasiveness and easier accessibility within the clinical setting, several limitations such as optimal target definition, high signal to background ratio and associated artifacts hinder the accurate diagnosis of specific types of deep-seated tumors, besides associated high cost. In this review we discuss various imaging, molecular, and low-cost diagnostic tools and related technological advancements, to provide a better understanding of cancer diagnostics, unraveling new opportunities for effective management of cancer, particularly in low- and middle-income countries (LMICs). RECENT FINDINGS Herein we discuss various technological advancements that are being utilized to construct an assortment of new diagnostic techniques that incorporate hardware, image reconstruction software, imaging devices, biomarkers, and even artificial intelligence algorithms, thereby providing a reliable diagnosis and analysis of the tumor. Also, we provide a brief account of alternative low cost-effective cancer therapy devices (CryoPop®, LumaGEM®, MarginProbe®) and picture archiving and communication systems (PACS), emphasizing the need for multi-disciplinary collaboration among radiologists, pathologists, and other involved specialties for improving cancer diagnostics. CONCLUSION Revolutionary technological advancements in cancer imaging and molecular biology techniques are indispensable for the accurate diagnosis and prognosis of cancer.
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Affiliation(s)
- Akhil Pulumati
- University of Missouri‐Kansas CityKansas CityMissouriUSA
| | - Anika Pulumati
- University of Missouri‐Kansas CityKansas CityMissouriUSA
| | - Bilikere S. Dwarakanath
- Central Research FacilitySri Ramachandra Institute of Higher Education and Research PorurChennaiIndia
- Department of BiotechnologyIndian Academy Degree CollegeBangaloreIndia
| | | | - Rao V. L. Papineni
- PACT & Health LLCBranfordConnecticutUSA
- Department of SurgeryUniversity of Kansas Medical CenterKansas CityKansasUSA
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Application of Metabolic Reprogramming to Cancer Imaging and Diagnosis. Int J Mol Sci 2022; 23:ijms232415831. [PMID: 36555470 PMCID: PMC9782057 DOI: 10.3390/ijms232415831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/12/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
Cellular metabolism governs the signaling that supports physiological mechanisms and homeostasis in an individual, including neuronal transmission, wound healing, and circadian clock manipulation. Various factors have been linked to abnormal metabolic reprogramming, including gene mutations, epigenetic modifications, altered protein epitopes, and their involvement in the development of disease, including cancer. The presence of multiple distinct hallmarks and the resulting cellular reprogramming process have gradually revealed that these metabolism-related molecules may be able to be used to track or prevent the progression of cancer. Consequently, translational medicines have been developed using metabolic substrates, precursors, and other products depending on their biochemical mechanism of action. It is important to note that these metabolic analogs can also be used for imaging and therapeutic purposes in addition to competing for metabolic functions. In particular, due to their isotopic labeling, these compounds may also be used to localize and visualize tumor cells after uptake. In this review, the current development status, applicability, and limitations of compounds targeting metabolic reprogramming are described, as well as the imaging platforms that are most suitable for each compound and the types of cancer to which they are most appropriate.
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Noninvasive Delineation of Glioma Infiltration with Combined 7T Chemical Exchange Saturation Transfer Imaging and MR Spectroscopy: A Diagnostic Accuracy Study. Metabolites 2022; 12:metabo12100901. [PMID: 36295803 PMCID: PMC9607140 DOI: 10.3390/metabo12100901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 09/14/2022] [Accepted: 09/19/2022] [Indexed: 11/16/2022] Open
Abstract
For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST and MRS to predict glioma infiltration. Eighteen glioma patients of different tumor grades were enrolled in this study; 18F-fluoroethyltyrosine (FET)-PET, amide proton transfer CEST at 7 Tesla(T), MRS and conventional MR at 3T were conducted preoperatively. Multi modalities and their association were evaluated using Pearson correlation analysis patient-wise and voxel-wise. Both CEST (R = 0.736, p < 0.001) and MRS (R = 0.495, p = 0.037) correlated with FET-PET, while the correlation between CEST and MRS was weaker. In subgroup analysis, APT values were significantly higher in high grade glioma (3.923 ± 1.239) and IDH wildtype group (3.932 ± 1.264) than low grade glioma (3.317 ± 0.868, p < 0.001) or IDH mutant group (3.358 ± 0.847, p < 0.001). Using high FET uptake as the standard, the CEST/MRS combination (AUC, 95% CI: 0.910, 0.907−0.913) predicted tumor infiltration better than CEST (0.812, 0.808−0.815) or MRS (0.888, 0.885−0.891) alone, consistent with contrast-enhancing and T2-hyperintense areas. Probability maps of tumor presence constructed from the CEST/MRS combination were preliminarily verified by multi-region biopsies. The combination of 7T CEST/MRS might serve as a promising non-radioactive alternative to delineate glioma infiltration, thus reshaping the guidance for tumor resection and irradiation.
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Yano H, Ikegame Y, Miwa K, Nakayama N, Maruyama T, Ikuta S, Yokoyama K, Muragaki Y, Iwama T, Shinoda J. Radiological Prediction of Isocitrate Dehydrogenase (IDH) Mutational Status and Pathological Verification for Lower-Grade Astrocytomas. Cureus 2022; 14:e27157. [PMID: 36017268 PMCID: PMC9393092 DOI: 10.7759/cureus.27157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/22/2022] [Indexed: 11/06/2022] Open
Abstract
Background and objective The isocitrate dehydrogenase (IDH) status of patients with World Health Organization (WHO) grade II or III astrocytoma is essential for understanding its biological features and determining therapeutic strategies. This study aimed to use radiological analysis to predict the IDH status of patients with lower-grade astrocytomas and to verify the pathological implications. Methods In this study, 47 patients with grade II (17 cases) or III astrocytomas (30 cases), based on 2016 WHO Classification, underwent methionine (MET) positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) on the same day between January 2013 and June 2020. The patients were retrospectively assessed. Immunohistochemistry showed 23 cases of IDH-mutant and 24 of IDH-wildtype. Based on fluid-attenuated recovery inversion (FLAIR)/T2 imaging, three doctors blinded to clinical data independently allocated 18 patients to the clear boundary group between the tumor and the normal brain and 29 to the unclear boundary group. The peak ratios of N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, and Cho/NAA and the tumor-to-normal region (T/N) ratio for maximum accumulation in MET-PET were calculated. For statistical analysis, Fisher’s exact test was used to assess associations between two variables, and the Mann-Whitney U test to compare the values between the IDH-wildtype and IDH-mutant groups. The optimal cut-off values of MET T/N ratio and MRS parameters for discriminating IDH-wildtype from IDH-mutant were obtained using receiver operating characteristics curves. Results The unclear boundary group had significantly more IDH-wildtype cases than the clear boundary group (P<0.001). The IDH-wildtype group had significantly lower Cho/Cr (<1.84) and Cho/NAA (<1.62) ratios (P=0.02 and P=0.047, respectively) and a higher MET T/N ratio (>1.44, P=0.02) than the IDH-mutant group. The odds for the IDH-wildtype were 0.22 for patients who fulfilled none of the four criteria, including boundary status and three ratios, and 0.9 for all four criteria. Conclusions These results suggest that the combination of MRI, MRS, and MET-PET examination could be helpful for the prediction of IDH status in WHO grade II/III gliomas.
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Han S, Qu FW, Wang PF, Liu YX, Li SW, Yan CX. Development and Validation of a Nomogram Model Based on Hematological Indicators for Predicting the Prognosis of Diffused Gliomas. Front Surg 2022; 9:803237. [PMID: 35495765 PMCID: PMC9043458 DOI: 10.3389/fsurg.2022.803237] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 03/08/2022] [Indexed: 01/23/2023] Open
Abstract
Background Diffused gliomas are aggressive malignant brain tumors. Various hematological factors have been proven to predict the prognosis of patients with gliomas. The aim of this study is to integrate these hematological markers and develop a comprehensive system for predicting the prognosis of patients with gliomas. Method This retrospective study included 723 patients pathologically diagnosed with diffused gliomas. Hematological indicators were collected preoperatively, including neutrophil-to-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), albumin globulin ratio (AGR), platelet distribution width (PDW), red blood cell distribution width (RDW), fibrinogen (FIB), and prognostic nutritional index (PNI). Least absolute shrinkage and selection operator (LASSO) Cox was applied to screen the hematological indicators for a better prediction of patients' prognosis and to build an inflammation-nutrition score. A nomogram model was developed to predict the overall survival (OS), which included age, tumor grade, IDH-1 mutations, and inflammation-nutrition score. Result Patients were randomly divided into a primary cohort (n = 509) and a validation cohort (n = 214). There was no difference in age and IDH-1 mutation frequency between the cohorts. In the primary cohort, NLR, LMR, AGR, FIB, and PNI were selected to build an inflammation nutrition score. Patients with a high-risk inflammation-nutrition score had a short median OS of 17.40 months compared with 27.43 months in the low-risk group [HR 2.54; 95% CI (1.91–3.37); p < 0.001]. Moreover, age, tumor grade, IDH-1 mutations, and inflammation-nutrition score were independent prognostic factors in the multivariate analysis and thus were included in the nomogram model. The nomogram model showed a high prediction value with a Harrell's concordance index (C-index) of 0.75 [95% CI (0.72–0.77)]. The validation cohort supported these results. Conclusion The prognostic nomogram model provided a high prognostic predictive power for patients with gliomas.
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Affiliation(s)
- Song Han
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Fang-wen Qu
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
- Grade 2018, Medical College, Qingdao University, Qingdao, China
| | - Peng-fei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Ying-xin Liu
- Grade 2018, Medical College, Qingdao University, Qingdao, China
| | - Shou-wei Li
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Chang-xiang Yan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
- *Correspondence: Chang-xiang Yan
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Zhou W, Huang Q, Wen J, Li M, Zhu Y, Liu Y, Dai Y, Guan Y, Zhou Z, Hua T. Integrated CT Radiomics Features Could Enhance the Efficacy of 18F-FET PET for Non-Invasive Isocitrate Dehydrogenase Genotype Prediction in Adult Untreated Gliomas: A Retrospective Cohort Study. Front Oncol 2021; 11:772703. [PMID: 34869011 PMCID: PMC8640504 DOI: 10.3389/fonc.2021.772703] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/01/2021] [Indexed: 01/03/2023] Open
Abstract
Purpose We aimed to investigate the predictive models based on O-[2-(18F)fluoroethyl]-l-tyrosine positron emission tomography/computed tomography (18F-FET PET/CT) radiomics features for the isocitrate dehydrogenase (IDH) genotype identification in adult gliomas. Methods Fifty-eight consecutive pathologically confirmed adult glioma patients with pretreatment 18F-FET PET/CT were retrospectively enrolled. One hundred and five radiomics features were extracted for analysis in each modality. Three independent radiomics models (PET-Rad Model, CT-Rad Model and PET/CT-Rad Model) predicting IDH mutation status were generated using the least absolute shrinkage and selection operator (LASSO) regression analysis based on machine learning algorithms. All-subsets regression and cross validation were applied for the filter and calibration of the predictive radiomics models. Besides, semi-quantitative parameters including maximum, peak and mean tumor to background ratio (TBRmax, TBRpeak, TBRmean), standard deviation of glioma lesion standardized uptake value (SUVSD), metabolic tumor volume (MTV) and total lesion tracer uptake (TLU) were obtained and filtered for the simple model construction with clinical feature of brain midline involvement status. The area under the receiver operating characteristic curve (AUC) was applied for the evaluation of the predictive models. Results The AUC of the simple predictive model consists of semi-quantitative parameter SUVSD and dichotomized brain midline involvement status was 0.786 (95% CI 0.659-0.883). The AUC of PET-Rad Model building with three 18F-FET PET radiomics parameters was 0.812 (95% CI 0.688-0.902). The AUC of CT-Rad Model building with three co-registered CT radiomics parameters was 0.883 (95% CI 0.771-0.952). While the AUC of the combined 18F-FET PET/CT-Rad Model building with three CT and one PET radiomics features was 0.912 (95% CI 0.808-0.970). DeLong test results indicated the PET/CT-Rad Model outperformed the PET-Rad Model (p = 0.048) and simple predictive model (p = 0.034). Further combination of the PET/CT-Rad Model with the clinical feature of dichotomized tumor location status could slightly enhance the AUC to 0.917 (95% CI 0.814-0.973). Conclusion The predictive model combining 18F-FET PET and integrated CT radiomics features could significantly enhance and well balance the non-invasive IDH genotype prediction in untreated gliomas, which is important in clinical decision making for personalized treatment.
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Affiliation(s)
- Weiyan Zhou
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Qi Huang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianbo Wen
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming Li
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuhua Zhu
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yan Liu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.,Jinan Guoke Medical Engineering Technology Development Co., LTD, Jinan, China
| | - Yakang Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.,Jinan Guoke Medical Engineering Technology Development Co., LTD, Jinan, China
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhirui Zhou
- Radiation Oncology Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Tao Hua
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
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Zhang A, Xu H, Zhang Z, Liu Y, Han X, Yuan L, Ni Y, Gao S, Xu Y, Chen S, Jiang J, Chen Y, Zhang X, Lou M, Zhang J. Establishment of a nomogram with EMP3 for predicting clinical outcomes in patients with glioma: A bi-center study. CNS Neurosci Ther 2021; 27:1238-1250. [PMID: 34268874 PMCID: PMC8446216 DOI: 10.1111/cns.13701] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 06/10/2021] [Accepted: 06/16/2021] [Indexed: 12/20/2022] Open
Abstract
Aim To demonstrate the clinical value of epithelial membrane protein 3 (EMP3) with bioinformatic analysis and clinical data, and then to establish a practical nomogram predictive model with bicenter validation. Methods The data from CGGA and TCGA database were used to analyze the expression of EMP3 and its correlation with clinical prognosis. Then, we analyzed EMP3 expression in samples from 179 glioma patients from 2013 to 2017. Univariate and multivariate cox regression were used to predict the prognosis with multiple factors. Finally, a nomogram to predict poor outcomes was formulated. The accuracy and discrimination of nomograms were determined with ROC curve and calibration curve in training and validation cohorts. Results EMP3 was significantly higher in higher‐grade glioma and predicted poor prognosis. In multivariate analysis, high expression of EMP3 (HR = 2.842, 95% CI 1.984–4.071), WHO grade (HR = 1.991, 95% CI 1.235–3.212), and IDH1 mutant (HR = 0.503, 95% CI 0.344–0.737) were included. The nomogram was constructed based on the above features, which represented great predictive value in clinical outcomes. Conclusion This study demonstrated EMP3 as a novel predictor for clinical progression and clinical outcomes in glioma. Moreover, the nomogram with EMP3 expression represented a practical approach to provide individualized risk assessment for glioma patients.
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Affiliation(s)
- Anke Zhang
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Houshi Xu
- Department of Neurosurgery, School of Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Zeyu Zhang
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yibo Liu
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Xiaying Han
- Department of Orthopedics, School of Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | | | - Yunjia Ni
- Department of Neurosurgery, School of Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Shiqi Gao
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yuanzhi Xu
- Department of Neurosurgery, School of Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Sheng Chen
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | | | - Yike Chen
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Xiaotao Zhang
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Meiqing Lou
- Department of Neurosurgery, School of Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jianmin Zhang
- Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
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Unterrainer M, Ruf V, von Rohr K, Suchorska B, Mittlmeier LM, Beyer L, Brendel M, Wenter V, Kunz WG, Bartenstein P, Herms J, Niyazi M, Tonn JC, Albert NL. TERT-Promoter Mutational Status in Glioblastoma - Is There an Association With Amino Acid Uptake on Dynamic 18F-FET PET? Front Oncol 2021; 11:645316. [PMID: 33996563 PMCID: PMC8121001 DOI: 10.3389/fonc.2021.645316] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/26/2021] [Indexed: 12/19/2022] Open
Abstract
Objective The mutation of the ‘telomerase reverse transcriptase gene promoter’ (TERTp) has been identified as an important factor for individual prognostication and tumorigenesis and will be implemented in upcoming glioma classifications. Uptake characteristics on dynamic 18F-FET PET have been shown to serve as additional imaging biomarker for prognosis. However, data on the correlation of TERTp-mutational status and amino acid uptake on dynamic 18F-FET PET are missing. Therefore, we aimed to analyze whether static and dynamic 18F-FET PET parameters are associated with the TERTp-mutational status in de-novo IDH-wildtype glioblastoma and whether a TERTp-mutation can be predicted by dynamic 18F-FET PET. Methods Patients with de-novo IDH-wildtype glioblastoma, WHO grade IV, available TERTp-mutational status and dynamic 18F-FET PET scan prior to any therapy were included. Here, established clinical parameters maximal and mean tumor-to-background-ratios (TBRmax/TBRmean), the biological-tumor-volume (BTV) and minimal-time-to-peak (TTPmin) on dynamic PET were analyzed and correlated with the TERTp-mutational status. Results One hundred IDH-wildtype glioblastoma patients were evaluated; 85/100 of the analyzed tumors showed a TERTp-mutation (C228T or C250T), 15/100 were classified as TERTp-wildtype. None of the static PET parameters was associated with the TERTp-mutational status (median TBRmax 3.41 vs. 3.32 (p=0.362), TBRmean 2.09 vs. 2.02 (p=0.349) and BTV 26.1 vs. 22.4 ml (p=0.377)). Also, the dynamic PET parameter TTPmin did not differ in both groups (12.5 vs. 12.5 min, p=0.411). Within the TERTp-mutant subgroups (i.e., C228T (n=23) & C250T (n=62)), the median TBRmax (3.33 vs. 3.69, p=0.095), TBRmean (2.08 vs. 2.09, p=0.352), BTV (25.4 vs. 30.0 ml, p=0.130) and TTPmin (12.5 vs. 12.5 min, p=0.190) were comparable, too. Conclusion Uptake characteristics on dynamic 18F-FET PET are not associated with the TERTp-mutational status in glioblastoma However, as both, dynamic 18F-FET PET parameters as well as the TERTp-mutation status are well-known prognostic biomarkers, future studies should investigate the complementary and independent prognostic value of both factors in order to further stratify patients into risk groups.
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Affiliation(s)
- Marcus Unterrainer
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.,Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Viktoria Ruf
- Department of Neuropathology and Prion Research, LMU Munich, Munich, Germany
| | - Katharina von Rohr
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Bogdana Suchorska
- German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | | | - Leonie Beyer
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Vera Wenter
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang G Kunz
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jochen Herms
- Department of Neuropathology and Prion Research, LMU Munich, Munich, Germany
| | - Maximilian Niyazi
- German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Jörg C Tonn
- German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | - Nathalie Lisa Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Heidelberg, Germany
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