Hirata K, Kobayashi K, Wong KP, Manabe O, Surmak A, Tamaki N, Huang SC. A semi-automated technique determining the liver standardized uptake value reference for tumor delineation in FDG PET-CT. PLoS One. 2014 Aug 27;9(8):e105682. doi: 10.1371/journal.pone.0105682. PMID: 25162396; PMCID: PMC4146536.
This is our first publication of Metavol. In this article, we proposed a new method to define a volume-of-interest in the liver reproducibly. Please choose this paper if you kindly cite a Metavol paper. Papers citing Metavol (this paper) are listed here.
Larobina M, Megna R, Solla R. Comparison of three freeware software packages for 18F-FDG PET texture feature calculation. Jpn J Radiol. 2021 Feb 17. doi: 10.1007/s11604-021-01100-0. Epub ahead of print. PMID: 33595789.
Metavol was compared with LIFEx (which I believe most widely used) and CGITA in terms of texture analysis.
Hirata K, Manabe O, Magota K, Furuya S, Shiga T, Kudo K. A Preliminary Study to Use SUVmax of FDG PET-CT as an Identifier of Lesion for Artificial Intelligence. Front Med (Lausanne). 2021 Apr 28;8:647562. doi: 10.3389/fmed.2021.647562. PMID: 33996855; PMCID: PMC8113693.
The maximum standardized uptake value (SUVmax) is often described in daily diagnostic reports of FDG-PET/CT. If SUVmax can be used as an identifier of lesion, that would greatly help AI interpret diagnostic reports. We demonstrated that the lesion can be localized using SUVmax strings.
Preclinical studies (n=1)
Maruyama K, Okada T, Ueha T, Isohashi K, Ikeda H, Kanai Y, Sasaki K, Gentsu T, Ueshima E, Sofue K, Nogami M, Yamaguchi M, Sugimoto K, Sakai Y, Hatazawa J, Murakami T. In vivo evaluation of percutaneous carbon dioxide treatment for improving intratumoral hypoxia using 18F-fluoromisonidazole PET-CT. Oncol Lett. 2021 Mar;21(3):207. doi: 10.3892/ol.2021.12468. Epub 2021 Jan 14. PMID: 33574946; PMCID: PMC7816357.
Intratumoral hypoxia in a nude mouse model was measured using FMISO and Metavol.
Clinical applications for malignant/inflammatory diseases
Brain tumor (n=3)
Kobayashi K, Hirata K, Yamaguchi S, Manabe O, Terasaka S, Kobayashi H, Shiga T, Hattori N, Tanaka S, Kuge Y, Tamaki N. Prognostic value of volume-based measurements on (11)C-methionine PET in glioma patients. Eur J Nucl Med Mol Imaging. 2015 Jun;42(7):1071-80. doi: 10.1007/s00259-015-3046-1. Epub 2015 Apr 8. PMID: 25852010.
Manabe O, Yamaguchi S, Hirata K, Kobayashi K, Kobayashi H, Terasaka S, Toyonaga T, Magota K, Kuge Y, Tamaki N, Shiga T, Kudo K. Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma. Diagnostics (Basel). 2021 Jan 28;11(2):189. doi: 10.3390/diagnostics11020189. PMID: 33525709; PMCID: PMC7911154.
Yamaguchi S, Hirata K, Toyonaga T, Kobayashi K, Ishi Y, Motegi H, Kobayashi H, Shiga T, Tamaki N, Terasaka S, Houkin K. Change in 18F-Fluoromisonidazole PET Is an Early Predictor of the Prognosis in the Patients with Recurrent High-Grade Glioma Receiving Bevacizumab Treatment. PLoS One. 2016 Dec 9;11(12):e0167917. doi: 10.1371/journal.pone.0167917. PMID: 27936194; PMCID: PMC5148016.
Head and neck cancer (n=2)
Na KJ, Choi H. Tumor Metabolic Features Identified by 18F-FDG PET Correlate with Gene Networks of Immune Cell Microenvironment in Head and Neck Cancer. J Nucl Med. 2018 Jan;59(1):31-37. doi: 10.2967/jnumed.117.194217. Epub 2017 Jun 6. PMID: 28588149.
Nakagawa J, Fujima N, Hirata K, Tang M, Tsuneta S, Suzuki J, Harada T, Ikebe Y, Homma A, Kano S, Minowa K, Kudo K. Utility of the deep learning technique for the diagnosis of orbital invasion on CT in patients with a nasal or sinonasal tumor. Cancer Imaging. 2022 Sep 22;22(1):52. doi: 10.1186/s40644-022-00492-0. PMID: 36138422; PMCID: PMC9502604.
Thyroid cancer (n=1)
Uchiyama Y, Hirata K, Watanabe S, Okamoto S, Shiga T, Okada K, Ito YM, Kudo K. Development and validation of a prediction model based on the organ-based metabolic tumor volume on FDG-PET in patients with differentiated thyroid carcinoma. Ann Nucl Med. 2021 Aug 11. doi: 10.1007/s12149-021-01664-x. Epub ahead of print. PMID: 34379284.
Thymic carcinoma (n=1)
Hamaji M, Koyasu S, Omasa M, Nakakura A, Morita S, Nakagawa T, Miyahara S, Miyata R, Yokoyama Y, Kawakami K, Suga M, Takahashi M, Terada Y, Muranishi Y, Miyahara R, Sumitomo R, Huang CL, Aoyama A, Takahashi Y, Date H. Are volume-dependent parameters in positron emission tomography predictive of postoperative recurrence after resection in patients with thymic carcinoma? Surg Today. 2021 Feb;51(2):322-326. doi: 10.1007/s00595-020-02045-z. Epub 2020 Jun 13. PMID: 32535710.
Breast cancer (n=5)
Satoh Y, Imai M, Hirata K, Asakawa Y, Ikegawa C, Onishi H. Optimal relaxation parameters of dynamic row-action maximum likelihood algorithm and post-smoothing filter for image reconstruction of dedicated breast PET. Ann Nucl Med. 2021 Mar 27. doi: 10.1007/s12149-021-01604-9. Epub ahead of print. PMID: 33772738.
Satoh Y, Hirata K, Tamada D, Funayama S, Onishi H. Texture Analysis in the Diagnosis of Primary Breast Cancer: Comparison of High-Resolution Dedicated Breast Positron Emission Tomography (dbPET) and Whole-Body PET/CT. Front Med (Lausanne). 2020 Dec 23;7:603303. doi: 10.3389/fmed.2020.603303. PMID: 33425949; PMCID: PMC7793660.
Brito AE, Santos A, Sasse AD, Cabello C, Oliveira P, Mosci C, Souza T, Amorim B, Lima M, Ramos CD, Etchebehere E. 18F-Fluoride PET/CT tumor burden quantification predicts survival in breast cancer. Oncotarget. 2017 May 30;8(22):36001-36011. doi: 10.18632/oncotarget.16418. PMID: 28415595; PMCID: PMC5482633.
Satoh Y, Imai M, Ikegawa C, Onishi H. Image quality evaluation of real low-dose breast PET. Jpn J Radiol. 2022 May 25. doi: 10.1007/s11604-022-01293-y. Epub ahead of print. PMID: 35612727.
Satoh Y, Imai M, Ikegawa C, Hirata K, Abo N, Kusuzaki M, Oyama-Manabe N, Onishi H. Effect of radioactivity outside the field of view on image quality of dedicated breast positron emission tomography: preliminary phantom and clinical studies. Ann Nucl Med. 2022 Oct 8. doi: 10.1007/s12149-022-01789-7. Epub ahead of print. PMID: 36207497.
Lung cancer (n=1)
Okazaki E, Seura H, Hasegawa Y, Okamura T, Fukuda H. Prognostic Value of the Volumetric Parameters of Dual-Time-Point 18F-FDG PET/CT in Non-Small Cell Lung Cancer Treated With Definitive Radiation Therapy. AJR Am J Roentgenol. 2019 Dec;213(6):1366-1373. doi: 10.2214/AJR.19.21376. Epub 2019 Sep 11. PMID: 31509426.
Cardiac sarcoidosis (n=10)
Manabe O, Ohira H, Hirata K, Hayashi S, Naya M, Tsujino I, Aikawa T, Koyanagawa K, Oyama-Manabe N, Tomiyama Y, Magota K, Yoshinaga K, Tamaki N. Use of 18F-FDG PET/CT texture analysis to diagnose cardiac sarcoidosis. Eur J Nucl Med Mol Imaging. 2019 Jun;46(6):1240-1247. doi: 10.1007/s00259-018-4195-9. Epub 2018 Oct 16. PMID: 30327855.
Manabe O, Koyanagawa K, Hirata K, Oyama-Manabe N, Ohira H, Aikawa T, Furuya S, Naya M, Tsujino I, Tomiyama Y, Otaki Y, Anzai T, Tamaki N. Prognostic Value of 18F-FDG PET Using Texture Analysis in Cardiac Sarcoidosis. JACC Cardiovasc Imaging. 2020 Apr;13(4):1096-1097. doi: 10.1016/j.jcmg.2019.11.021. Epub 2020 Jan 15. PMID: 31954654.
Manabe O, Yoshinaga K, Ohira H, Masuda A, Sato T, Tsujino I, Yamada A, Oyama-Manabe N, Hirata K, Nishimura M, Tamaki N. The effects of 18-h fasting with low-carbohydrate diet preparation on suppressed physiological myocardial (18)F-fluorodeoxyglucose (FDG) uptake and possible minimal effects of unfractionated heparin use in patients with suspected cardiac involvement sarcoidosis. J Nucl Cardiol. 2016 Apr;23(2):244-52. doi: 10.1007/s12350-015-0226-0. Epub 2015 Aug 5. PMID: 26243179; PMCID: PMC4785205.
Koyanagawa K, Naya M, Aikawa T, Manabe O, Kuzume M, Ohira H, Tsujino I, Tamaki N, Anzai T. Prognostic value of phase analysis on gated single photon emission computed tomography in patients with cardiac sarcoidosis. J Nucl Cardiol. 2021 Feb;28(1):128-136. doi: 10.1007/s12350-019-01660-9. Epub 2019 Feb 27. PMID: 30815835.
Omote K, Naya M, Koyanagawa K, Aikawa T, Manabe O, Nagai T, Kamiya K, Kato Y, Komoriyama H, Kuzume M, Tamaki N, Anzai T. 18F-FDG uptake of the right ventricle is an important predictor of histopathologic diagnosis by endomyocardial biopsy in patients with cardiac sarcoidosis. J Nucl Cardiol. 2020 Dec;27(6):2135-2143. doi: 10.1007/s12350-018-01541-7. Epub 2019 Jan 4. PMID: 30610523.
Furuya S, Naya M, Manabe O, Hirata K, Ohira H, Aikawa T, Koyanagawa K, Magota K, Tsujino I, Anzai T, Kuge Y, Oyama-Manabe N, Kudo K, Shiga T, Tamaki N. 18F-FMISO PET/CT detects hypoxic lesions of cardiac and extra-cardiac involvement in patients with sarcoidosis. J Nucl Cardiol. 2019 Dec 9. doi: 10.1007/s12350-019-01976-6. Epub ahead of print. PMID: 31820409.
Koyanagawa K, Naya M, Aikawa T, Manabe O, Furuya S, Kuzume M, Oyama-Manabe N, Ohira H, Tsujino I, Anzai T. The rate of myocardial perfusion recovery after steroid therapy and its implication for cardiac events in cardiac sarcoidosis and primarily preserved left ventricular ejection fraction. J Nucl Cardiol. 2019 Oct 11. doi: 10.1007/s12350-019-01916-4. Epub ahead of print. PMID: 31605274.
Manabe O, Kroenke M, Aikawa T, Murayama A, Naya M, Masuda A, Oyama-Manabe N, Hirata K, Watanabe S, Shiga T, Katoh C, Tamaki N. Volume-based glucose metabolic analysis of FDG PET/CT: The optimum threshold and conditions to suppress physiological myocardial uptake. J Nucl Cardiol. 2019 Jun;26(3):909-918. doi: 10.1007/s12350-017-1122-6. Epub 2017 Dec 14. PMID: 29243072.
Furuya S, Manabe O, Ohira H, Hirata K, Aikawa T, Naya M, Tsujino I, Koyanagawa K, Anzai T, Oyama-Manabe N, Shiga T. Which is the proper reference tissue for measuring the change in FDG PET metabolic volume of cardiac sarcoidosis before and after steroid therapy? EJNMMI Res. 2018 Oct 5;8(1):94. doi: 10.1186/s13550-018-0447-8. PMID: 30291527; PMCID: PMC6173675.
Kobayashi Y, Sato T, Nagai T, Hirata K, Tsuneta S, Kato Y, Komoriyama H, Kamiya K, Konishi T, Omote K, Ohira H, Kudo K, Konno S, Anzai T. Association of high serum soluble interleukin 2 receptor levels with risk of adverse events in cardiac sarcoidosis. ESC Heart Fail. 2021 Sep 12. doi: 10.1002/ehf2.13614. Epub ahead of print. PMID: 34514715.
Liver cancer (n=1)
Myssayev A, Myssayev A, Ideguchi R, Kudo T. Association of FDG PET/CT-derived parameters with tumor markers and survival rate in Hepatocellular carcinoma. Acta Medica Nagasakiensia, 64(3), 81-90 - July 2021. doi: 10.11343/amn.64.81.
Wang M, Jiang H, Shi T, Yao YD. HD-RDS-UNet: Leveraging Spatial-Temporal Correlation between the Decoder Feature Maps for Lymphoma Segmentation," in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2021.3102612.
Pancreatic cancer (n=1)
Myssayev A, Myssayev A, Ideguchi R, Eguchi S, Adachi T, Sumida Y, Tobinaga S, Uetani M, Kudo T. Usefulness of FDG PET/CT derived parameters in prediction of histopathological finding during the surgery in patients with pancreatic adenocarcinoma. PLoS One. 2019 Jan 10;14(1):e0210178. doi: 10.1371/journal.pone.0210178. PMID: 30629646; PMCID: PMC6328180.
Colorectal cancer (n=2)
Demir Y, Sürücü E, Şengöz T, Koç M, Kaya GÇ. Liver metabolic activity changes over time with neoadjuvant therapy in locally advanced rectal cancer. Nucl Med Commun. 2016 Feb;37(2):116-21. doi: 10.1097/MNM.0000000000000412. PMID: 26440564.
Kido H, Kato S, Funahashi K, Shibuya K, Sasaki Y, Urita Y, Hori M, Mizumura S. The metabolic parameters based on volume in PET/CT are associated with clinicopathological N stage of colorectal cancer and can predict prognosis. EJNMMI Res. 2021 Sep 6;11(1):87. doi: 10.1186/s13550-021-00831-5. PMID: 34487264.
Endometrial cancer (n=1)
Sudo S, Hattori N, Manabe O, Kato F, Mimura R, Magota K, Sugimori H, Hirata K, Sakuragi N, Tamaki N. FDG PET/CT diagnostic criteria may need adjustment based on MRI to estimate the presurgical risk of extrapelvic infiltration in patients with uterine endometrial cancer. Eur J Nucl Med Mol Imaging. 2015 Apr;42(5):676-84. doi: 10.1007/s00259-014-2964-7. Epub 2014 Dec 13. PMID: 25504022.
Prostate cancer (n=5)
Zou Q, Jiao J, Zou MH, Li MZ, Yang T, Xu L, Zhang Y. Semi-automatic evaluation of baseline whole-body tumor burden as an imaging biomarker of 68Ga-PSMA-11 PET/CT in newly diagnosed prostate cancer. Abdom Radiol (NY). 2020 Dec;45(12):4202-4213. doi: 10.1007/s00261-020-02745-7. Epub 2020 Sep 18. PMID: 32948911.
Rosar F, Dewes S, Ries M, Schaefer A, Khreish F, Maus S, Bohnenberger H, Linxweiler J, Bartholomä M, Ohlmann C, Ezziddin S. New insights in the paradigm of upregulation of tumoral PSMA expression by androgen receptor blockade: Enzalutamide induces PSMA upregulation in castration-resistant prostate cancer even in patients having previously progressed on enzalutamide. Eur J Nucl Med Mol Imaging. 2020 Mar;47(3):687-694. doi: 10.1007/s00259-019-04674-0. Epub 2020 Jan 3. PMID: 31901103.
Gafita A, Calais J, Franz C, Rauscher I, Wang H, Roberstson A, Czernin J, Weber WA, Eiber M. Evaluation of SUV normalized by lean body mass (SUL) in 68Ga-PSMA11 PET/CT: a bi-centric analysis. EJNMMI Res. 2019 Dec 2;9(1):103. doi: 10.1186/s13550-019-0572-z. PMID: 31792771; PMCID: PMC6889088.
Gafita A, Bieth M, Krönke M, Tetteh G, Navarro F, Wang H, Günther E, Menze B, Weber WA, Eiber M. qPSMA: Semiautomatic Software for Whole-Body Tumor Burden Assessment in Prostate Cancer Using 68Ga-PSMA11 PET/CT. J Nucl Med. 2019 Sep;60(9):1277-1283. doi: 10.2967/jnumed.118.224055. Epub 2019 Mar 8. PMID: 30850484; PMCID: PMC6735278.
Brito AET, Mourato FA, de Oliveira RPM, Leal ALG, Filho PJA, de Filho JLL. Evaluation of whole-body tumor burden with 68Ga-PSMA PET/CT in the biochemical recurrence of prostate cancer. Ann Nucl Med. 2019 May;33(5):344-350. doi: 10.1007/s12149-019-01342-z. Epub 2019 Feb 11. PMID: 30746599.
Lymphoma (n=7)
Kurtz DM, Green MR, Bratman SV, Scherer F, Liu CL, Kunder CA, Takahashi K, Glover C, Keane C, Kihira S, Visser B, Callahan J, Kong KA, Faham M, Corbelli KS, Miklos D, Advani RH, Levy R, Hicks RJ, Hertzberg M, Ohgami RS, Gandhi MK, Diehn M, Alizadeh AA. Noninvasive monitoring of diffuse large B-cell lymphoma by immunoglobulin high-throughput sequencing. Blood. 2015 Jun 11;125(24):3679-87. doi: 10.1182/blood-2015-03-635169. Epub 2015 Apr 17. PMID: 25887775; PMCID: PMC4463733.
218 papers cited this paper, as of October 31, 2022.
Scherer F, Kurtz DM, Newman AM, Stehr H, Craig AF, Esfahani MS, Lovejoy AF, Chabon JJ, Klass DM, Liu CL, Zhou L, Glover C, Visser BC, Poultsides GA, Advani RH, Maeda LS, Gupta NK, Levy R, Ohgami RS, Kunder CA, Diehn M, Alizadeh AA. Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA. Sci Transl Med. 2016 Nov 9;8(364):364ra155. doi: 10.1126/scitranslmed.aai8545. PMID: 27831904; PMCID: PMC5490494.
283 papers cited this paper, as of October 31, 2022.
Senjo H, Kanaya M, Izumiyama K, Minauchi K, Hirata K, Mori A, Saito M, Tanaka M, Iijima H, Tsukamoto E, Itoh K, Ota S, Morioka M, Hashimoto D, Teshima T; North Japan Hematology Study Group (NJHSG). Serum level of soluble interleukin-2 receptor is positively correlated with metabolic tumor volume on 18 F-FDG PET/CT in newly diagnosed patients with diffuse large B-cell lymphoma. Cancer Med. 2019 Mar;8(3):953-962. doi: 10.1002/cam4.1973. Epub 2019 Feb 20. PMID: 30790452; PMCID: PMC6434200.
Senjo H, Hirata K, Izumiyama K, Minauchi K, Tsukamoto E, Itoh K, Kanaya M, Mori A, Ota S, Hashimoto D, Teshima T; North Japan Hematology Study Group. High metabolic heterogeneity on baseline 18FDG-PET/CT scan as a poor prognostic factor for newly diagnosed diffuse large B-cell lymphoma. Blood Adv. 2020 May 26;4(10):2286-2296. doi: 10.1182/bloodadvances.2020001816. PMID: 32453838; PMCID: PMC7252551.
Kitadate A, Narita K, Fukumoto K, Terao T, Tsushima T, Kobayashi H, Abe Y, Miura D, Takeuchi M, Machida Y, Matsue K. Baseline total lesion glycolysis combined with interim positron emission tomography-computed tomography is a robust predictor of outcome in patients with peripheral T-cell lymphoma. Cancer Med. 2020 Aug;9(15):5509-5518. doi: 10.1002/cam4.3226. Epub 2020 Jun 18. PMID: 32558387; PMCID: PMC7402824.
Terao T, Machida Y, Tsushima T, Miura D, Narita K, Kitadate A, Takeuchi M, Matsue K. Pre-treatment metabolic tumour volume and total lesion glycolysis are superior to conventional positron-emission tomography/computed tomography variables for outcome prediction in patients with newly diagnosed multiple myeloma in clinical practice. Br J Haematol. 2020 Oct;191(2):223-230. doi: 10.1111/bjh.16633. Epub 2020 Apr 6. PMID: 32253760.
Kameda T, Nakashima S, Mitamura K, Yamamoto Y, Norikane T, Shimada H, Wakiya R, Kato M, Miyagi T, Sugihara K, Mino R, Mizusaki M, Kadowaki N, Dobashi H. FDG-PET/CT imaging parameters for predicting spontaneous regression of methotrexate-associated lymphoproliferative disorder in patients with rheumatoid arthritis. Sci Rep. 2022 Sep 13;12(1):15367. doi: 10.1038/s41598-022-19727-y. PMID: 36100660; PMCID: PMC9470546.
Multiple myoloma (n=1)
Terao T, Machida Y, Narita K, Kuzume A, Tabata R, Tsushima T, Miura D, Takeuchi M, Tateishi U, Matsue K. Total diffusion volume in MRI vs. total lesion glycolysis in PET/CT for tumor volume evaluation of multiple myeloma. Eur Radiol. 2021 Jan 26. doi: 10.1007/s00330-021-07687-2. Epub ahead of print. PMID: 33496828.
Sarcoma (n=1)
Kitao T, Shiga T, Hirata K, Sekizawa M, Takei T, Yamashiro K, Tamaki N. Volume-based parameters on FDG PET may predict the proliferative potential of soft-tissue sarcomas. Ann Nucl Med. 2019 Jan;33(1):22-31. doi: 10.1007/s12149-018-1298-0. Epub 2018 Sep 8. PMID: 30196378.
Melanoma (n=1)
Dirks I, Keyaerts M, Neyns B, Vandemeulebroucke J. Computer-aided detection and segmentation of malignant melanoma lesions on whole-body 18F-FDG PET/CT using an interpretable deep learning approach. Comput Methods Programs Biomed. 2022 Jun;221:106902. doi: 10.1016/j.cmpb.2022.106902. Epub 2022 May 22. PMID: 35636357.
IgG4-related disease (n=1)
Mitamura K, Arai-Okuda H, Yamamoto Y, Norikane T, Takami Y, Fujimoto K, Wakiya R, Ozaki H, Dobashi H, Nishiyama Y. Disease activity and response to therapy monitored by [18F]FDG PET/CT using volume-based indices in IgG4-related disease. EJNMMI Res. 2020 Dec 9;10(1):153. doi: 10.1186/s13550-020-00743-w. PMID: 33296037; PMCID: PMC7726066.
Others (n=1)
Yoshimura T, Hasegawa A, Kogame S, Magota K, Kimura R, Watanabe S, Hirata K, Sugimori H. Medical Radiation Exposure Reduction in PET via Super-Resolution Deep Learning Model. Diagnostics (Basel). 2022 Mar 31;12(4):872. doi: 10.3390/diagnostics12040872. PMID: 35453920; PMCID: PMC9025130.
Hirata K, Tamaki N. Quantitative FDG PET Assessment for Oncology Therapy. Cancers (Basel). 2021 Feb 19;13(4):869. doi: 10.3390/cancers13040869. PMID: 33669531; PMCID: PMC7922629.
Santos, D.F., Takahashi, M.E., Camacho, M. et al. Whole-body tumor burden in PET/CT expert review. Clin Transl Imaging (2022). https://doi.org/10.1007/s40336-022-00517-5