Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy

被引：0

作者：

Song Xue

Andrei Gafita

Chao Dong

Yu Zhao

Giles Tetteh

Bjoern H. Menze

Sibylle Ziegler

Wolfgang Weber

Ali Afshar-Oromieh

Axel Rominger

Matthias Eiber

Kuangyu Shi

机构：

[1] Inselspital,Dept. Nuclear Medicine

[2] Bern University Hospital,Dept. Nuclear Medicine

[3] University of Bern,Dept. Molecular & Medical Pharmacology

[4] Technical University of Munich,Dept. Electrical Engineering

[5] University of California,Dept. Informatics

[6] Technical University of Munich,Dept. Nuclear Medicine

[7] Technical University of Munich,undefined

[8] University Hospital,undefined

[9] LMU Munich,undefined

来源：

European Journal of Nuclear Medicine and Molecular Imaging | 2022年 / 49卷

关键词：

Radioligand therapy; Lu-PSMA I&T; Dosimetry; Treatment planning; Machine learning;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

页码：4064 / 4072

页数：8

共 50 条

[1] Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy
Xue, Song
Gafita, Andrei
Dong, Chao
Zhao, Yu
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Ziegler, Sibylle
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EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 49 (12) : 4064 - 4072
[2] Machine learning to predict post-therapy dosimetry for 177Lu-PSMA I&T treatment
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[3] Patient dosimetry of 177Lu-PSMA I&T in metastatic prostate cancer treatment: the experience in Thailand
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[6] Voxel-wise Prediction of Post-therapy Dosimetry for 177Lu-PSMA I&T Therapyusing Deep Learning
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[7] Pretherapeutic Comparative Dosimetry of 177Lu-rhPSMA-7.3 and 177Lu-PSMA I&T in Patients with Metastatic Castration-Resistant Prostate Cancer
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[10] Comparative preclinical biodistribution, dosimetry and endoradiotherapy in mCRPC of 177Lu-rhPSMA-7.3 and 177Lu-PSMA I&T
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