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Phantom-Based Standardization Method for (123)I-metaiodobenzylguanidine Heart-to-Mediastinum Ratio Validated by D-SPECT Versus Anger Camera

Background: The (123)I-metaiodobenzylguanidine heart-to-mediastinum ratios (HMRs) have been standardized between D-SPECT and Anger cameras in a small patient cohort using a phantom-based conversion method. This study aimed to determine the validity of this method and compare the diagnostic performan...

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Detalles Bibliográficos
Autores principales: Yamashita, Shozo, Nakajima, Kenichi, Okuda, Koichi, Yamamoto, Haruki, Shibutani, Takayuki, Yoneyama, Tatsuya, Tsuji, Shiro, Yokoyama, Kunihiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Japanese Society of Nuclear Cardiology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10696155/
http://dx.doi.org/10.17996/anc.23-00003
Descripción
Sumario:Background: The (123)I-metaiodobenzylguanidine heart-to-mediastinum ratios (HMRs) have been standardized between D-SPECT and Anger cameras in a small patient cohort using a phantom-based conversion method. This study aimed to determine the validity of this method and compare the diagnostic performance of the two cameras in a larger patient cohort. Methods: We retrospectively calculated HMRs from early and late anterior-planar equivalent and planar images acquired from 173 patients in 177 studies using D-SPECT and Anger cameras, respectively. The D-SPECT HMRs were cross-calibrated to an Anger camera using conversion coefficients based on previous phantom findings, then standardized to medium-energy general-purpose collimator conditions. Relationships between HMRs before and after corrections were investigated. Late HMRs were classified into four cardiac mortality risk groups and divided into two groups using a threshold of 2.2 to verify diagnostic performance concordance. Results: Correction improved linear regression lines and differences in HMRs among the groups. The overall ratios of perfect concordance were (134 [75.7%] of 177), and higher in groups with very low (49 [80.3%] of 61) and high (51 [86.4%] of 59) HMRs when the standardized HMR was classified according to cardiac mortality risk. That between the systems was the highest (164 [92.7%] of 177) when the HMR was divided by a threshold value of 2.2. Conclusions: Phantom-based conversion can standardize HMRs between D-SPECT and Anger cameras because the standardized HMR provided comparable diagnostic performance. Our findings indicated that this conversion could be applied to multicenter studies that include both D-SPECT and Anger cameras.