ABSTRACT
La actividad extracardíaca (AEC) puede afectar la interpretación del SPECT de perfusión miocárdica (SPM); los softwares disponibles incluyen delimitación de bordes para resolver este problema. Objectivo. Evaluar la influencia de AEC en detección automática de bordes miocárdicos en condiciones normales y perfusión anormal y evaluar reproducibilidad del procesamiento semi-automático. Métodos. Se analizaron 100 SPM, 50 con AEC; cada sub-grupo incluyó 25 casos con alteraciones de perfusión. Los casos fueron procesados automáticamente y por 4 operadores independientes con diferente nivel de experiencia. Se empleó software QGS y QPS con enmascaramiento y reubicación del ventrículo izquierdo y se analizaron parámetros funcionales (volumen final diastólico y sistólico, fracción de eyección) y parámetros de perfusión como el score sumado de reversibilidad y la extensión del defecto de perfusión en reposo. Los datos se compararon con correlación de Pearson y test de student. Resultados. La correlación interobservador empeoró considerablemente con AEC y fue moderadamente afectada por alteraciones de perfusión. Los observadores más experimentados mostraron mejor correlación. La reproducibilidad fue mayor para los parámetros funcionales de perfusión, independiente de la experiencia del observador. Conclusiones. La AEC afecta de manera significativa la delimitación automática de bordes miocárdicos, influyendo en los valores de SPM. La reproducibilidad interobservador con procesamiento manual fue más afectada en parámetros funcionales que en scores de perfusión. Las alteraciones de perfusión no interfieren con la reproducibilidad del software, y cuando estaban presentes, se observó una mejor correlación. Si no existe AEC importante, la intervención manual en el procesamiento debe evitarse(AU)
Objective. Extracardiac activity (ECA) may affect interpretation of gated SPECT myocardial perfusion studies (MPSs). To solve this problem, available softwares include myocardial edge delimitation. Purpose. To evaluate the influence of ECA in automatic myocardial edge detection under normal conditions and with abnormal perfusion and also evaluate the reproducibility of semi-automatic processing. Methods. A total of 100 MPSs, 50 with ECA, were analyzed. Each subgroup included 25 cases with perfusion abnormalities. The cases were processed automatically and by 4 independent operators with different levels of experience. Commercial QGS and QPS softwares were used with tools to mask and relocate the left ventricle area. Functional parameters (final diastolic and systolic volumes and ejection fraction) and perfusion parameters such as the reversibility perfusion score and rest perfusion defect extension were analyzed. The data were compared with Pearson's correlation and Student's test. Results. Interobserver correlation significantly worsened with the presence of ECA and was moderately affected by perfusion abnormalities. More experienced observers presented better correlation. Reproducibility was greater for the functional perfusion parameters, independently of the observer's experience. Conclusions. ECA significantly affects automatic edging delimitation, affecting the MPS values. Interobserver reproducibility with manual processing was more altered regarding funtional parameters than in the perfusion scores. Perfusion abnormalities did not interfere with software reproducibility, and when present, better correlation was found. If ECA is not present, manual intervention should be avoided(AU)
Subject(s)
Humans , Female , Middle Aged , Perfusion/trends , Tomography, Emission-Computed, Single-Photon/instrumentation , Tomography, Emission-Computed, Single-Photon/methods , Stroke Volume , Tomography, Emission-Computed, Single-Photon/trends , Tomography, Emission-Computed, Single-PhotonABSTRACT
OBJECTIVE: Extracardiac activity (ECA) may affect interpretation of gated SPECT myocardial perfusion studies (MPSs). To solve this problem, available softwares include myocardial edge delimitation. PURPOSE: To evaluate the influence of ECA in automatic myocardial edge detection under normal conditions and with abnormal perfusion and also evaluate the reproducibility of semi-automatic processing. METHODS: A total of 100 MPSs, 50 with ECA, were analyzed. Each subgroup included 25 cases with perfusion abnormalities. The cases were processed automatically and by 4 independent operators with different levels of experience. Commercial QGS and QPS softwares were used with tools to mask and relocate the left ventricle area. Functional parameters (final diastolic and systolic volumes and ejection fraction) and perfusion parameters such as the reversibility perfusion score and rest perfusion defect extension were analyzed. The data were compared with Pearson's correlation and Student's test. RESULTS: Interobserver correlation significantly worsened with the presence of ECA and was moderately affected by perfusion abnormalities. More experienced observers presented better correlation. Reproducibility was greater for the functional perfusion parameters, independently of the observer's experience. CONCLUSIONS: ECA significantly affects automatic edging delimitation, affecting the MPS values. Interobserver reproducibility with manual processing was more altered regarding functional parameters than in the perfusion scores. Perfusion abnormalities did not interfere with software reproducibility, and when present, better correlation was found. If ECA is not present, manual intervention should be avoided.
