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qPSMA: Semiautomatic Software for Whole-Body Tumor Burden Assessment in Prostate Cancer Using 68Ga-PSMA11 PET/CT.
Gafita, Andrei; Bieth, Marie; Krönke, Markus; Tetteh, Giles; Navarro, Fernando; Wang, Hui; Günther, Elisabeth; Menze, Bjoern; Weber, Wolfgang A; Eiber, Matthias.
Afiliación
  • Gafita A; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and andrei.gafita@tum.de.
  • Bieth M; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and.
  • Krönke M; Department of Informatics, Technical University Munich, Munich, Germany.
  • Tetteh G; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and.
  • Navarro F; Department of Informatics, Technical University Munich, Munich, Germany.
  • Wang H; Department of Informatics, Technical University Munich, Munich, Germany.
  • Günther E; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and.
  • Menze B; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and.
  • Weber WA; Department of Informatics, Technical University Munich, Munich, Germany.
  • Eiber M; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and.
J Nucl Med ; 60(9): 1277-1283, 2019 09.
Article en En | MEDLINE | ID: mdl-30850484
ABSTRACT
Our aim was to introduce and validate qPSMA, a semiautomatic software package for whole-body tumor burden assessment in prostate cancer patients using 68Ga-prostate-specific membrane antigen (PSMA) 11 PET/CT.

Methods:

qPSMA reads hybrid PET/CT images in DICOM format. Its pipeline was written using Python and C++ languages. A bone mask based on CT and a normal-uptake mask including organs with physiologic 68Ga-PSMA11 uptake are automatically computed. An SUV threshold of 3 and a liver-based threshold are used to segment bone and soft-tissue lesions, respectively. Manual corrections can be applied using different tools. Multiple output parameters are computed, that is, PSMA ligand-positive tumor volume (PSMA-TV), PSMA ligand-positive total lesion (PSMA-TL), PSMA SUVmean, and PSMA SUVmax Twenty 68Ga-PSMA11 PET/CT data sets were used to validate and evaluate the performance characteristics of qPSMA. Four analyses were performed validation of the semiautomatic algorithm for liver background activity determination, assessment of intra- and interobserver variability, validation of data from qPSMA by comparison with Syngo.via, and assessment of computational time and comparison of PSMA PET-derived parameters with serum prostate-specific antigen.

Results:

Automatic liver background calculation resulted in a mean relative difference of 0.74% (intraclass correlation coefficient [ICC], 0.996; 95%CI, 0.989;0.998) compared with METAVOL. Intra- and interobserver variability analyses showed high agreement (all ICCs > 0.990). Quantitative output parameters were compared for 68 lesions. Paired t testing showed no significant differences between the values obtained with the 2 software packages. The ICC estimates obtained for PSMA-TV, PSMA-TL, SUVmean, and SUVmax were 1.000 (95%CI, 1.000;1.000), 1.000 (95%CI, 1.000;1.000), 0.995 (95%CI, 0.992;0.997), and 0.999 (95%CI, 0.999;1.000), respectively. The first and second reads for intraobserver variability resulted in mean computational times of 13.63 min (range, 8.22-25.45 min) and 9.27 min (range, 8.10-12.15 min), respectively (P = 0.001). Highly significant correlations were found between serum prostate-specific antigen value and both PSMA-TV (r = 0.72, P < 0.001) and PSMA-TL (r = 0.66, P = 0.002).

Conclusion:

Semiautomatic analyses of whole-body tumor burden in 68Ga-PSMA11 PET/CT is feasible. qPSMA is a robust software package that can help physicians quantify tumor load in heavily metastasized prostate cancer patients.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Compuestos Organometálicos / Neoplasias de la Próstata / Procesamiento de Imagen Asistido por Computador / Glicoproteínas de Membrana / Carga Tumoral / Imagen de Cuerpo Entero / Tomografía Computarizada por Tomografía de Emisión de Positrones Tipo de estudio: Prognostic_studies Límite: Humans / Male Idioma: En Revista: J Nucl Med Año: 2019 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Compuestos Organometálicos / Neoplasias de la Próstata / Procesamiento de Imagen Asistido por Computador / Glicoproteínas de Membrana / Carga Tumoral / Imagen de Cuerpo Entero / Tomografía Computarizada por Tomografía de Emisión de Positrones Tipo de estudio: Prognostic_studies Límite: Humans / Male Idioma: En Revista: J Nucl Med Año: 2019 Tipo del documento: Article