qPSMA: Semiautomatic Software for Whole-Body Tumor Burden Assessment in Prostate Cancer Using Ga-PSMA11 PET/CT.

Our aim was to introduce and validate qPSMA, a semiautomatic software package for whole-body tumor burden assessment in prostate cancer patients using Ga-prostate-specific membrane antigen (PSMA) 11 PET/CT. qPSMA reads hybrid PET/CT images in DICOM format. Its pipeline was written using Python and C++ languages.

Segmentation of Skeleton and Organs in Whole-Body CT Images via Iterative Trilateration.

Whole body oncological screening using CT images requires a good anatomical localisation of organs and the skeleton. While a number of algorithms for multi-organ localisation have been presented, developing algorithms for a dense anatomical annotation of the whole skeleton, however, has not been addressed until now. Only methods for specialised applications, e.

Exploring New Multimodal Quantitative Imaging Indices for the Assessment of Osseous Tumor Burden in Prostate Cancer Using Ga-PSMA PET/CT.

PET combined with CT and prostate-specific membrane antigen (PSMA) ligands has gained significant interest for staging prostate cancer (PC). In this study, we propose 2 multimodal quantitative indices as imaging biomarkers for the assessment of osseous tumor burden using Ga-PSMA PET/CT and present preliminary clinical data. We defined 2 bone PET indices (BPIs) that incorporate anatomic information from CT and functional information from Ga-PSMA PET: BPI is the percentage of bone volume affected by tumor and BPI additionally considers the level of PSMA expression.

Atlas construction for dynamic (4D) PET using diffeomorphic transformations.

A novel dynamic (4D) PET to PET image registration procedure is proposed and applied to multiple PET scans acquired with the high resolution research tomograph (HRRT), the highest resolution human brain PET scanner available in the world. By extending the recent diffeomorphic log-demons (DLD) method and applying it to multiple dynamic [11C]raclopride scans from the HRRT, an important step towards construction of a PET atlas of unprecedented quality for [11C]raclopride imaging of the human brain has been achieved. Accounting for the temporal dimension in PET data improves registration accuracy when compared to registration of 3D to 3D time-averaged PET images.