Characterization of myocardial perfusion imaging systems - an extension of quality metrics.

Purpose: The aim of this study was to evaluate the performance of myocardial perfusion imaging (MPI) systems in detecting perfusion defects (PDs). The defect perfusion index (DPI) was introduced to extend and further advance the current MPI quality metrics.

Methods: An anthropomorphic phantom simulating normal and pathological myocardial perfusion conditions was imaged by various NaI-crystal detector systems with and without corrections for scatter (SC) and attenuation (AC) (Symbia, Symbia + SC, Symbia IQ + SCAC, Symbia IQ), and cadmium-zinc-telluride detector systems without corrections (DSPECT, D530c).

On dosimetric characteristics of detectors for relative dosimetry in small fields: a multicenter experimental study.

. In this multicentric collaborative study, we aimed to verify whether the selected radiation detectors satisfy the requirements of TRS-483 Code of Practice for relative small field dosimetry in megavoltage photon beams used in radiotherapy, by investigating four dosimetric characteristics. Furthermore, we intended to analyze and complement the recommendations given in TRS-483.

Determination of volume averaging correction factors using an elliptical absorbed dose model for Gamma Knife Perfexion.

Purpose: The purpose of this study is to calculate volume averaging correction factors for detectors used in the dosimetry of Gamma Knife's narrow photon beams, and to determine the impact of volume averaging on the field output correction factor.

Methods: Simulations of different Gamma Knife fields were done using elliptical dose model formalism with newly introduced fit functions. To determine volume averaging correction factors a calculation of the absorbed dose over the volume of the detector was performed.

Reduction of SPECT acquisition time using deep learning: A phantom study.

Single photon emission computed tomography (SPECT) procedures are characterized by long acquisition time to acquire diagnostically acceptable image data. The goal of this investigation was to assess the feasibility of using a deep convolutional neural network (DCNN) to reduce the acquisition time. The DCNN was implemented using the PyTorch and trained using image data from standard SPECT quality phantoms.

Dosimetric accuracy of three dose calculation algorithms for radiation therapy of in situ non-small cell lung carcinoma.

Background: Study determines differences in calculated dose distributions for non-small cell lung carcinoma (NSC LC) patients. NSC LC cases were investigated, being the most common lung cancer treated by radiotherapy in our clinical practice.

Materials And Methods: A retrospective study of 15 NSCLC patient dose distributions originally calculated using standard superposition (SS) and recalculated using collapsed cone (CC ) and Monte Carlo (MC) based algorithm expressed as dose to medium in medium (MCD) and dose to water in medium (MCD) was performed so that prescribed dose covers at least 99% of the gross target volume (GTV).