ABSTRACT
Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen-Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists' scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists' ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists' scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists' scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland-Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform's low inter-user variability and the high accuracy of its T1c and FLAIR AI models.
ABSTRACT
Two typos are corrected, and the linear refractive index n is removed from the expressions of the phase shift in Opt. Lett.46, 560 (2021)OPLEDP0146-959210.1364/OL.414895. The removal of n reduces the gate efficiency, but it does not affect the general findings. Here, we present the corrected equations and the corresponding new numerical results, showing that increasing the pulse energy from 1.8 nJ to 4 nJ leads to nearly the same results of Opt. Lett.46, 560 (2021)OPLEDP0146-959210.1364/OL.414895.
ABSTRACT
The ultrafast detection of single photons is currently restricted by the limited time resolution (a few picoseconds) of the available single-photon detectors. Optical gates offer a faster time resolution, but so far they have been applied mostly to ensembles of emitters. Here, we demonstrate through a semi-analytical model that the ultrafast time-resolved detection of single quantum emitters can be possible using an optical Kerr shutter at gigahertz rates under focused illumination. This technique provides sub-picosecond time resolution, while keeping a gate efficiency at around 85%. These findings lay the ground for future experimental investigations on the ultrafast dynamics of single quantum emitters, with implications for quantum nanophotonics and molecular physics.
