Propagation-based phase-contrast breast computed tomography: a visual grading assessment of the performance of photon-counting and flat-panel X-ray detectors
Giannotti, N.; Tavakoli Taba, S.; Gureyev, T.; Lewis, S.; Brombal, L.; Longo, R.; Donato, S.; Tromba, G.; Arana Pena, L.; Hausermann, D.; Hall, C.; Maksimenko, A.; Arhatari, B.; Nesterets, Y.; Brennan, P.
Show abstract
Rationale and objectivesBreast cancer represents the leading cause of death from cancer in women worldwide. Early detection of breast tumours improves the prognosis and survival rate. Propagation-based phase-contrast computed tomography (PB-CT) is a technique that uses refraction and absorption of the X-ray to produce images for clinical applications. This study compared the performance of photon-counting and flat-panel X-ray detectors in PB-CT breast imaging using synchrotron radiation. Materials and methodsMastectomy specimens underwent PB-CT imaging using the Hamamatsu C10900D Flat Panel and PIXIRAD-8 CdTe single-photon-counting detectors. PB-CT images generated at different imaging conditions were compared to absorption-based CT (AB-CT) reference images acquired with the same detectors to investigate the image quality improvement delivered by PB-CT relative to AB-CT. The image quality of the different image sets was assessed by eleven readers in a visual grading characteristics (VGC) study. ResultsThe intraclass correlation coefficient showed a moderate/good interobserver agreement for the image set analysed (ICC = 0.626, p = <0.001). The area under the curve showed that the image quality improvement in PB-CT images obtained by the PIXIRAD-8 CdTe single-photon-counting detector were consistently higher than the one for flat-panel Hamamatsu detector. The level of improvement in image quality was more substantial at lower radiation doses. ConclusionIn this study, the PIXIRAD-8 photon-counting detector was associated with higher image quality scores at all tested radiation dose levels, which was likely a result of the combined effect of the absence of dark current noise and better spatial resolution, compared to the flat-panel detector.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm 95%
- Precise dose verification in proton therapy using Positron Emission Tomography. 95%
- Reproducible spectral CT thermometry with liver-mimicking phantoms for image-guided thermal ablation 94%
Similar papers in this journal
- Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality 94%
- Recent advances in the clinical applications of machine learning in proton therapy 93%
- Model uncertainty estimates for deep learning mammographic density prediction using ordinal and classification approaches 90%
Similar papers in this journal
- Non-Invasive monitoring of normal tissue radiation damage using quantitative ultrasound spectroscopy 94%
- Experimental investigation of oxygen diffusion in the peak and valley region of minibeam patterns during X-Ray irradiation 93%
- Cell lines of the same anatomic site and histologic type show large variability in intrinsic radiosensitivity and relative biological effectiveness to protons and carbon ions 92%
Similar papers in this journal
- Inclusion of a GaAs detector model in the Photon Counting Toolkit software for the study of breast imaging systems 94%
- National diagnostic reference levels for digital diagnostic and screening mammography in Uganda. 94%
- Internal calibration for opportunistic computed tomography muscle density analysis 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.