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Characterization and Clinical Translation of a Novel Prototype Kilovoltage Dual-Layer Imager for Onboard Imaging.

PubMed
Authors: Harris TC, Jacobson M, Bruegger R, Birrer V, Ferguson D, Hu YH, Myronakis M, Lehmann M, Arroyo PC, Etemadpour R, Fueglistaller R, Berbeco RI

Year

2026

Paper ID

9661

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

325

Citations

1

Abstract

PURPOSE: Dual-energy imaging offers several benefits, including artifact reduction and material decomposition. This imaging may be achieved via multiple detecting layers with beam hardening between layers creating spectral separation. We describe the construction, characterization, and clinical translation of a novel prototype dual-layer flat-panel detector for kilovoltage (kV) onboard radiation therapy imaging. METHODS AND MATERIALS: The dual-layer imager (DLI) was designed with the first layer matching existing detector construction: cesium-iodide (CsI) scintillator and amorphous silicon thin-film transistor photodiode array. The second layer has a slightly thicker CsI scintillator, providing extra photon detection efficiency. The prototype DLI was built by an industry partner. For clinical deployment, top layer information was sent to the treatment console; data from both layers were sent to a research PC for retrospective analysis. Modulation transfer function (MTF(f)) and noise power spectrum were measured for the top, bottom, and combined layers. Detective quantum efficiency (DQE(f)) was calculated from the results. Leeds phantom imaging further assessed detector performance. Initial patient data were analyzed to determine material decomposition feasibility. Log-weighted subtraction and virtual monoenergetic images were generated. RESULTS: The DLI was deployed on a clinical TrueBeam linear accelerator (linac). For 120 kVp, the DQE(0) is 0.48 for the top layer, 0.13 for the bottom layer (using initial fluence), and 0.61 for the combined. Leeds contrast-to-noise ratio, with the top layer as the baseline, was -45.8% for the bottom layer and +12.4% for the combined. MTF50 went from 1.38 top layer to 0.96 combined. Initial log-weighted subtraction of layers of patients' lung kV's successfully suppressed bone material. Virtual monoenergetic images were generated: 40 keV increased soft tissue contrast by 1.6×, whereas 120 keV increased uniformity in metal artifact regions by 41.4%. CONCLUSIONS: A novel kV DLI was constructed and translated on a clinical linac. Combining the layers increases DQE with an MTF reduction. More importantly, it adds dual-energy imaging capabilities to a linac. Preliminary results show promise for spectral imaging applications, such as metal artifact reduction and bone removal to enable better lung tumor visualization.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • PURPOSE: Dual-energy imaging offers several benefits, including artifact reduction and material decomposition.

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