Abstract
BackgroundTo investigate if iodine density overlay maps (IDO) and virtual monoenergetic images at 40 keV (VMI40keV) acquired from spectral detector computed tomography (SDCT) can improve detection of incidental skeletal muscle metastases in whole-body CT staging examinations compared to conventional images.MethodsIn total, 40 consecutive cancer patients who underwent clinically-indicated, contrast-enhanced, oncologic staging SDCT were included at this retrospective study: 16 patients with n = 108 skeletal muscle metastases confirmed by prior or follow-up CT, 18F-FDG-PET, MRI or histopathology, and a control group of 24 patients without metastases. Four independent readers performed blinded, randomized visual detection of skeletal muscle metastases in conventional images, IDO and VMI40keV, indicating diagnostic certainty for each lesion on a 5-point Likert scale. Quantitatively, ROI-based measurements of attenuation (HU) in conventional images and VMI40keV and iodine concentration in IDO were conducted. CNR was calculated and receiver operating characteristics (ROC) analysis of quantitative parameters was performed.ResultsRegarding subjective assessment, IDO (63.2 (58.5–67.8) %) and VMI40keV (54.4 (49.6–59.2) %) showed an increased sensitivity for skeletal muscle metastases compared to conventional images (39.8 (35.2–44.6) %). Specificity was comparable in VMI40keV (69.8 (63.2–75.8) %) and conventional images (69.2 (60.6–76.9) %), while in IDO, it was moderately increased to 74.2 (65.3–78.4) %. Quantitative image analysis revealed that CNR of skeletal muscle metastases to circumjacent muscle was more than doubled in VMI40keV (25.8 ± 11.1) compared to conventional images (10.0 ± 5.3, p ≤ 0.001). Iodine concentration obtained from IDO and HU acquired from VMI40kev (AUC = 0.98 each) were superior to HU attenuation in conventional images (AUC = 0.94) regarding differentiation between healthy and metastatic muscular tissue (p ≤ 0.05).ConclusionsIDO and VMI40keV provided by SDCT improve diagnostic accuracy in the assessment of incidental skeletal muscle metastases compared to conventional CT.
Highlights
To investigate if iodine density overlay maps (IDO) and virtual monoenergetic images at 40 keV (VMI40keV) acquired from spectral detector computed tomography (SDCT) can improve detection of incidental skeletal muscle metastases in whole-body CT staging examinations compared to conventional images
Subjective analysis Subjective analysis revealed a higher sensitivity for skeletal muscle metastases (SMM) in IDO (63.2 (58.5–67.8) %) as well as in VMI40keV (54.4 (49.6–59.2) %) compared to conventional images (CI) (39.8 (35.2–44.6) %)
Overall specificity was marginally higher in IDO
Summary
To investigate if iodine density overlay maps (IDO) and virtual monoenergetic images at 40 keV (VMI40keV) acquired from spectral detector computed tomography (SDCT) can improve detection of incidental skeletal muscle metastases in whole-body CT staging examinations compared to conventional images. In DECT, one high- and one low-energy dataset is acquired from the polyenergetic x-ray spectrum This can be achieved through different technical approaches: tube-based DECT scanner work with 1) two sources at different tube voltage (dual-source), 2) two sequent rotations at different tube potentials (dual spin), 3) a technique, in which a beam filter is used to split up an x-ray emitted by a single source in two different-energetic partial beams (twin beam) or 4) rapid switching of tube potentials (kVp switching) [15]. Low noise is of special relevance for low keV virtual monoenergetic images (VMI) which have been shown to improve lesion detection of different metastatic conditions, such as pulmonary or hepatic metastasis but are impaired by an increase in image noise at source-based DECT [14, 17, 18] Another inherent gain of the detector-based approach is that post-processing takes place within the raw data domain while tube-based DECT either requires previous angular/temporal interpolation or only enables post-processing within the projection domain
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