In:
BMC Medical Imaging, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2020-12)
Kurzfassung:
Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the efficacy of quantitative parameters measured by dual-energy spectral computed tomographic (CT) for this differentiation. Methods Twenty-eight patients were examined by dual-energy spectral CT. The effective and normalized atomic number (Z eff and Z eff-N, respectively); spectral Hounsfield unit curve (λ HU ) slope; and iodine and normalized iodine concentration (IC and IC N , respectively) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t -tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and accuracy were calculated using receiver operating characteristic (ROC) curves. Predictive probabilities were used to generate ROC curves to determine the diagnostic value. Results Examination of pre-contrast λ HU , Z eff , Z eff-N , IC, IC N , and venous phase IC N showed no significant differences in quantitative parameters ( P 〉 0.05). Venous phase λ HU , Z eff , Z eff-N , and IC in glioma recurrence were higher than in treatment-related changes ( P 〈 0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm 3 , achieving 66.7, 91.7, 83.3, and 91.7% sensitivity; 100.0, 77.8, 88.9, and 77.8% specificity; 100.0, 73.3, 83.3, and 73.3% PPV; 81.8, 93.3, 88.9, and 93.3% NPV; and 86.7, 83.3, 86.7, and 83.3% accuracy, respectively. The respective areas under the curve (AUCs) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes. Conclusions Glioma recurrence could be potentially differentiated from treatment-related changes based on quantitative values measured by dual-energy spectral CT imaging.
Materialart:
Online-Ressource
ISSN:
1471-2342
DOI:
10.1186/s12880-019-0406-5
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2020
ZDB Id:
2061975-3
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