کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4225064 1609744 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Noise-optimized advanced image-based virtual monoenergetic imaging for improved visualization of lung cancer: Comparison with traditional virtual monoenergetic imaging
ترجمه فارسی عنوان
تصویربرداری یکنواخت انرژی مجازی مبتنی بر تصویر بهینه شده برای سر و صدا برای بهبود تصویربرداری از سرطان ریه: مقایسه با تصویربرداری مجازی مونوآرتریک مجازی
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی رادیولوژی و تصویربرداری
چکیده انگلیسی


• Image noise was significantly reduced at low keV-levels with the novel monoenergetic algorithm.
• Tumor contrast-to-noise ratio peaked in the 40/55 keV series reconstructed with the novel algorithm.
• Tumor signal-to-noise and contrast-to-noise ratios were higher with noise-optimized VMI+ compared to traditional VMI.
• Subjective image quality ratings were highest for the 55 keV series reconstructed with the novel algorithm.
• The novel algorithm for monoenergetic dual-energy CT may improve visualization of lung cancer.

PurposeTo assess the effect of a noise-optimized image-based virtual monoenergetic imaging (VMI+) algorithm in direct comparison with the traditional VMI technique and standard linearly-blended images emulating 120-kVp acquisition (M_0.3) on image quality at dual-energy CT in patients with lung cancer.Materials and MethodsDual-source dual-energy CT examinations of 48 patients with biopsy-proven primary (n = 31) or recurrent (n = 20) lung cancer were evaluated. Images were reconstructed as M_0.3, and VMI+ and traditional VMI series at 40, 55, and 70 keV. Attenuation of tumor, descending aorta, pulmonary trunk, latissimus muscle, and noise were measured. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Five-point scales were used by three observers to subjectively evaluate general image impression, tumor delineation, image sharpness, and image noise.ResultsBackground noise was consistently lower with VMI+ compared to VMI at all keV levels (all p < 0.0001) and M_0.3 (all p ≤ 0.0004). Tumor SNR and CNR peaked in the 40 keV VMI+ series, significantly higher compared to all VMI and M_0.3 series (all p < 0.0008). Observers preferred the 55 keV VMI+ series regarding general image impression and tumor delineation compared to all other series (all p < 0.0001). Image sharpness and image noise ratings were highest in the 55 keV VMI+ and 70 keV VMI and VMI+ reconstructions.ConclusionsTumor CNR peaked at 40 keV VMI+ while observers preferred 55 keV VMI+ series overall other series for dual-energy CT of lung cancer. The noise-optimized VMI+ technique showed significantly lower background noise and higher SNR and CNR compared to the traditional VMI technique at matching keV levels.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Radiology - Volume 85, Issue 3, March 2016, Pages 665–672
نویسندگان
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