Spectral CT imaging in the differential diagnosis of necrotic hepatocellular carcinoma and hepatic abscess

Yu, Yanxia; Guo, Linxin; Hu, Caihong; Chen, K.

doi:10.1016/j.crad.2014.08.018

Cited by 19 publications

(10 citation statements)

References 14 publications

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“…[14] Our result showed that IC of GC was significantly higher than that of NGM both in AP and PVP. The increased IC value in GC would indicate the increased angiogenesis in the development of tumors, since the angiogenesis is the fundamental process and the growth formation would determine their enhancement in CT. [19] ROC analysis in this study indicated that IC had high sensitivity and specificity for discriminating GC from NGM.…”

Section: Discussionmentioning

confidence: 79%

“…Our results are consistent with many other clinical applications in that the quantitative nIC measurement was proven to be valuable, such as differentiating hepatic lesions, evaluating lymph nodes in rectal cancer and papillary thyroid cancer, and distinguishing between differentiated and undifferentiated GCs. [11,14,16,18,21] On the other hand, results indicated that the nIC ratio (including IC ratio) had no diagnostic value for discriminating GC from GI and NGM.…”

Section: Discussionmentioning

confidence: 95%

“…For medical diagnostic imaging with GSI scanning mode, water and iodine were often selected as the basis material pairs for material-decomposition image presentation because their atomic numbers span the range of atomic numbers for materials generally found in medical imaging and approximate those of soft tissue and iodinated contrast material to result in material-attenuation images that were intuitive to interpret. [11,14] For GC and GI in the mucosa and NGM, their IC values were derived from the iodine-based material decomposition images.…”

Section: Discussionmentioning

confidence: 99%

“…[4] In addition, there is increasing evidence that the inflammation seems to play a critical role in the development and progression of numerous cancers. [22,23] The main reaction of inflammation is the increased blood flow secondary to vasodilation and increased vascular permeability, which would lead to more IC in the gastric mucosa in enhanced CT. [14,19,22] Insko et al [24] summarized taking advantage of the gastric wall thickness was 1 cm or greater, focal, eccentric, and gastric wall enhanced almost would reach a 92% specificity for indicating malignant lesions, while with a low sensitivity. So taking these features into account, the diagnostic accuracy for GI has reached 98%.…”

Section: Discussionmentioning

confidence: 99%

“…The iodine concentration (IC) measurement in the iodine-based material decomposition image may be used to reflect the different contrast uptakes in gastric mucosa and GC, and the use of monochromatic X-ray beam in DESCT would eliminate the beam-hardening artifacts and average attenuation effects. [11,14,16,17] DESCT has demonstrated its value in gastric imaging to improve the N staging accuracy and to differentiate tumor histopathology type and lymph nodes. [16] …”

Section: Introductionmentioning

confidence: 99%

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Differentiating malignant from benign gastric mucosal lesions with quantitative analysis in dual energy spectral computed tomography

et al. 2017

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To investigate the value of quantitative analysis in dual energy spectral computed tomography (DESCT) for differentiating malignant gastric mucosal lesions from benign gastric mucosal lesions (including gastric inflammation [GI] and normal gastric mucosa [NGM]). This study was approved by the ethics committee, and all patients provided written informed consent. A total of 161 consecutive patients (63 with gastric cancer [GC], 48 with GI, and 50 with NGM) who underwent dual-phase contrast enhanced DESCT scans in the arterial phase (AP) and portal venous phase (PVP) were included in this study. Iodine concentration (IC) in lesions was derived from the iodine-based material-decomposition images and normalized to that in the aorta to obtain normalized IC (nIC). The ratios of IC and nIC between the AP and PVP were calculated. Diagnostic confidence for GC and GI was evaluated with reviewing the features including gastric wall thickness, focal, and eccentric on the conventional polychromatic images. All statistical analyses were performed by using statistical software SPSS 17.0 (SPSS, Chicago, IL). IC and nIC in GC differed significantly from those in GI and NGM, except for nICAP in comparing GC with GI. Mean nIC values of GC (0.18 ± 0.06 in AP and 0.62 ± 0.16 in PVP) were significantly higher than that of NGM (0.12 ± 0.03 in AP and 0.37 ± 0.08 in PVP) (all P < 0.05). There was also significant difference for IC values in GC, GI, and NGM (24.19 ± 8.27, 19.07 ± 5.82, and 13.61 ± 2.52 mg/mL, respectively, in AP and 28.00 ± 7.01, 24.66 ± 6.55, and 16.94 ± 3.06 mg/mL, respectively, in PVP). Based on Receiver Operating Characteristic Curve analysis, nIC and IC in PVP had high sensitivities of 88.89% and 90.48%, respectively, in differentiating GC from NGM, while the sensitivities were 71.43% and 88.89% during AP. Ratios IC and nIC ratios did not provide adequate diagnostic accuracy with their area under curves less than 0.65. With the conventional features, the diagnostic accuracies for GC and GI were 75.0% and 98.0%, respectively. Quantitative analysis of DESCT imaging parameters for gastric mucosa, such as nIC and IC, is useful for differentiating malignant from benign gastric mucosal lesions.

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Section: Discussionmentioning

confidence: 79%