Angiogenesis plays a pivotal role in PTC aggressiveness and recurrence. CD31, an endothelial marker, provides a histological correlate of tumor vascularity. This study aimed to establish a multimodal imaging framework using Doppler ultrasound (US) and dual-energy CT (DECT) to capture CD31-associated vascular phenotypes for recurrence risk stratification. A total of 414 PTC patients (training set, 151; test set 1, 137; test set 2, 126) were included. Clinical and radiographic features, including demographics, tumor morphology, Doppler US grade, US grayscale values, and DECT parameters, were analyzed. CD31 expression was assessed by immunohistochemistry in the training set and served as a reference for vascular phenotyping. Logistic regression was applied to identify imaging-derived vascular signatures linked to CD31 expression. Recurrence-free survival (RFS) was analyzed across all datasets to evaluate prognostic value. High CD31 expression correlated with advanced tumor stage (p = 0.003), lymph node metastasis (p = 0.001), extrathyroidal extension (p < 0.001), and recurrence (p < 0.001). The vascular phenotype model integrating Doppler US grade, unenhanced electron density (ED), arterial-phase iodine concentration (IC), and venous-phase IC/ED ratio achieved an AUC of 0.815 (95

Purpose: To determine the optimal virtual monochromatic images (VMIs) from dual-layer spectral detector computed tomography for the visualization and diagnosis of metastatic lateral cervical lymph nodes (LNs) in patients with papillary thyroid carcinoma (PTC). Methods: Ninety-five lateral cervical LNs (49 metastatic and 46 non-metastatic) derived from 24 patients (16 females; mean age, 40.0 +/- 13.4 years) were included. 40-100 kiloelectron voltage (keV) VMIs, 120 keV VMI and conventional 120 kV peak (kVp) polyenergetic image (PI) were reconstructed. Five-point scale of subjective image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of LNs were assessed and compared among each VMI and 120 kVp PI. Receiver operating characteristic (ROC) curves and Delong tests were used to assess and compare the diagnostic efficacy of arterial enhancement fraction (AEF) based on each VMI and 120 kVp PI. Results: 40 keV VMI showed significantly higher SNR and CNR in both arterial and venous phases, and better image quality in arterial phase than 70-100 keV VMIs, 120 keV VMI, and 120 kVp PI (all p < 0.05). In all sets of images, AEF values of metastatic LNs were significantly higher than those of non-metastatic LNs (all p < 0.05). When using AEF value of 40 keV VMI to diagnose metastatic lateral cervical LNs, an area under ROC curve (AUC) of 0.878, sensitivity of 87.8 % and specificity of 80.4 % could be obtained, while the AUC of AEF value of 120 kVp PI was 0.815 (p = 0.154). Conclusion: 40 keV VMI might be optimal for displaying and diagnosing the metastatic lateral cervical LNs in patients with PTC.

Background To evaluate the effect of Hashimoto’s thyroiditis (HT) on dual-energy computed tomography (DECT) quantitative parameters of cervical lymph nodes (LNs) in patients with papillary thyroid cancer (PTC), and its effect on the diagnostic performance and threshold of DECT in preoperatively identifying metastatic cervical LNs. Methods A total of 479 LNs from 233 PTC patients were classified into four groups: HT+/LN+, HT+/LN−, HT−/LN + and HT−/LN − group. DECT quantitative parameters including iodine concentration (IC), normalized IC (NIC), effective atomic number (Z eff ), and slope of the spectral Hounsfield unit curve (λ HU ) in the arterial phase (AP) and venous phase were compared. Receiver operating characteristic curve analyses were performed to evaluate DECT parameters’ diagnostic performance in differentiating metastatic from nonmetastatic LNs in the HT − and HT + groups. Results The HT+/LN + group exhibited lower values of DECT parameters than the HT−/LN + group (all p < 0.05). Conversely, the HT+/LN − group exhibited higher values of DECT parameters than the HT−/LN − group (all p < 0.05). In the HT + group, if an AP-IC of 1.850 mg/mL was used as the threshold value, then the optimal diagnostic performance (area under the curve, 0.757; sensitivity, 69.4%; specificity, 71.0%) could be obtained. The optimal threshold value of AP-IC in the HT − group was 2.050 mg/mL. In contrast, in the HT − group, AP-NIC demonstrated the highest area under the curve of 0.988, when an optimal threshold of 0.243 was used. The optimal threshold value of AP-NIC was 0.188 in the HT + group. Conclusions HT affected DECT quantitative parameters of LNs and subsequent the diagnostic thresholds. When using DECT to diagnose metastatic LNs in patients with PTC, whether HT is coexistent should be clarified considering the different diagnostic thresholds.

Objective:To evaluate the feasibility of virtual non-contrast scan(VNC)images using dual-layer detector spec-tral CT instead of true non-contrast scan(TNC)images in patients with papillary thyroid carcinoma(PTC).Methods:The images of 86 patients with PTC were analyzed retrospectively.TNC images were obtained by conventional plain scan,while arterial and venous VNC(VNC-a and VNC-v)images were generated from the arterial and venous phases of enhanced CT images by a post-processing algorithm,respectively.Average attenuation value,image noise,and amount and length of calcification were measured.And the radiation dose was calculated.A 5-point scale was used to evaluate the subjective score of image quality.Results:The average VNC attenuation values of sternocleidomastoid muscle,cervical cancellous bone,normal thyroid gland,and thyroid nodule were significantly lower than TNC(P<0.05),and the average VNC attenuation values of neck fat were sig-nificantly higher than TNC(P<0.05).The signal-to-noise ratio(SNR)of cervical cancellous bone,normal thyroid gland,and thy-roid nodule in TNC image was significantly higher than that in VNC image(P<0.05).The contrast noise ratio(CNR)was signifi-cantly higher in TNC images than in VNC images(P<0.001).Compared with TNC images,VNC images showed no statistically significant difference in the amount of calcification detected(P>0.05),but significant difference in the length of calcification(P<0.05).The subjective scores of TNC images were higher than those of VNC image(P<0.001).Using VNC scan instead of TNC scan,the effective dose was reduced by 34.2%.Conclusion:Considering the different attenuation values,SNR,CNR,and cal-cification length,we conclude that although the radiation dose of subjects can be reduced,VNC images should not be used directly to replace TNC images of PTC patients.

To investigate the added value of quantitative parameters derived from dual-layer spectral detector computed tomography (SDCT) for diagnosing metastatic cervical lymph nodes (LNs) in patients with papillary thyroid cancer (PTC). A total of 219 cervical LNs (121 non-metastatic and 98 metastatic) were enrolled from 73 patients with PTC. Conventional CT image features including enlarged size, abnormal enhancement, calcification, cystic change and extranodal extension were evaluated. SDCT-derived quantitative parameters including normalized iodine concentration (NIC), effective atomic number (Zeff-c) and slope of energy spectrum curve (λHU) in both arterial phase and venous phase were measured and calculated. The χ2 or Fisher's precision probability test was used to compare qualitative CT image features. Mann–Whitney U test was used to compare quantitative parameters. Multivariate logistic regression analysis was applied to build three models based on conventional features (model 1), quantitative parameters (model 2) and their combination (model 3). ROC curves analysis was used to assess and compare the diagnostic performances. Metastatic LNs demonstrated significantly higher NIC, Zeff-c, and λHU in both arterial phase and venous phase than non-metastatic LNs (all P < 0.001). Model 1 = − 1.477 + 1.902 × abnormal enhancement + 2.414 × calcification. Model 2 = − 4.818 + 10.951 × arterial phase NIC + 0.836 × arterial phase λHU. Model 3 = − 4.991 + 0.562 × abnormal enhancement + 2.380 × calcification + 10.624 × arterial phase NIC + 0.779 × arterial phase λHU. Model 3 showed the best performance (AUC = 0.958), followed by model 2 (AUC = 0.954). Both these two models overperformed model 1 (AUC = 0.740) (both P < 0.001). Compared with conventional CT image features alone, adding quantitative parameters derived from SDCT could improve the performance in diagnosing metastatic cervical LNs in patients with PTC.

To explore the added value of arterial enhancement fraction (AEF) derived from dual-energy computed tomography CT (DECT) to conventional image features for diagnosing cervical lymph node (LN) metastasis in papillary thyroid cancer (PTC). A total of 273 cervical LNs (153 non-metastatic and 120 metastatic) were recruited from 92 patients with PTC. Qualitative image features of LNs were assessed. Both single-energy CT (SECT)–derived AEF (AEFS) and DECT-derived AEF (AEFD) were calculated. Correlation between AEFD and AEFS was determined using Pearson’s correlation coefficient. Multivariate logistic regression analysis with the forward variable selection method was used to build three models (conventional features, conventional features + AEFS, and conventional features + AEFD). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Abnormal enhancement, calcification, and cystic change were chosen to build model 1 and the model provided moderate diagnostic performance with an area under the ROC curve (AUC) of 0.675. Metastatic LNs demonstrated both significantly higher AEFD (1.14 vs 0.48; p < 0.001) and AEFS (1.08 vs 0.38; p < 0.001) than non-metastatic LNs. AEFD correlated well with AEFS (r = 0.802; p < 0.001), and exhibited comparable performance with AEFS (AUC, 0.867 vs 0.852; p = 0.628). Combining CT image features with AEFS (model 2) and AEFD (model 3) could significantly improve diagnostic performances (AUC, 0.865 vs 0.675; AUC, 0.883 vs 0.675; both p < 0.001). AEFD correlated well with AEFS, and exhibited comparable performance with AEFS. Integrating qualitative CT image features with both AEFS and AEFD could further improve the ability in diagnosing cervical LN metastasis in PTC. Arterial enhancement fraction (AEF) values, especially AEF derived from dual-energy computed tomography, can help to diagnose cervical lymph node metastasis in patients with papillary thyroid cancer, and complement conventional CT image features for improved clinical decision making. • Metastatic cervical lymph nodes (LNs) demonstrated significantly higher arterial enhancement fraction (AEF) derived from dual-energy computed tomography (DECT) and single-energy CT (SECT)–derived AEF (AEF S ) than non-metastatic LNs in patients with papillary thyroid cancer. • DECT-derived AEF (AEF D ) correlated significantly with AEF S , and exhibited comparable performance with AEF S . • Integrating qualitative CT images features with both AEF S and AEF D could further improve the differential ability.

Background Dual-energy computed tomography (DECT) can provide objective evaluation of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC). Purpose To investigate the relationship between quantitative parameters acquired from DECT and histopathological prognostic factors in LHSCC. Material and Methods A total of 65 patients with LHSCC who underwent arterial phase and venous phase DECT scans were retrospectively enrolled. Iodine concentration (IC) and normalized IC (NIC) of the tumor were calculated in both the arterial (IC A and NIC A ) and venous (IC V and NIC V ) phases, and compared among different pathological grades, T stages, and lymph node stages. Receiver operating characteristic (ROC) curves were generated to evaluate their diagnostic performance. Results There were significantly differences on IC A and NIC A among three pathological grades (IC A , P = 0.001; NIC A , P = 0.002). For differentiating moderately and poorly differentiated from well-differentiated LHSCC using IC A and NIC A , the areas under curve (AUCs) were 0.753 and 0.726, respectively. High T stage (T3/4) LHSCC showed significantly higher IC A ( P = 0.012) and NIC A ( P = 0.005) than low T stage (T1/2) LHSCC. The AUCs of the IC A and NIC A were 0.674 and 0.703, respectively, in discriminating high from low T stage LHSCC. Lymph node metastasis (LNM)-positive (N1/2/3) LHSCC showed significantly higher IC A ( P = 0.008) and NIC A ( P = 0.003) than LNM-negative (N0) LHSCC. For discriminating the LNM-positive from the LNM-negative group using IC A and NIC A , the AUCs were 0.697 and 0.744, respectively. Conclusion IC A and NIC A might be helpful in assessing histopathological prognostic factors in patients with LHSCC.

目的 探讨联合伪连续式动脉自旋标记(pCASL)及扩散加权成像(DWI)在腮腺肿瘤鉴别诊断中的价值.方法 回顾性分析行pCASL和DWI扫描的64例腮腺肿瘤患者.测量并比较腮腺多形性腺瘤、腺淋巴瘤和恶性肿瘤3组间肿瘤血流量(TBF)和表观扩散系数(ADC)的差异.采用受试者工作特征(ROC)曲线分析有差异的参数在腮腺肿瘤鉴别诊断中的效能.结果 腮腺多形性腺瘤ADC值显著高于腺淋巴瘤及恶性肿瘤(P＜0.001),而TBF值显著低于腺淋巴瘤(P＜0.001)及恶性肿瘤(P=0.013).联合TBF及ADC鉴别腺淋巴瘤和多形性腺瘤的曲线下面积(AUC)0.937,特异度100.0％,其效能优于单独利用TBF(AUC 0.921,特异度94.4％)及ADC(AUC 0.923,特异度94.4％).联合TBF及ADC鉴别恶性肿瘤和多形性腺瘤(AUC 0.978),诊断效能较单纯利用TBF(AUC 0.850)或ADC(AUC 0.969)升高.结论 基于pCASL及DWI所得的TBF和ADC有助于多形性腺瘤的检出,但是对腺淋巴瘤、恶性肿瘤的鉴别能力有限,需结合临床或其他影像资料进一步区分.

Purpose To study the influence of sex, age and thyroid function indices on dual-energy computed tomography (DECT)-derived quantitative parameters of thyroid in patients with or without Hashimoto’s thyroiditis (HT). Material and methods A total of 198 consecutive patients who underwent DECT scan of neck due to unilateral thyroid lesions were retrospectively enrolled. Iodine concentration (IC), total iodine content (TIC) and volume of normal thyroid lobe were calculated. Influences of sex, age and thyroid function indices on DECT-derived parameters in overall study population, subgroup patients with, and those without HT were assessed using Mann–Whitney U test, Student’s T-test, and Spearman correlation analyses, respectively, as appropriate. Results HT group showed significantly lower IC and TIC, while higher volume than No-HT group (all p < 0.001). The volume was larger in male than that in female in overall study population and No-HT group ( p = 0.047 and 0.010, respectively). There was no significant difference in any DECT-derived parameters between low (≤ 35 years) and high (> 35 years) age group in all three groups (all p > 0.05). TPOAb and TgAb correlated positively with IC and TIC, and negatively with volume in overall study population (all p < 0.05). TPOAb and TgAb also correlated positively with IC in HT group ( p = 0.002 and 0.007, respectively). Conclusion DECT-derived parameters of thyroid differed significantly between patients with and without HT. Sex and thyroid function indices could affect the DECT-derived parameters. Aforementioned physiological factors should be considered when analyzing the DECT-derived parameters of thyroid.

OBJECTIVES:To evaluate the performance of texture analysis (TA) of diffusion kurtosis imaging (DKI) in differentiating malignant from benign sinonasal lesions, and its added value to the conventional imaging features.METHODS:Fifty-eight patients with malignant and 40 patients with benign sinonasal lesions were retrospectively enrolled. Conventional CT and MRI features were reviewed. Texture parameters were obtained and compared between two groups. Multivariate logistic regression analysis was used to identify the most valuable variables. Receiver operating characteristic curves were performed to assess the differentiating performance of independent variables and their combination.RESULTS:There were significant differences in tumor necrosis, bone erosion and soft tissue invasion between the two groups (all p < 0.05). There were significant differences in the 10th and entropy of Apparent diffusion coefficient map, the mean, 10th and entropy of D map, the mean and 90th of K map between the two groups (all p < 0.002). The bone erosion, entropy of D, and mean of K were independent variables associated with malignant tumors. Receiver operating characteristic analyses indicated that the combination of three features possessed better differentiating performance than bone erosion alone (p = 0.003).CONCLUSION:TA of DKI could supply incremental value to conventional imaging features for pre-operative differential diagnosis between benign and malignant sinonasal lesions.ADVANCES IN KNOWLEDGE:The present study is the first to combine conventional imaging features and the TA of DKI in the differential diagnosis between benign and malignant sinonasal lesions. Our findings suggest that TA of DKI could supply incremental value to conventional imaging features.

Rationale and objectives: To develop and validate 2 iodine maps based radiomics nomograms for preoperatively predicting cervical lymph node metastasis (LNM) and central lymph node metastasis (CLNM) in papillary thyroid cancer (PTC). Materials and methods: A total of 346 patients with PTC were enrolled and allocated to training (242) and validation (104) sets. Radiomics features were extracted from arterial and venous phase iodine maps, respectively. Aggregated machine-learning strategy was applied for features selection and construction of 2 radiomics scores (LN rad-score; CLN rad-score). Logistic regression model was employed to establish two radiomics nomograms (nomogram 1: predicting LNM; nomogram 2: predicting CLNM) after incorporating LN or CLN rad-score with clinical predictors. Nomograms performance was determined by discrimination, calibration and clinical usefulness. Results: Nomogram 1 incorporated LN rad-score, age (categorized by 55) and CT reported LN status; Nomogram 2 incorporated CLN rad-score, capsule contact >25% and CT reported CLN status. 2 nomograms both showed good discrimination and calibration in the training (AUC = 0.847; AUC = 0.837) and validation cohorts (AUC = 0.807; AUC = 0.795). Significant improved AUC, net reclassification index (NRI) and integrated discriminatory improvement (IDI) confirmed additional great predictive value of 2 rad-scores, compared with clinical models without radiomics. Decision curve analysis indicated clinical utility of nomograms. 2 nomograms both demonstrated favorable predictive efficacy in CT reported LN or CLN negative subgroup (AUC = 0.766; AUC = 0.744). Conclusion: The presented 2 radiomics nomograms are useful tools for preoperative prediction of LNM and CLNM in PTC.

To evaluate the value of texture analysis (TA) of conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in the differential diagnosis between sinonasal non-Hodgkin’s lymphoma (NHL) and squamous cell carcinoma (SCC). Forty-two patients with sinonasal SCC and 30 patients with NHL were retrospectively enrolled. TAs were performed on T2-weighted image (T2WI), apparent diffusion coefficient (ADC) and contrast-enhanced T1-weighted image (T1WI). Texture parameters, including mean value, skewness, kurtosis, entropy and uniformity were obtained and compared between sinonasal SCC and NHL groups. Receiver-operating characteristic (ROC) curves and logistic regression analyses were used to evaluate the diagnostic value and identify the independent TA parameters. The mean value and entropy of ADC, and mean value of contrast-enhanced T1WI were significantly lower in the sinonasal NHL group than those in the SCC group (all P < 0.05). ROC analysis indicated that the entropy of ADC had the best diagnostic performance (AUC 0.832; Sensitivity 0.95; Specificity 0.67; Cutoff value 6.522). Logistic regression analysis showed that the entropy of ADC (P = 0.002, OR = 26.990) was the independent parameter for differentiating sinonasal NHL from SCC. TA parameters of conventional MRI and DWI, particularly the entropy value of ADC, might be useful in the differentiating diagnosis between sinonasal NHL and SCC.

ObjectivesThe current study evaluates the performance of dual-energy computed tomography (DECT) derived extracellular volume (ECV) fraction based on dual-layer spectral detector CT for diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid cancer (PTC) and compares it with the value of ECV derived from conventional single-energy CT (SECT).MethodsOne hundred and fifty-seven cervical LNs (81 non-metastatic and 76 metastatic) were recruited. Among them, 59 cervical LNs (27 non-metastatic and 32 metastatic) were affected by cervical root artifact on the contrast-enhanced CT images in the arterial phase. Both the SECT-derived ECV fraction (ECVS) and the DECT-derived ECV fraction (ECVD) were calculated. A Pearson correlation coefficient and a Bland–Altman analysis were performed to evaluate the correlations between ECVD and ECVS. Receiver operator characteristic curves analysis and the Delong method were performed to assess and compare the diagnostic performance.ResultsECVD correlated significantly with ECVS (r = 0.925; p <0.001) with a small bias (−0.6). Metastatic LNs showed significantly higher ECVD (42.41% vs 22.53%, p <0.001) and ECVS (39.18% vs 25.45%, p <0.001) than non-metastatic LNs. By setting an ECVD of 36.45% as the cut-off value, optimal diagnostic performance could be achieved (AUC = 0.813), which was comparable with that of ECVS (cut-off value = 34.99%; AUC = 0.793) (p = 0.265). For LNs affected by cervical root artifact, ECVD also showed favorable efficiency (AUC = 0.756), which was also comparable with that of ECVS (AUC = 0.716) (p = 0.244).ConclusionsECVD showed a significant correlation with ECVS. Compared with ECVS, ECVD showed comparable performance in diagnosing metastatic cervical LNs in PTC patients, even though the LNs were affected by cervical root artifacts on arterial phase CT.

Objective:To explore the diagnostic value of radiomics based on arterial-venous mixed images derived from dual-energy CT (DECT) data in diagnosis of cervical lymph nodes (LNs) metastasis of papillary thyroid cancer (PTC).Methods:From June 2017 to December 2018, eighty-four patients with preoperatively DECT scanning and pathologically confirmed PTC (129 non-metastatic LNs and 97 metastatic LNs) in the First Affiliated Hospital of Nanjing Medical University were included in this study. The clinical and imaging data of all patients were retrospectively analyzed. The training cohort consisted of 62 PTC cases with 156 LNs (91 non-metastatic LNs and 65 metastatic LNs). An independent validation cohort consisted of 22 PTC patients with 70 LNs (38 non-metastatic LNs and 32 metastatic LNs). Semi-automatic LNs segmentation was conducted on arterial-venous mixed images derived from DECT using Syngo.via Frontier Radiomics software. Totally 1 226 radiomics features were extracted from arterial-venous mixed images for each LN. The least absolute shrinkage and selection operator (LASSO) regression was applied for radiomics features selection and signature building. The logistic regression modeling was used to construct diagnostic models based on the CT image features of LNs (model 1), the radiomics signature (model 2) and the combination of the CT image features and radiomics signature (model 3). An intuitive nomogram was plotted for model 3. The ROC curve analyses and area under the curve (AUC) were performed to evaluate the diagnostic efficiency of the three models, with the performances compared using the Delong test.Results:Model 1 was developed with LNs shape, degree of enhancement, pattern of enhancement, calcification and extra nodal extension. Three arterial phase radiomics features were selected and used to establish radiomics signature using LASSO regression (model 2). Model 3 was developed with LNs size, shape, degree of enhancement and radiomics signature. In both the training and validation cohort, model 3 showed the best diagnostic performance (AUC=0.965, 0.933), followed by model 2 (AUC=0.947, 0.910), and both these two models significantly outperformed model 1 (AUC=0.850, 0.846) (training cohort, Z=4.066 and 3.758, P both<0.001; validation cohort, Z=2.871 and 1.998, P=0.017 and 0.042) respectively. Conclusion:The radiomics model based on arterial-venous mixed images derived from DECT data can realize effective diagnosis of LNs metastasis in patients with PTC; and the combination model of radiomics signature with CT image features can further improve the diagnostic accuracy.

Objective:To evaluate the diagnostic value of the combination of CT image features and quantitative dual-energy CT (DECT) parameters in diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid carcinoma (PTC).Methods:Preoperative DECT imaging data of 103 patients with pathologically proven PTC in the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2019 were retrospectively analyzed. Taking 2002 American Association of Head and Neck Surgery criteria for LNs division as a reference, cervical LNs were divided into 7 levels. A total of 245 LNs were enrolled using radiological-pathological subzone comparison method. According to pathological results, 107 LNs were classified as metastatic LNs group and 138 LNs were classified as non-metastatic LNs group. CT image features including size, shape, margin, degree of enhancement, pattern of enhancement, calcification, cystic change and extra nodal extension were assessed. Quantitative DECT parameters including standardized iodine concentration (NIC), standardized effective atomic number (Z eff-c) and slope of energy spectrum curve (λ HU) were calculated. The χ 2 test or Mann-Whitney U rank sum test were used to compare the difference of CT image features and quantitative parameters between the two groups. The multivariate logistic regression analysis was used to build models based on CT image features, quantitative DECT parameters and their combination. The ROC curve analyses were performed to evaluate the diagnostic efficiency. Results:Significant differences were found in all CT image features between metastatic and non-metastatic LNs groups ( P<0.05). All the arterial and venous phase DECT parameters in metastatic LNs group were higher than those in non-metastatic LNs group ( P<0.001). The area under curve (AUC), sensitivity, specificity of combination of logistic model based on both CT image features and quantitative DECT parameters were 0.922, 86.0% and 92.8% for diagnosing cervical LNs metastasis from PTC. The AUC value, sensitivity, specificity of logistic model based on quantitative DECT parameters were 0.912, 84.1% and 93.5%. Both of them outperformed logistic model based on CT image features with an AUC of 0.783, a sensitivity of 71.0% and a specificity of 73.9% ( Z=5.212, 4.554, P<0.001). Conclusions:Compared with CT image features, quantitative DECT parameters has better diagnostic performance in differentiating metastatic from non-metastatic LNs in patients with PTC. Integrating CT image features with quantitative dual-energy CT parameters together can furthermore improve the differentiating performance.

OBJECTIVE: To assess the feasibility of using virtual non-contrast (VNC) images derived from dual-energy computed tomography (DECT) to replace true non-contrast (TNC) images of papillary thyroid carcinoma (PTC) patients. METHODS: Images of 96 PTC patients were retrospectively analyzed. TNC images were acquired under the single-energy mode of DECT after the plain scanning. The arterial and venous phase VNC (VNC-a and VNC-v) images were generated by the post-processing algorithm from the arterial phase and venous phase of contrast-enhanced CT images, respectively. Mean attenuation values, image noise, number and length of calcification were measured. Radiation dose was also calculated. Last, subjective score of image quality was evaluated by a 5-point scale. RESULTS: Signal-to-noise ratio (SNR) of each tissue in TNC images is significantly higher than that of VNC images ( p<0.050). Contrast-to-noise ratio (CNR) of fat, muscle, thyroid nodules and internal carotid artery in TNC images is significantly higher than that of VNC images, while CNR in TNC images is lower for cervical vertebra ( p<0.001). Calcification is detected on TNC images of 44 patients, while it is omitted on VNC images of 14 patients (31.8%). The subjective score of TNC images is higher than VNC images ( p<0.001). The effective dose reduction is 47.6% by avoiding plain scanning. CONCLUSIONS: Considering the different attenuation value, SNR, CNR and especially reduced detection rate of calcification, we deem that VNC images cannot be directly used to replace TNC images in PTC patients, despite the reduced radiation dose.

Objective To evaluate the influence of post-label delay times (PLDs) on the performance of 3D pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging for characterizing parotid gland tumors and to explore the optimal PLDs for the differential diagnosis. Materials and method Fifty-eight consecutive patients with parotid gland tumors were enrolled, including 33 patients with pleomorphic adenomas (PAs), 16 patients with Warthin’s tumors (WTs), and 9 patients with malignant tumors (MTs). 3D pCASL was scanned for each patient five times, with PLDs of 1025 ms, 1525 ms, 2025 ms, 2525 ms, and 3025 ms. Tumor blood flow (TBF) was calculated, and compared among different PLDs and tumor groups. Performance of TBF at different PLDs was evaluated using receiver operating characteristic analysis. Results With an increasing PLD, TBF tended to gradually increase in PAs ( p < 0.001), while TBF tended to slightly increase and then gradually decrease in WTs ( p = 0.001), and PAs showed significantly lower TBF than WTs at all 5 PLDs ( p < 0.05). PAs showed significantly lower TBF than MTs at 4 PLDs ( p < 0.05), except at 3025 ms ( p = 0.062). WTs showed higher TBF than MTs at all 5 PLDs; however, differences did not reach significance ( p > 0.05). Setting a TBF of 64.350 mL/100g/min at a PLD of 1525 ms, or a TBF of 23.700 mL/100g/min at a PLD of 1025 ms as the cutoff values, optimal performance could be obtained for differentiating PAs from WTs (AUC = 0.905) or from MTs (AUC = 0.872). Conclusions Short PLDs (1025 ms or 1525 ms) are suggested to be used in 3D pCASL for characterizing parotid gland tumors in clinical practice. Key Points • With 5 different PLDs, 3D pCASL can reflect the variation of blood flow in parotid gland tumors. • 3D pCASL is useful for characterizing PAs from WTs or MTs. • Short PLDs (1025 ms or 1525 ms) are suggested to be used in 3D pCASL for characterizing parotid gland tumors in clinical practice.

目的 探讨MR纵向弛豫时间定量成像(T1mapping)技术对大鼠放射性唾液腺损伤后纤维化进程的评估价值.方法 21只Sprague-Dawley大鼠随机分为照射组(18只)和假照射组(3只).照射组大鼠颌下腺区行单次15 Gy的X线照射以造模,并于照射后1、2、4、8、12和24周行T1mapping扫描,每个时间点各3只.假照射组大鼠不予以X线照射,并于假照射后第1天行T1mapping扫描.完成MR扫描后,取颌下腺组织行马松三色染色,以研究腺体纤维化.采用单因素方差分析比较各组(假照射组、照射后1、2、4、8、12、24周组)间T1值和颌下腺纤维化程度的差异.采用Spearman相关性检验评估颌下腺T1值与纤维化程度的相关性.结果各组间大鼠颌下腺T1值(P＜0.001)及纤维化程度(P =0.017)差异均具有统计学意义.大鼠颌下腺T1值在照射后1周先显著减小(P=0.035),后于照射后2～24周呈上升趋势,并于24周时显著增大(P＜0.001).大鼠颌下腺纤维化程度在照射后呈整体上升趋势,并于24周时显著加重(P=0.025).颌下腺T1值与纤维化程度呈正相关(r=0.735,P＜0.001).结论T1 mapping技术可无创、定量评估大鼠放射性损伤后唾液腺纤维化程度.

Background Computed tomography texture analysis (CTTA) provides objective and quantitative information regarding tumor heterogeneity beyond visual inspection. However, no study has yet used CTTA to differentiate metastatic from non-metastatic cervical lymph node in patients with papillary thyroid cancer (PTC). Purpose To evaluate the value of texture analysis of dual-phase contrast-enhanced CT images in diagnosing cervical lymph node metastasis in patients with PTC. Material and Methods Metastatic (n = 27) and non-metastatic (n = 32) cervical lymph nodes were analyzed retrospectively. Texture analyses were performed on both arterial (A) and venous (V) phase CT images. Texture parameters, including mean gray-level intensity, skewness, kurtosis, entropy, and uniformity, were obtained and compared between groups. Receiver operating characteristic (ROC) curves analyses and multivariate logistic regression analysis were used in our study. Results Metastatic lymph nodes showed significantly higher A-mean gray-level intensity, A-entropy, and lower A-kurtosis and V-kurtosis (allP < 0.001) than non-metastatic mimics. The ROC curve analyses indicated that A-kurtosis demonstrated an optimal diagnostic area under the curve (AUC; 0.884) and specificity (92.59%), while the A-mean gray-level intensity showed optimal diagnostic sensitivity (90.62%). Multivariate logistic regression analysis showed that A-mean gray-level intensity (P = 0.006, odds ratio [OR] = 24.297) and V-kurtosis (P = 0.014, OR = 19.651) were the independent predictor for metastatic cervical lymph node. Conclusion Dual-phase contrast-enhanced CCTA-especially A-mean gray-level intensity and V-kurtosis-may have the potential to diagnose metastatic cervical lymph node in patients with PTC.

Background Several magnetic resonance imaging (MRI) sequences have been applied to assess injured glands but without histological validation. Purpose To evaluate longitudinal changes in multiparametric MRI (mp-MRI) of irradiated salivary glands in a rat model and investigate correlations between mp-MRI and histological findings. Study Type Prospective. Animal Model Submandibular glands of 36 rats were radiated using a single dose of 15 Gy X-ray (irradiation [IR] group), and 6 other rats were enrolled into sham-IR group. mp-MRI were scanned 1 day after sham-IR (n = 6), or 1, 2, 4, 8, 12, 24 weeks after IR (n = 36, 6 per subgroup). Field Strength/Sequence A 3.0-T/Diffusion-weighted imaging (DWI), readout-segmented echo-planar imaging (EPI) sequence; intravoxel incoherent motion DWI, single-shot EPI sequence; T1 mapping, dual-flip-angle gradient-echo sequence with volumetric interpolated breath-hold examination; T2 mapping, turbo spin-echo sequence. Assessment Parameters including apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), T1 and T2 value were obtained. Histological examinations, including hematoxylin and eosin staining (for acinar cell fraction [AC%] detection), Masson's trichrome staining (for degree of fibrosis [F%] determination) and CD34-immunohistochemical staining (for microvessel density [MVD] calculation), were performed at corresponding time points. Statistical Tests One-way analysis of variance was used to compare the mp-MRI and histological parameters among different groups. Spearman correlation analysis was applied to determine the correlation between mp-MRI and histological parameters. Two-sided P <= 0.05 was considered statistically significant. Results Changes of mp-MRI parameters (ADC, D, D*, f, T1, T2) and histological results (AC%, F%, MVD) among the seven groups were all significant. ADC, D, and T2 values negatively correlated with AC% (ADC, r = -0.728; D, r = -0.773; T2, r = -0.600), f positively correlated with MVD (r = 0.496), and T1 values positively correlated with F% (r = 0.714). Data Conclusion mp-MRI might be able to noninvasively and quantitatively evaluate the dynamic pathological changes within the irradiated salivary glands. Evidence Level 1 Technical Efficacy Stage 2