RESUMEN
Objectives: Serous microcystic adenoma (SMA), a primary benign pancreatic tumor which can be clinically followed-up instead of undergoing surgery, are sometimes mis-distinguished as pancreatic neuroendocrine tumor (pNET) in regular preoperative imaging examinations. This study aimed to analyze preoperative contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) features of SMAs in comparison to pNETs. Material and methods: In this retrospective study, patients with imaging-diagnosed pancreatic lesions were screened between October 2020 to October 2022 (ethical approval No. B2020-309R). Performing by a Siemens Sequoia (Siemens Medical Solutions, Mountain View, CA, USA) equipped with a 5C-1 curved array transducer (3.0-4.5 MHz), CEUS examination was conducted to observe the microvascular perfusion patterns of pancreatic lesions in arterial phase, venous/late phases (VLP) using SonoVue® (Bracco Imaging Spa, Milan, Italy) as the contrast agent. Virtual touch tissue imaging and quantification (VTIQ) - SWE was used to measure the shear wave velocity (SWV, m/s) value to represent the quantitative stiffness of pancreatic lesions. Multivariate logistic regression was performed to analyze potential ultrasound and clinical features in discriminating SMAs and pNETs. Results: Finally, 30 SMA and 40 pNET patients were included. All pancreatic lesions were pathologically proven via biopsy or surgery. During the arterial phase of CEUS, most SMAs and pNETs showed iso- or hyperenhancement (29/30, 97 % and 31/40, 78 %), with a specific early honeycomb enhancement pattern appeared in 14/30 (47 %) SMA lesions. During the VLP, while most of the SMA lesions remained iso- or hyperenhancement (25/30, 83 %), nearly half of the pNET lesions revealed an attenuated hypoenhancement (17/40, 43 %). The proportion of hypoenhancement pattern during the VLP of CEUS differed significantly between SMAs and pNETs (P = 0.021). The measured SWV value of SMAs was significantly higher than pNETs (2.04 ± 0.70 m/s versus 1.42 ± 0.44 m/s, P = 0.002). Taking a SWV value > 1.83 m/s as a cutoff in differentiating SMAs and pNETs, the area under the receiver operating characteristic curve (AUROC) was 0.825, with sensitivity, specificity and likelihood ratio (+) of 85.71 %, 72.73 % and 3.143, respectively. Multivariate logistic regression revealed that SWV value (m/s) of the pancreatic lesion was an independent variable in discriminating SMA and pNET. Conclusion: By comprehensively evaluating CEUS patterns and SWE features, SMA and pNET may be well differentiated before the operation. While SMA typically presents as harder lesion in VTIQ-SWE, exhibiting a specific honeycomb hyperenhancement pattern during the arterial phase of CEUS, pNET is characterized by relative softness, occasionally displaying a wash-out pattern during the VLP of CEUS.
RESUMEN
PURPOSE: To develop a multi-parameter intrahepatic cholangiocarcinoma (ICC) scoring system and compare its diagnostic performance with contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system M (LR-M) criteria for differentiating ICC from hepatocellular carcinoma (HCC). METHODS: This retrospective study enrolled 62 high-risk patients with ICCs and 62 high-risk patients with matched HCCs between January 2022 and December 2022 from two institutions. The CEUS LR-M criteria was modified by adjusting the early wash-out onset (within 45 s) and the marked wash-out (within 3 min). Then, a multi-parameter ICC scoring system was established based on clinical features, B-mode ultrasound features, and modified LR-M criteria. RESULT: We found that elevated CA 19-9 (OR=12.647), lesion boundary (OR=11.601), peripheral rim-like arterial phase hyperenhancement (OR=23.654), early wash-out onset (OR=7.211), and marked wash-out (OR=19.605) were positive predictors of ICC, whereas elevated alpha-fetoprotein (OR=0.078) was a negative predictor. Based on these findings, an ICC scoring system was established. Compared with the modified LR-M and LR-M criteria, the ICC scoring system showed the highest area under the curve (0.911 vs. 0.831 and 0.750, both p<0.05) and specificity (0.935 vs. 0.774 and 0.565, both p<0.05). Moreover, the numbers of HCCs categorized as LR-M decreased from 27 (43.5%) to 14 (22.6%) and 4 (6.5%) using the modified LR-M criteria and ICC scoring system, respectively. CONCLUSION: The modified LR-M criteria-based multi-parameter ICC scoring system had the highest specificity for diagnosing ICC and reduced the number of HCC cases diagnosed as LR-M category.
Asunto(s)
Neoplasias de los Conductos Biliares , Carcinoma Hepatocelular , Colangiocarcinoma , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/diagnóstico por imagen , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/diagnóstico por imagen , Neoplasias Hepáticas/patología , Estudios Retrospectivos , Medios de Contraste , Diagnóstico Diferencial , Colangiocarcinoma/diagnóstico por imagen , Colangiocarcinoma/patología , Conductos Biliares Intrahepáticos/patología , Neoplasias de los Conductos Biliares/diagnóstico por imagen , Neoplasias de los Conductos Biliares/patología , Imagen por Resonancia Magnética/métodos , Sensibilidad y EspecificidadRESUMEN
OBJECTIVE: We aimed to investigate whether the radiomics analysis based on B-mode ultrasound (BMUS) images could predict histopathological tumor grades in pancreatic neuroendocrine tumors (pNETs). METHODS: A total of 64 patients with surgery and histopathologically confirmed pNETs were retrospectively included (34 male and 30 female, mean age 52.4 ± 12.2 years). Patients were divided into training cohort (n = 44) and validation cohort (n = 20). All pNETs were classified into Grade 1 (G1), Grade 2 (G2), and Grade 3 (G3) tumors based on the Ki-67 proliferation index and the mitotic activity according to WHO 2017 criteria. Maximum relevance minimum redundancy, least absolute shrinkage and selection operator were used for feature selection. Receiver operating characteristic curve analysis was used to evaluate the model performance. RESULTS: Finally, 18 G1 pNETs, 35 G2 pNETs, and 11 G3 pNETs patients were included. The radiomic score derived from BMUS images to predict G2/G3 from G1 displayed a good performance with an area under the receiver operating characteristic curve of 0.844 in the training cohort, and 0.833 in the testing cohort. The radiomic score achieved an accuracy of 81.8% in the training cohort and 80.0% in the testing cohort, a sensitivity of 0.750 and 0.786, a specificity of 0.833 and 0.833 in the training/testing cohorts. Clinical benefit of the score also exhibited superior usefulness of the radiomic score, as shown by the decision curve analysis. CONCLUSIONS: Radiomic data constructed from BMUS images have the potential for predicting histopathological tumor grades in patients with pNETs. ADVANCES IN KNOWLEDGE: The radiomic model constructed from BMUS images has the potential for predicting histopathological tumor grades and Ki-67 proliferation indexes in patients with pNETs.
Asunto(s)
Tumores Neuroectodérmicos Primitivos , Tumores Neuroendocrinos , Neoplasias Pancreáticas , Humanos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Tumores Neuroendocrinos/diagnóstico por imagen , Tumores Neuroendocrinos/patología , Estudios Retrospectivos , Antígeno Ki-67 , Clasificación del Tumor , Neoplasias Pancreáticas/diagnóstico por imagen , Neoplasias Pancreáticas/patologíaRESUMEN
PURPOSES: To evaluate the application of contrast enhanced ultrasound (CEUS) in preoperatively differential diagnosis between pancreatic solid pseudopapillary tumors (SPTs) and pancreatic neuroendocrine tumors (pNETs). PATIENTS AND METHODS: This retrospective study was approved by Institutional Review Board. Patients with surgical resection and histopathological diagnosis as SPTs and pNETs were included. All patients underwent B mode ultrasound (BMUS) and CEUS examinations within one week before surgical operation. On BMUS, the size, location, echogenicity, calcification, and margin of lesions were observed and recorded. On CEUS imaging, enhancement patterns, and enhancement degrees were recorded and analyzed. An independent t-test or Mann-Whitney U test was used for comparison between continuous variables. Chi-square test was used to compare the CEUS patterns. RESULTS: From February 2017 to Dec 2022, patients diagnosed as SPTs (nâ=â39) and pNETs (nâ=â48) were retrospectively included. On BMUS, anechoic cystic changes (19/39, 48.72%) and hyperechoic calcification (14/39, 35.90%) are more commonly detected in SPTs (Pâ=â0.000). On CEUS imaging, the majority of SPTs (27/39, 69.23%) showed hypo-enhancement in the arterial phase, while most of the pNETs (36/48, 75.00%) showed hyper- or iso-enhancement in the arterial phase (Pâ=â0.000). In the venous phase, most of the SPTs (32/39, 82.05%) showed hypo-enhancement, while over half of pNETs (29/48, 60.42%) showed hyper- or iso-enhancement compared to pancreatic parenchyma (Pâ=â0.001). CONCLUSIONS: CEUS is a valuable and non-invasive imaging method to make preoperatively differential diagnoses between SPTs and pNETs.
Asunto(s)
Tumores Neuroectodérmicos Primitivos , Tumores Neuroendocrinos , Neoplasias Pancreáticas , Humanos , Diagnóstico Diferencial , Estudios Retrospectivos , Tumores Neuroendocrinos/diagnóstico por imagen , Tumores Neuroendocrinos/patología , Medios de Contraste , Neoplasias Pancreáticas/cirugía , UltrasonografíaRESUMEN
Objective: To investigate whether the dynamic contrast-enhanced ultrasound (DCE-US) analysis and quantitative parameters could be helpful for predicting histopathologic grades of pancreatic neuroendocrine tumors (pNETs). Methods: This retrospective study conducted a comprehensive review of the CEUS database between March 2017 and November 2021 in Zhongshan Hospital, Fudan University. Ultrasound examinations were performed by an ACUSON Sequioa unit equipped with a 3.5 MHz 6C−1 convex array transducer, and an ACUSON OXANA2 unit equipped with a 3.5 MHz 5C−1 convex array transducer. SonoVue® (Bracco Inc., Milan, Italy) was used for all CEUS examinations. Time intensity curves (TICs) and quantitative parameters of DCE-US were created by Vuebox® software (Bracco, Italy). Inclusion criteria were: patients with histopathologically proved pNETs, patients who underwent pancreatic B-mode ultrasounds (BMUS) and CEUS scans one week before surgery or biopsy and had DCE-US imaging documented for more than 2 min, patients with solid or predominantly solid lesions and patients with definite diagnosis of histopathological grades of pNETs. Based on their prognosis, patients were categorized into two groups: pNETs G1/G2 group and pNETs G3/pNECs group. Results: A total of 42 patients who underwent surgery (n = 38) or biopsy (n = 4) and had histopathologically confirmed pNETs were included. According to the WHO 2019 criteria, all pNETs were classified into grade 1 (G1, n = 10), grade 2 (G2, n = 21), or grade 3 (G3)/pancreatic neuroendocrine carcinomas (pNECs) (n = 11), based on the Ki−67 proliferation index and the mitotic activity. The majority of the TICs (27/31) of pNETs G1/G2 were above or equal to those of pancreatic parenchyma in the arterial phase, but most (7/11) pNETs G3/pNECs had TICs below those of pancreatic parenchyma from arterial phase to late phase (p < 0.05). Among all the CEUS quantitative parameters of DCE-US, values of relative rise time (rPE), relative mean transit time (rmTT) and relative area under the curve (rAUC) were significantly higher in pNETs G1/G2 group than those in pNETs G3/pNECs group (p < 0.05). Taking an rPE below 1.09 as the optimal cut-off value, the sensitivity, specificity and accuracy for prediction of pNETs G3/pNECs from G1/G2 were 90.91% [58.70% to 99.80%], 67.64% [48.61% to 83.32%] and 85.78% [74.14% to 97.42%], respectively. Taking rAUC below 0.855 as the optimal cut-off value, the sensitivity, specificity and accuracy for prediction of pNETs G3/pNECs from G1/G2 were 90.91% [66.26% to 99.53%], 83.87% [67.37% to 92.91%] and 94.72% [88.30% to 100.00%], respectively. Conclusions: Dynamic contrast-enhanced ultrasound analysis might be helpful for predicting the pathological grades of pNETs. Among all quantitative parameters, rPE, rmTT and rAUC are potentially useful parameters for predicting G3/pNECs with aggressive behavior.
RESUMEN
OBJECTIVE: This study seeks to evaluate the value of the high-frame-rate vector flow imaging technique in assessing the hemodynamic changes of carotid atherosclerotic stenosis in aging people (>60 years old). METHODS: Aging patients diagnosed with carotid atherosclerotic stenosis who underwent carotid high-frame-rate vector flow imaging examination were prospectively enrolled. A Mindray Resona7s ultrasound machine equipped with high-frame-rate vector flow function was used for ultrasound evaluation. First, B mode ultrasound and color Doppler flow imaging were used to evaluate carotid stenosis. Then, the vector arrows and flow streamline detected by V Flow were analyzed and the wall shear stress values (Pa) at the carotid stenosis site were measured. All patients were divided into symptomatic and asymptomatic groups according to whether they had acute/subacute stroke or other clinical symptoms within 2 weeks before ultrasound examination. The results of digital subtraction angiography or computed tomography angiography were used as the gold standard. The stenosis rate was calcified, according to North American Symptomatic Carotid Endarterectomy Trial criteria. The diagnostic values of wall shear stress, conventional ultrasound, and the combined diagnosis in carotid atherosclerotic stenosis were compared. RESULTS: Finally, 88 patients with carotid atherosclerotic plaque were enrolled (71 males (80.7%), mean age 67.6 ± 5.4 years). The success rate of high-frame-rate vector flow imaging was 96.7% (88/91). The WSS value of symptomatic carotid stenosis (1.4 ± 0.15 Pa) was significantly higher than that of asymptomatic carotid stenosis (0.80 ± 0.08 Pa) (p < 0.05). Taking the wall shear stress value > 0.78 Pa as the diagnostic criteria for symptomatic carotid atherosclerotic plaque, the area under receiver operating characteristic curves was 0.79 with 87.1% sensitivity and 69.6% specificity. The area under receiver operating characteristic curves of the combined diagnosis (0.966) for differentiating severe carotid atherosclerotic stenosis was significantly higher than that of conventional ultrasound and WSS value, with 89.7% sensitivity and 93.2% specificity (p < 0.05). CONCLUSION: As a non-invasive imaging method, the high-frame-rate vector flow imaging technique showed potential value in the preoperative assessment of the symptomatic carotid atherosclerotic stenosis and diagnosing carotid atherosclerotic stenosis in aging patients.