Identification of superficial invasive and indolent lymphomatous lymph nodes by multiple Ultrasonographic vascular imaging

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Method A retrospectively study enrolled 82 lymphoma patients. According to proliferation rates and clinical course, the lymph nodes were classified as invasive and indolent lymphomatous lymph nodes. All patients underwent ultrasound (US) with three effective techniques: color Doppler flow imaging (CDFI), angio plus ultrasound imaging (AngioPLUS), and contrast-enhanced ultrasound (CEUS). Qualitative and quantitative parameters from the two groups were compared. Finally, the area under the receiver-operating characteristic (ROC) and regression analysis were used to compare the differences between the two groups and determine the diagnostic efficiency of the three techniques for differentiating invasive lymphoma from indolent lymphoma. Result The types of blood flow distribution between invasive and indolent lymphomatous lymph nodes were statistically different in all three Ultrasound techniques. In CDFI, invasive or indolent lymphomatous lymph nodes were determined by resistance index (RI) (p < 0.001). In CEUS, the differences between the two groups in necrosis and arrival time (ATM) (p = 0.026, 0.043) were statistically significant. Finally, CDFI combined with CEUS had the highest diagnostic sensitivity of 98.1%. Interobserver agreements for qualitative parameters were all excellent. Conclusion Ultrasonographic Vascular imaging is an aid in identifying invasive and indolent lymphomatous lymph nodes, and CDFI combined with CEUS had the highest diagnostic sensitivity, which can guide clinicians to make more accurate diagnosis and better treatment for patients. Biological sciences/Biological techniques Biological sciences/Cancer Health sciences/Oncology Color Doppler flow angio plus CEUS lymphoma aggressiveness Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Advances in knowledge Transformation of lymphoma exists in some patients and the results of this study may assist in identifying the presence of transformed lymphoma and guide clinical management. Selection of appropriate lymph nodes for puncture is a pressing clinical problem, and ultrasound can identify transformed lymph nodes and ultimately guide puncture biopsy. Introduction According to the fifth edition of the World Health Organization Classification of Lymphoid Neoplasms of the Haematological System, lymphomas can be divided into more than 100 subtypes[ 1 ]. Based on the proliferation rates and clinical course, they are broadly divided into invasive and indolent lymphomas[ 2 ]. Clinically, transformation may occur in various low-grade indolent non-Hodgkin's lymphomas (NHL), which is defined as the progression from a histologically indolent lymphoma to a more invasive lymphoma. In this stage of the disease, there are different types of lymphomas in the body (FL with DLBCL, etc.). This transformation is associated with disease progression and poor prognosis[ 3 ]. Obtaining specific tissues to produce pathological findings is currently the predominant method of diagnosing lymphoma. However, simply obtaining the most accessible lymph node may not establish the diagnosis as transformation usually only occurs in part of lymph nodes or extranodal sites[ 4 ]. Consequently, it is necessary to determine the clinical imaging presentation of invasive lymphoma to select biopsy sites and subsequent treatment. PET/CT has been proven helpful in identifying transformed lymph nodes with clinical signs[ 5 ]. However, its high cost and radiological damage are a deterrent for some patients. Besides, current studies have shown that the accuracy of PET/CT in identifying benign tumors and indolent lymphomas is not ideal[ 6 ]. So, the attention is focused on a non-invasive and easy-to-use diagnostic technique, which is ultrasonographic vascular imaging. Based on the pathophysiological background, angiogenesis has a vital role in lymphoma biology, and lymphoma subtypes differ significantly in terms of angiogenesis[ 7 – 10 ]. Menzel et al[ 11 ] found that the progression of invasive lymphoma is usually accompanied by a so-called "vascular phase," which represents extensive vascularization of the lymph nodes, with the exponential growth of the internal vessels and no intervals, while indolent lymphomas are well differentiated, with relatively normal blood flow. Hence, we focus on the advantages of ultrasonographic Vascular imaging for qualitative and quantitative assessment of lymph node blood flow. The techniques include color Doppler flow (CDFI), angio plus ultrasound imaging (AngioPLUS), and contrast-enhanced ultrasound (CEUS). It was proved that CDFI is helpful to the differential diagnosis of superficial enlarged lymph nodes and to reflect the aggressiveness of lymphoma[ 12 ]. AngioPLUS maximizes the velocity resolution of blood flow with a detailed resolution of up to 50 microns, which can detect the tiny vessels[ 13 ]. And CEUS combines real-time visualization of microvascular perfusion in nodules and time-intensity curve (TIC) analysis to provide an objective and quantitative way to analyze perfusion characteristics of lymph nodes [ 14 , 15 ]. Therefore, this study evaluated whether ultrasonographic vascular imaging could help differentiate superficial lymph nodes of different WHO lymphoma subtypes, thus providing guidance and recommendations for clinical biopsy. Materials and Method All the qualitative and quantitative indicators of ultrasonographic vascular imaging were assessed by two radiologists with more than five years of experience. Patients We conducted a retrospective analysis of 116 patients between September 2020 and November 2022, who underwent ultrasonographic vascular imaging for superficial enlarged lymph nodes. Superficial lymph nodes that showed high uptake in PET/CT were selected in our study. Then, 34 patients were further excluded based on the following exclusion criteria: selected lymph nodes without pathological confirmation(n = 12); age < 18 years(n = 0); fused lymphomas(n = 6); interval between US examination and histopathology more than 60 days(n = 0); pregnant or breast-feeding women(n = 0); patients underwent chemical or radiation therapy(n = 5); people who are allergic to contrast media (n = 3); patients with severe heart failure or cachexia(n = 8); those with more than one histologically confirmed subtype of NHL or coexistence of Hodgkin's disease and NHL(n = 0). Ultimately, 82 patients with 82 lesions were enrolled in the study. Pathological confirmation was performed for all patients based on the fifth edition of the WHO Classification of Lymphoid Neoplasms of the Haematological System. According to the proliferation rates and clinical course, lymph nodes are divided into indolent and invasive lymphomatous lymph nodes[ 2 ]. The study was approved by the Ethics Committee under ethics number 2022-SR-058. All methods were performed in accordance with the relevant guidelines and regulations. Two sonographers performed the three ultrasound examinations on the patients at the same time. CDFI CDFI was performed on the Aixplorer ultrasound system (SuperSonic Imagine,Aix-en-Provence, France) equipped with an SL15-4 linear transducer. The sampling frame was sized to completely encapsulate the mass. The color gain was adjusted to a level where low velocity vascular flow in the target lesion can be detected with minimal background noise. The velocity scale for color Doppler examination was 10 cm/s. Multi-sectional scanning was used to show the maximum vascular flow in the target lesion. If lymphatic hilar structures were present, they need to be adequately displayed. Patients took a supine position, breathed calmly, and fully exposed the area to be examined. The patterns of CDFI were categorized as the following four types[ 16 ]: (1) hilar; (2) peripheral; (3) mixed: the existence of both hilar and peripheral flow signal or scattered short rod-shaped blood flow signals; and (4) absent. The resistance index (RI) of blood flow should be measured at different sites[ 12 ]. Besides, the sampling volumes were all adjusted to the smallest size to avoid bias caused by different volumes sizes [ 14 ]. AngioPLUS AngioPLUS was also performed on the Aixplorer ultrasound system with SL15-4 linear transducer. The color gain and sampling frame were adjusted in line with that of the color Doppler, while the scale was set at 3cm/s. The same lymph nodes as described above were selected for AngioPLUS. Referring to the previous literature[ 13 , 17 ], we assessed the microvascular condition within the lymphoma in terms of AngioPLUS amount, distribution of vessels, and Four-tier vascularity score. The number of vessels in the lymphoma could be qualitatively defined as follows: (1). Absent; (2). Minimal: 1–2 vessels within the mass or at the edge of the mass; (3). Moderate: 3–4 vessels within the mass or at the edge of the mass; (4). Marked: 5 or more penetrating vessels in the mass; The distribution of blood vessels was defined as: (1). Absent; (2). Vessels in the rim; (3). Internal blood flow: punctate or perforating vessels exist in the mass; (4). Combined. For four-tier vascularity score, we referred to the scoring method designed by Min Ji Son et al[ 18 ]: (1). Score 1: no vessels; central or peripheral punctate vessels; (2). Score 2: 1 or 2 peripheral vessels that do not enter the nodes; (3). Score 3: 3 or more peripheral vessels, or 1–2 penetrating vessels; (4). Score 4: 3 or more penetrating vessels or disrupted internal blood flow. CEUS The LogiqE9 ultrasound machine (GE Medical Systems, Milwaukee, WI, USA) with a 9L linear transducer was used to perform the CEUS examination in MSK GEN mode. The mechanical index (MI) and thermal index (TI) was set at 0.14, 0.0 respectively. Then 5ml of 0.9% saline was added into the contrast medium (SonoVue, Bracco, Milan, Italian) and shaken forcefully to make emulsion-like microbubbles for preparation. The patient was positioned as above, and the same lymphoma section as above is selected for observation. Afterward, 2.4 ml of contrast medium was injected rapidly into the patient's elbow vein, followed by 5 ml of saline. The timer built into the machine started simultaneously and recorded the angiography process in real-time for approximately 60s. During this procedure, the probe was kept fixed. After the angiography, the dynamic video was saved, and the patient was closely observed for any discomfort. CEUS imaging analysis The characteristics of lymphomas in CEUS included enhancement mode, boundary, intensity, distribution, and necrosis [ 19 , 20 ]. (1) Enhancement intensity was divided into no enhancement, low enhancement (lower than surrounding normal tissue), moderate enhancement (equal to the surrounding normal tissue), high enhancement (higher than surrounding normal tissue, but lower than surrounding arteries), and intense enhancement (equal to the surrounding arteries). (2) Enhancement distribution was classified as hilar, central (enhanced from peripheral to the interior), centrifugal (enhanced from the center to peripheral), mixed (simultaneously enhanced at the margins and the center or diffuse enhancement), and peripheral. (3) Enhancement boundary was divided into clear and unclear. (4) Enhancement patterns: homogeneous and heterogeneous. Observe the process of lymphoma angiography and intercept the period from 1 second before the start of enhancement to 40 seconds of enhancement for TIC analysis, using GE LogiqE9 quantification software. The entire enhanced lymph node was selected as the region of interest (ROI). It was essential to avoid surrounding tissues and blood vessels when outlining the ROI. The parameters provided by TIC analysis had to be measured three times and averaged, including arrival time (ATM); time to peak (TP); △T = TTP-ATM; area under the gamma curve (Area); curve gradient (Grad); base intensity (BI); peak intensity (PI) [ 19 ]. Histologic Analysis Experienced hematopathologists reviewed all tissue specimens at our institution. The pathological diagnosis was confirmed for all patients based on the fifth edition of the World Health Organization Classification of Lymphoid Neoplasms of the Haematological System. Statistical Analysis SPSS software (version 21.0; IBM Corporation, NY, USA) was used for data analysis. The quantitative parameters were expressed as mean ± SD. Statistical analysis between the two groups was done using independent samples t-test for quantitative parameters and chi-square test for qualitative parameters. Regression analysis was used to diagnose image characteristics and quantitative parameters jointly. The diagnostic value of different ultrasound techniques was analyzed by the area under the receiver-operating characteristic (ROC) with the Medcalc 18.2.1.0 software. P < 0.05 was statistically significant. Observer consistency was assessed using intra-group correlation (ICC) and kappa for continuous and categorical variables. Consistency was considered poor when ICC/kappa was 0-0.4; 0.4–0.59, fair; 0.6–0.74, good; and 0.75-1, excellent[ 21 ]. Results ICC ICC and kappa values showed excellent inter-observer agreement (Table 1 ). Table 1 Consistency of the observers with regard to US features of lymphomas. Features ICC/Kappa Features ICC/Kappa Patterns of CDFI 0.883 AT 0.883 Amount of vessels 0.857 TP 0.882 Distribution of vessels 0.873 △T 0.814 Four-tier vascularity score 0.903 BI 0.903 Enhancement intensity 0.878 PI 0.912 Enhancement distribution 0.801 △I 0.857 Enhancement boundary 0.812 Grad 0.842 Necrosis 0.89 AUC 0.853 Enhancement pattern 0.855 RI 0.837 Clinical features Eighty-two patients (37 males and 45 females; average age, 60.3 years; range, 28–88 years) with 82 lymphomatous lymph nodes were enrolled in our research. Of the 82 lymphomatous lymph nodes, there were 54 cases of invasive lymphoma (45 cases of diffuse large B-cell lymphoma, DLBCL; 3 cases of anaplastic large cell lymphoma, ALCL; 6 cases of grade III follicular lymphoma) and 28 cases of indolent lymphoma (13 cases of I-II follicular lymphoma, FL; 11 cases of nodal marginal zone lymphoma, MZL; 2 cases of lymphoplasmacytic lymphoma, LPL; and 2 cases of B-Cell Lymphoproliferative Disease, BCLD). Besides, 54 enlarged lymph nodes were in the neck, 17 in the inguinal region, and 11 in the axillary. CDFI and AngioPLUS Characteristics of CDFI and AngioPLUS in invasive lymphoma and indolent lymph nodes are compared in Table 2 . There was a significant difference in the characteristics of internal vascular distribution between the two groups. In invasive lymphoma, it mainly presented as “mixed” blood flow (25/54, 46.3%) (Fig. 1 ) and an absence of blood flow (9/54, 16.7%), whereas half of the indolent lymphoma (50.0%) manifested as “hilar” type of blood flow (P = 0.002) (Fig. 2 ). Besides, “marginal” blood supply was only present in invasive lymphomas (10/54, 18.5%). The RI of invasive lymphoma (0.66 ± 0.09, range 0.51–0.84) was higher than that of indolent lymphomas (0.56 ± 0.07, range 0.41–0.69) (P < 0.001) (Fig. 3 ). The optimal cut-off value of RI was 0.625, with the sensitivity, specificity, accuracy and the area under the curve (AUC) of 67.4%, 84.6%, 81.3% and 0.813 respectively. Likewise, interms of AngioPLUS, the distribution of microvasculature of invasive lymphomas (11/54, 20.4%) was more likely to show marginal vessels than indolent lymphomas (1/28, 3.6%). However, there was no statistical significance regarding AngioPLUS amount and Four-tier vascularity score in the lymph nodes. Table 2 CDFI and AngioPLUS in 82 Invasive and Indolent lymphomas. Pathology type Characteristic Invasive lymphoma (n = 54) Indolent lymphoma (n = 28) P value RI Patterns of CDFI Absent hilar Mixed Peripheral 0.66 ± 0.09 9(16.7%) 10(18.5%) 25(46.3%) 10(18.5%) 0.56 ± 0.07 1(3.6%) 14(50.0%) 13(46.4%) 0(0.0%) < 0.001 0.002 Amount of vessels Absent Minimal Moderate Marked Distribution of vessels 2(3.7%) 10(18.5%) 12(22.2%) 30(55.6%) 0(0.0%) 1(3.6%) 7(25.0%) 20(71.4%) 0.185 Absent Internal vascularity Vessels in rim Combined Four-tier vascularity score 1 2 3 4 2(3.7%) 7(13.0%) 11(20.4%) 34(63.0%) 6(11.1%) 10(18.5%) 16(29.6%) 22(40.7%) 0(0.0%) 10(35.7%) 1(3.6%) 17(60.7%) 0(0.0%) 2(7.1%) 12(42.9%) 14(50.0%) 0.024 0.115 CEUS Quantitative results of CEUS are shown in Table 3 . For the optimization of the threshold values for ATM (15.058s), differences were observed between the two groups, with the AUC of 0.636, the sensitivity of 53.6%, and the specificity of 83.3%, respectively (P = 0.043). There were no statistical differences for the remaining parameters. Qualitative findings of CEUS are summarized in Table 4 . The results showed that the majority of invasive (43/54, 79.7%) and indolent (28/28, 100%) lymphomas displayed hyperenhancement, and no statistical difference was found between them (P = 0.141). Concerning enhancement distribution, invasive lymphomas (19/54, 35.2% vs. 4/28,14.3%) showed more of a centripetal enhancement distribution. Besides, “marginal” enhancement (P = 0.028) and necrosis (p = 0.026) (Fig. 4 ) were only seen in invasive lymphomas. Table 3 Qualitative results of CEUS. Invasive lymphoma Indolent lymphoma Parameter Range Mean ± Standard Deviation Range Mean ± Standard Deviation P value AT 3.55–21.62 11.90 ± 3.80 5.88–21.35 13.84 ± 4.50 0.043 TP 9.22–38.77 23.3 ± 16.25 14.81–36.81 24.21 ± 6.19 0.547 △T 5.67–23.83 11.44 ± 3.57 6.61–16.37 10.38 ± 2.67 0.171 BI -70.90to -54.43 -63.18 ± 3.46 -70.50to -57.5 -63.82 ± 3.38 0.426 PI -60.64to -34.31 -46.35 ± 5.52 -56.70to -32.57 -46.46 ± 6.09 0.937 △I 6.96–26.84 16.82 ± 3.92 8.60-30.33 17.36 ± 4.86 0.592 Grad 0.442–3.802 1.72 ± 0.65 0.57–3.85 1.78 ± 0.75 0.891 AUC 96.41-567.958 329.36 ± 103.29 117.37-795.52 328.23 ± 143.27 0.968 Table 4 Comparison of the invasive and indolent lymphoma qualitative parameters using CEUS Pathology type Characteristic Invasive lymphoma Indolent lymphoma P value Enhancement intensity none weak moderate high intense Enhancement pattern homogeneous 0(0.0%) 3(5.5%) 7(13.0%) 16(29.6%) 28(51.9%) 23(42.6%) 0(0.0%) 0(0.0%) 0(0.0%) 11(39.3%) 17(60.7%) 18(64.3%) 0.141 0.062 heterogeneous 31(57.4%) 10(35.7%) Enhancement distribution hilar central centrifugal mixed Peripheral Enhancement boundary clear 11(20.4%) 19(35.2%) 4(7.4%) 15(27.8%) 5(9.3%) 25(46.3%) 11(39.3%) 4(14.3%) 6(21.4%) 7(25.0%) 0(0.0%) 17(60.7%) 0.028 0.215 unclear Necrosis yes no 29(53.7%) 11(20.4%) 43(79.6%) 11(39.3%) 0(0.0%) 28(100%) 0.026 The combination of Ultrasound techniques The two groups' sensitivity, specificity, and accuracy of single and multiple combined imaging techniques were compared (Table 5 ). The results indicated that the combination of the three had the highest diagnostic efficacy (AUC = 0.941), with diagnostic sensitivity, specificity of 90.7%, 85.7%, respectively (Fig. 5 ). In contrast, CDFI combined with CEUS had the highest diagnostic sensitivity of 0.981. And there was no statistically significant difference in diagnostic efficacy between CDFI combined with CEUS and the combination of the three primary ultrasonographic Vascular imaging techniques (p = 0.261) ( Table 6 ) . Table 5 ROC analysis: invasive lymphoma vs. indolent lymphoma. Index AUROC value P -value CI 95% Sensitivity (%) Specificity (%) CDFI 0.808 < 0.001 0.714–0.902 0.667 0.857 AngioPLUS 0.676 0.009 0.556–0.796 0.870 0.357 CEUS 0.879 < 0.001 0.794–0.963 0.778 0.857 CDFI + CEUS 0.925 < 0.001 0.861–0.988 0.981 0.750 CDFI + AngioPLUS 0.808 < 0.001 0.714–0.902 0.667 0.857 AngioPLUS + CEUS 0.880 < 0.001 0.799–0.887 0.889 0.750 CDFI + CEUS + AngioPLUS 0.941 < 0.001 0.887–0.996 0.907 0.857 Table 6 A precise comparison of the diagnostic accuracy of different ultrasound techniques. CDFI vs AngioPLUS CDFI vs CEUS CDFI + CEUS vs CDFI + AngioPLUS CDFI + CEUS vs AngioPLUS + CEUS CDFI + CEUS vs CDFI + CEUS + AngioPLUS AngioPLUS + CDFI vs CDFI + CEUS + AngioPLUS Difference between areas 0.132 0.071 0.117 0.044 0.017 0.134 95%CI 0.034 to 0.230 -0.035 to 0.176 0.040 to 0.193 -0.006 to 0.09 -0.013 to 0.046 0.046 to 0.221 P value 0.009 0.189 0.003 0.086 0.261 0.003 Discussion There is growing evidence of a correlation between the type of vascular condition and the aggressiveness of lymphomas[ 7 , 22 , 23 ]. To identify signs of transformation and to identify potential biopsy sites, this retrospective study was designed to clarify invasive and indolent Lymphomatous lymph nodes through Ultrasonographic Vascular imaging, which finally impact the selection of treatment programmes. The three ultrasound techniques, including CDFI, AngiPLUS, and CEUS, are all capable of showing vascular distribution. The results indicated that indolent lymphomas presented more often with "hilar" and “centrifugal” blood flow types, while invasive lymphomas had a greater distribution of “mixed” and “central”. This is consistent with previous research findings[ 24 , 25 ]. Besides, “peripheral” blood flow type was only found in invasive lymphomas. In line with this, Giovagnorio et al[ 26 ] found that six lymphomas showing “peripheral” vessels pathologically were all confirmed as high-grade invasive lymphoma. In conclusion, there is a correlation between the type of vascular distribution and the tissue aggressiveness of the lymphoma. In terms of biological behavior, lymphoma center is initially infiltrated by tumor cells. But indolent lymphoma is slow to develop, so the surrounding area may remain untouched for a long time. As the inside-out invasion of the tumor cells, microinfiltrates may have developed in the surrounding areas, but CDFI cannot detect the microinfiltrates[ 12 ]. Thus, early lymphomas and indolent lymphomas were more likely to present a “hilar” distribution. In invasive lymphomas, tumor cells can even reach the lymph nodes from the external side, when the disease has its origin in another lymph node of the cluster and thereafter invades the rest of the nodes, similar to metastasis, which explains why invasive lymphomas show a predominance of "mixed" and "peripheral" distribution[ 26 ]. The RI values were higher in invasive lymphoma and lower in indolent lymphoma, with optimal cut-off value of 0.625, providing sensitivity, specificity, and accuracy of 67.4%, 84.6%, and 81.3% respectively. Likewise, in the JIANG et al. [ 19 ]study, the RI cut-off value was 0.595, providing a sensitivity, specificity, and accuracy of 85%, 79%, and 81.5%. In molecular biology, angiogenesis and translocation of vessels occur in the course of multiplication and infiltration of malignant tumor cells. This process is accompanied either by the destruction of the basement membrane of the blood vessels or by the migration and proliferation of endothelial cells, leading to the narrowing of blood vessels and an increase in blood flow resistance[ 27 ]. In contrast, in early-stage lymphoma or indolent lymphoma, the biological behavior of the lymphoma cells and the morphology of the vessels are similar to that of normal and, therefore, may have a lower RI. Consequently, as the aggressiveness of the lymphoma increases, the RI increases accordingly[ 28 ]. In CEUS, necrosis was only observed in invasive lymphomas. Although the rate of necrosis in lymphomas is low, necrosis can occur when the growth rate of tumor cells exceeds the rate of blood supply. The presence of necrosis, in turn, is often a late event in the invasion of lymph nodes and is highly suggestive of tumor aggressiveness[ 29 ]. The previous paper has noted that massive necrosis suggests complete lymph node invasion by neoplastic tissue [ 12 ]. Among the quantitative parameters of CEUS, ATM is shorter in invasive lymphomas (< 15.058), with a low AUC of 0.636, poor sensitivity of 53.6%, and high specificity of 83.3%, respectively. This probably is related to the fact that the more advanced the stage of the tumor, or the more aggressive it is, the more vascular the tumor contains. As a result, there is an increase in blood flow velocity within the tumor and, accordingly, a shorter ATM[ 19 ]. However, in the previous study by Jiang et al[ 19 ], they did not find any meaningful quantitative parameters in the differential diagnosis of invasive and indolent lymphomas by CEUS, given that their sample size of indolent lymphomas was only 12 cases. Although the number of vessels was not statistically different in our study, it is still an indicator we need to keep an eye on. Rich blood supply is the hallmark of malignant lymphoma[ 30 ]. In our study, both the indolent and invasive lymphomas had an abundant number of microvessels, and there was no statistical difference between them. Consistent with this, most lymphomas showed high enhancement in CEUS, especially indolent lymphomas, all of which exhibit hyperenhancement. Likewise, in the study by MA et al[ 31 ], four indolent lymphomas they included all showed a rapid homogenous hyper-enhanced pattern in CEUS, noting that CEUS imaging of indolent lymphomas was only affected by blood flow. Although there is massive angiogenesis within both invasive and indolent lymphomas, the vessels within the former are more immature, straggly, and tiny[ 32 ]. However, Over-angiogenesis is an independent marker of poorer survival in part of indolent lymphomas and may promote transformation [ 8 ]. Promisingly, the prediction of transformation of indolent lymphoma by angiography is a study direction. AngiPLUS improves the detection of abnormal blood flow distribution in malignant lymphomas and increases the diagnostic sensitivity (87%)[ 33 ]. With AngioPLUS, 18% of the lymphomas (10 cases of invasive lymphoma, 5 cases of indolent lymphoma) displayed a more complex distribution in our study. Relative to CDFI and AngioPLUS, the CEUS had the highest diagnostic specificity of 87.9%. It was also found that CEUS is less sensitive for diagnosis than AngioPLUS, which is consistent with the results obtained by Kratzer et al.[ 34 ] in their comparative study of AngioPLUS and CEUS in breast tumors. It may be that excessive contrast concentration does not match the injection rate and the purpose of the contrast, resulting in high and blurred contrast images of the target area and reduced fine resolution and contrast resolution[ 35 , 36 ]. Besides, the combination of the three techniques has the highest diagnostic efficacy (AUC = 0.941), with a sensitivity of 90.7%, specificity of 85.7%. CDFI combined with CEUS had the highest diagnostic sensitivity of 98.1%. Unexpectedly, there was no statistically significant difference between CDFI combined with CEUS and the combination of the three. Therefore, we recommend using CDFI in combination with CEUS to differentiate invasive and indolent lymphomas for the highest sensitivity and excellent diagnostic efficacy. However, our study has limitations. Firstly, the sample size was relatively small, especially for indolent lymphomas. Secondly, selection bias is due to selecting only superficial lymph nodes. For the cases of deep lymph node enlargement, extra-nodal infiltration, and hepatosplenic infiltration, this is still where the limitations of ultrasonography lie. Thirdly, the parameters of TIC may be affected by many factors, including the dose of contrast, the machine, the patient's metabolism, and the speed of contrast agent injection. Therefore, ultrasonographic vascular imaging can currently only be an aid in identifying invasive and indolent lymphomatous lymph nodes. It still requires a large sample size for further study. Conclusion Obtaining accurate pathological tissue for the early identification of transformed lymphoma before the onset of clinical symptoms is an ongoing endeavour for clinicians. Our study demonstrated that Ultrasonographic Vascular imaging can help identifying invasive and indolent lymphomatous lymph nodes, and CDFI combined with CEUS has the highest diagnostic sensitivity, which can guide clinicians to make more accurate diagnosis. Declarations Statement Informed consent was obtained from all subjects and/or their legal guardian. Acknowledgements We thank all the patients who participated in this study. Conflicts of Interest The authors declare no competing interests. Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Author information Authors: Wenjuan Lu 1a , Lin Li 1a , Hongyan Deng b , Wenqin Chen a , Hua Shu b , Pingyang Zhang * a and Xinhua Ye * b Affiliation: a Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China. b Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China. Contributions: All authors contributed to the study conception. Study design, material preparation, data collection and analysis were performed by W.L., L.L., P.Z. and X.Y. The first draft of the manuscript was written by W.L. and L.L. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. First Authors: Wenjuan Lu and Lin Lihavecontributed equally to this work and share first authorship. Corresponding authors: Correspondence toPingyang Zhang * a and Xinhua Ye * b Pingyang Zhang * : Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China. E-mail: [email protected] ; Xinhua Ye*: Department of Ultrasound, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China. E-mail: [email protected] ; Tel: 86-025-13952002732. Conflict of Interest Statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethical Statement The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol adheres to the 1964 Helsinki Declaration and its successive emendations and was approved by the local ethics committee (approval ID: 2022-SR-058). 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Koh, Comparison of the Diagnostic Performance of Power Doppler Ultrasound and a New Microvascular Doppler Ultrasound Technique (AngioPLUS) for Differentiating Benign and Malignant Breast Masses, J Ultrasound Med 37(11) (2018) 2689–2698. doi: 10.1002/jum.14602 . C. Dudau, S. Hameed, D. Gibson, et al., Can contrast-enhanced ultrasound distinguish malignant from reactive lymph nodes in patients with head and neck cancers?, Ultrasound Med Biol 40(4) (2014) 747–754. doi: 10.1016/j.ultrasmedbio.2013.10.015 . L. Xin, Z. Yan, X. Zhang, et al., Parameters for Contrast-Enhanced Ultrasound (CEUS) of Enlarged Superficial Lymph Nodes for the Evaluation of Therapeutic Response in Lymphoma: A Preliminary Study, Medical science monitor: international medical journal of experimental and clinical research 23 (2017) 5430–5438. A. Ahuja, M. Ying, An overview of neck node sonography, Invest Radiol 37(6) (2002) 333–342. D.D. Adler, P.L. Carson, J.M. Rubin, D. Quinn-Reid, Doppler ultrasound color flow imaging in the study of breast cancer: preliminary findings, Ultrasound Med Biol 16(6) (1990) 553–559. M.J. Son, S. Kim, H.K. Jung, K.H. Ko, J.E. Koh, A.Y. Park, Can Ultrasonographic Vascular and Elastographic Features of Invasive Ductal Breast Carcinoma Predict Histologic Aggressiveness?, Academic radiology 27(4) (2020) 487–496. doi: 10.1016/j.acra.2019.06.009 . W. Jiang, H. Xue, Q. Wang, X. Zhang, Z. Wang, C. Zhao, Value of contrast-enhanced ultrasound and PET/CT in assessment of extramedullary lymphoma, Eur J Radiol 99 (2018) 88–93. doi: 10.1016/j.ejrad.2017.12.001 . X. Niu, W. Jiang, X. Zhang, et al., Comparison of Contrast-Enhanced Ultrasound and Positron Emission Tomography/Computed Tomography (PET/CT) in Lymphoma, Med Sci Monit 24 (2018) 5558–5565. doi: 10.12659/MSM.908849 . A. Chhabra, O. Ashikyan, C. Slepicka, et al., Conventional MR and diffusion-weighted imaging of musculoskeletal soft tissue malignancy: correlation with histologic grading, Eur Radiol 29(8) (2019) 4485–4494. doi: 10.1007/s00330-018-5845-9 . A.M. Perry, T.M. Cardesa-Salzmann, P.N. Meyer, et al., A new biologic prognostic model based on immunohistochemistry predicts survival in patients with diffuse large B-cell lymphoma, Blood 120(11) (2012) 2290–2296. doi: 10.1182/blood-2012-05-430389 . S.P. Kataria, S. Malik, R. Yadav, R. Kapil, R. Sen, Histomorphological and Morphometric Evaluation of Microvessel Density in Nodal Non-Hodgkin Lymphoma Using CD34 and CD105, Journal of laboratory physicians 13(1) (2021) 22–28. doi: 10.1055/s-0041-1726569 . A. Sabaté-Llobera, M. Cortés-Romera, S. Mercadal, et al., Low-Dose PET/CT and Full-Dose Contrast-Enhanced CT at the Initial Staging of Localized Diffuse Large B-Cell Lymphomas, Clinical medicine insights. Blood disorders 9 (2016) 29–32. doi: 10.4137/CMBD.S38468 . N. Gómez León, R.C. Delgado-Bolton, L. Del Campo Del Val, et al., Multicenter Comparison of Contrast-Enhanced FDG PET/CT and 64-Slice Multi-Detector-Row CT for Initial Staging and Response Evaluation at the End of Treatment in Patients With Lymphoma, Clin Nucl Med 42(8) (2017) 595–602. doi: 10.1097/RLU.0000000000001718 . F. Giovagnorio, M. Galluzzo, C. Andreoli, C.M.L. De, V. David, Color Doppler sonography in the evaluation of superficial lymphomatous lymph nodes, J Ultrasound Med 21(4) (2002) 403–408. G. Esen, Ultrasound of superficial lymph nodes, Eur J Radiol 58(3) (2006) 345–359. M. Ying, A. Ahuja, F. Brook, Accuracy of sonographic vascular features in differentiating different causes of cervical lymphadenopathy, Ultrasound Med Biol 30(4) (2004) 441–447. A. Ahuja, M. Ying, Sonography of neck lymph nodes. Part II: abnormal lymph nodes, Clin Radiol 58(5) (2003) 359–366. J. Nie, W. Ling, Q. Yang, H. Jin, X. Ou, X. Ma, The Value of CEUS in Distinguishing Cancerous Lymph Nodes From the Primary Lymphoma of the Head and Neck, Front Oncol 10 (2020) 473. doi: 10.3389/fonc.2020.00473 . X. Ma, W. Ling, F. Xia, Y. Zhang, C. Zhu, J. He, Application of Contrast-Enhanced Ultrasound (CEUS) in Lymphomatous Lymph Nodes: A Comparison between PET/CT and Contrast-Enhanced CT, Contrast media & molecular imaging 2019 (2019) 5709698. doi: 10.1155/2019/5709698 . D. Ribatti, B. Nico, G. Ranieri, G. Specchia, A. Vacca, The role of angiogenesis in human non-Hodgkin lymphomas, Neoplasia (New York, N.Y.) 15(3) (2013) 231–238. J. Yoo, B.K. Je, J.Y. Choo, Ultrasonographic Demonstration of the Tissue Microvasculature in Children: Microvascular Ultrasonography Versus Conventional Color Doppler Ultrasonography, Korean J Radiol 21(2) (2020) 146–158. doi: 10.3348/kjr.2019.0500 . W. Kratzer, M. Güthle, F. Dobler, et al., Comparison of superb microvascular imaging (SMI) quantified with ImageJ to quantified contrast-enhanced ultrasound (qCEUS) in liver metastases-a pilot study, Quant Imaging Med Surg 12(3) (2022) 1762–1774. doi: 10.21037/qims-21-383 . E. Moghimirad, J. Bamber, E. Harris, Plane wave versus focused transmissions for contrast enhanced ultrasound imaging: the role of parameter settings and the effects of flow rate on contrast measurements, Phys Med Biol 64(9) (2019) 095003. doi: 10.1088/1361-6560/ab13f2 . D.T. Fetzer, V. Rafailidis, C. Peterson, E.G. Grant, P. Sidhu, R.G. Barr, Artifacts in contrast-enhanced ultrasound: a pictorial essay, Abdom Radiol (NY) 43(4) (2018) 977–997. doi: 10.1007/s00261-017-1417-8 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 07 Feb, 2025 Reviews received at journal 08 Dec, 2024 Reviewers agreed at journal 07 Dec, 2024 Reviewers agreed at journal 06 Dec, 2024 Reviews received at journal 20 Jul, 2024 Reviewers agreed at journal 07 Jul, 2024 Reviewers invited by journal 04 Jul, 2024 Editor assigned by journal 26 Jun, 2024 Editor invited by journal 04 Jun, 2024 Submission checks completed at journal 02 Jun, 2024 First submitted to journal 28 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4488051","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":313906205,"identity":"54bbbd49-8be1-4cd1-9c71-437938b63449","order_by":0,"name":"Wenjuan Lu","email":"","orcid":"","institution":"Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenjuan","middleName":"","lastName":"Lu","suffix":""},{"id":313906206,"identity":"a1449d7e-a697-48af-9f30-01431024bb97","order_by":1,"name":"Lin Li","email":"","orcid":"","institution":"Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Li","suffix":""},{"id":313906207,"identity":"f21a0083-8602-4b33-ba25-38512f805227","order_by":2,"name":"Hongyan Deng","email":"","orcid":"","institution":"Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongyan","middleName":"","lastName":"Deng","suffix":""},{"id":313906209,"identity":"5c191909-1acb-4cbb-8bd9-6d15863be440","order_by":3,"name":"Wenqin Chen","email":"","orcid":"","institution":"Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenqin","middleName":"","lastName":"Chen","suffix":""},{"id":313906210,"identity":"eb20a974-b633-4e37-be49-84f4c4b8d524","order_by":4,"name":"Hua Shu","email":"","orcid":"","institution":"Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Shu","suffix":""},{"id":313906211,"identity":"667b414a-0b12-4aa0-a395-df9adeedc17b","order_by":5,"name":"Pingyang Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYDACCSD+UGHDw8/eQIIWxhln0mQkew6QoIWZt+2wjcENByJ1yM/uPSbBc+Y8D8MNBsYPH3OI0MI451yahETFbR7G2Q3MkjO3EaGFWSLHTMLgzG0eZpkDbMy8xGhhA2lJbDvHwyaRQKQWHpCWg20HeHiI1iIhkZds2XAmmUeC52AzcX6Rn5F78PafCjt7++PNBz98JEYL0GksEhAGYwNR6kFamD8Qq3QUjIJRMApGKAAAgc8zI4z2OdQAAAAASUVORK5CYII=","orcid":"","institution":"Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Pingyang","middleName":"","lastName":"Zhang","suffix":""},{"id":313906213,"identity":"70de0939-6279-4bb9-864c-43712ec2c377","order_by":6,"name":"Xinhua Ye","email":"","orcid":"","institution":"Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xinhua","middleName":"","lastName":"Ye","suffix":""}],"badges":[],"createdAt":"2024-05-28 04:36:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4488051/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4488051/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-93545-w","type":"published","date":"2025-03-22T15:57:42+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58517603,"identity":"028d9c72-73d9-41c0-9372-22dd305f7a9d","added_by":"auto","created_at":"2024-06-17 16:58:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":808819,"visible":true,"origin":"","legend":"\u003cp\u003e(A): Invasive lymphoma appears on CDFI as a punctate \"central\" blood flow with a bit of \"Peripheral\" blood flow signal.\u003c/p\u003e\n\u003cp\u003e(B): On AngioPLUS, the same lymphoma shows an abundant “mixed” blood flow signal.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4488051/v1/d315ee23fa356d6f2d6c78ae.png"},{"id":58516692,"identity":"9e689b08-4f9c-4a64-8662-968b79c5e177","added_by":"auto","created_at":"2024-06-17 16:50:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":770270,"visible":true,"origin":"","legend":"\u003cp\u003eThe indolent lymphoma shows a typical \"hilar\" flow on CDFI (A), and the amount of flow signal is increasing on AngioPLUS(B).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4488051/v1/8355c8a726155a0eb4525e61.png"},{"id":58516687,"identity":"55600415-3908-41d6-b7b7-f811d2a5d09e","added_by":"auto","created_at":"2024-06-17 16:50:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46745,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of RI in invasive and indolent non-Hodgkin's lymphoma (NHL), demonstrating a higher RI in invasive NHL. However, in the lower RI levels, there is an overlap between invasive and indolent NHL.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4488051/v1/3d5f47c7f472f198bff78512.png"},{"id":58517604,"identity":"d7508d03-479f-4598-981e-93fcfd9f2927","added_by":"auto","created_at":"2024-06-17 16:58:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1111387,"visible":true,"origin":"","legend":"\u003cp\u003e(A): An indolent lymphoma appears as a well-defined homogeneous hyperenhancement on CEUS, suggesting that the blood supply is also abundant in indolent lymphomas.\u003c/p\u003e\n\u003cp\u003e(B): Two invasive lymphomas show heterogeneous enhancement on CEUS, with a large area of necrosis.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4488051/v1/7f0c5cb1f96b49f5ba2bdebd.png"},{"id":58516688,"identity":"ab623468-a9f2-4673-9f83-d721c493fb53","added_by":"auto","created_at":"2024-06-17 16:50:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41229,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve for assessing the diagnostic value of different vascular imaging.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4488051/v1/76349857bd29c14c0b120bd0.png"},{"id":79120454,"identity":"3d2bd7b0-5db6-455a-ba6a-884acbeedd91","added_by":"auto","created_at":"2025-03-24 16:08:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5252884,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4488051/v1/bf2fbdd9-acec-4ccb-957f-5ea15605100d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eIdentification of superficial invasive and indolent lymphomatous lymph nodes by multiple Ultrasonographic vascular imaging\u003c/p\u003e","fulltext":[{"header":"Advances in knowledge","content":"\u003col\u003e\n \u003cli\u003eTransformation of lymphoma exists in some patients and the results of this study may assist in identifying the presence of transformed lymphoma and guide clinical management.\u003c/li\u003e\n \u003cli\u003eSelection of appropriate lymph nodes for puncture is a pressing clinical problem, and ultrasound can identify transformed lymph nodes and ultimately guide puncture biopsy.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eAccording to the fifth edition of the World Health Organization Classification of Lymphoid Neoplasms of the Haematological System, lymphomas can be divided into more than 100 subtypes[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Based on the proliferation rates and clinical course, they are broadly divided into invasive and indolent lymphomas[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Clinically, transformation may occur in various low-grade indolent non-Hodgkin's lymphomas (NHL), which is defined as the progression from a histologically indolent lymphoma to a more invasive lymphoma. In this stage of the disease, there are different types of lymphomas in the body (FL with DLBCL, etc.). This transformation is associated with disease progression and poor prognosis[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Obtaining specific tissues to produce pathological findings is currently the predominant method of diagnosing lymphoma. However, simply obtaining the most accessible lymph node may not establish the diagnosis as transformation usually only occurs in part of lymph nodes or extranodal sites[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, it is necessary to determine the clinical imaging presentation of invasive lymphoma to select biopsy sites and subsequent treatment.\u003c/p\u003e \u003cp\u003ePET/CT has been proven helpful in identifying transformed lymph nodes with clinical signs[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, its high cost and radiological damage are a deterrent for some patients. Besides, current studies have shown that the accuracy of PET/CT in identifying benign tumors and indolent lymphomas is not ideal[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. So, the attention is focused on a non-invasive and easy-to-use diagnostic technique, which is ultrasonographic vascular imaging.\u003c/p\u003e \u003cp\u003eBased on the pathophysiological background, angiogenesis has a vital role in lymphoma biology, and lymphoma subtypes differ significantly in terms of angiogenesis[\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Menzel et al[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] found that the progression of invasive lymphoma is usually accompanied by a so-called \"vascular phase,\" which represents extensive vascularization of the lymph nodes, with the exponential growth of the internal vessels and no intervals, while indolent lymphomas are well differentiated, with relatively normal blood flow. Hence, we focus on the advantages of ultrasonographic Vascular imaging for qualitative and quantitative assessment of lymph node blood flow. The techniques include color Doppler flow (CDFI), angio plus ultrasound imaging (AngioPLUS), and contrast-enhanced ultrasound (CEUS). It was proved that CDFI is helpful to the differential diagnosis of superficial enlarged lymph nodes and to reflect the aggressiveness of lymphoma[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. AngioPLUS maximizes the velocity resolution of blood flow with a detailed resolution of up to 50 microns, which can detect the tiny vessels[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. And CEUS combines real-time visualization of microvascular perfusion in nodules and time-intensity curve (TIC) analysis to provide an objective and quantitative way to analyze perfusion characteristics of lymph nodes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, this study evaluated whether ultrasonographic vascular imaging could help differentiate superficial lymph nodes of different WHO lymphoma subtypes, thus providing guidance and recommendations for clinical biopsy.\u003c/p\u003e"},{"header":"Materials and Method","content":"\u003cp\u003eAll the qualitative and quantitative indicators of ultrasonographic vascular imaging were assessed by two radiologists with more than five years of experience.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective analysis of 116 patients between September 2020 and November 2022, who underwent ultrasonographic vascular imaging for superficial enlarged lymph nodes. Superficial lymph nodes that showed high uptake in PET/CT were selected in our study. Then, 34 patients were further excluded based on the following exclusion criteria: selected lymph nodes without pathological confirmation(n\u0026thinsp;=\u0026thinsp;12); age\u0026thinsp;\u0026lt;\u0026thinsp;18 years(n\u0026thinsp;=\u0026thinsp;0); fused lymphomas(n\u0026thinsp;=\u0026thinsp;6); interval between US examination and histopathology more than 60 days(n\u0026thinsp;=\u0026thinsp;0); pregnant or breast-feeding women(n\u0026thinsp;=\u0026thinsp;0); patients underwent chemical or radiation therapy(n\u0026thinsp;=\u0026thinsp;5); people who are allergic to contrast media (n\u0026thinsp;=\u0026thinsp;3); patients with severe heart failure or cachexia(n\u0026thinsp;=\u0026thinsp;8); those with more than one histologically confirmed subtype of NHL or coexistence of Hodgkin's disease and NHL(n\u0026thinsp;=\u0026thinsp;0). Ultimately, 82 patients with 82 lesions were enrolled in the study. Pathological confirmation was performed for all patients based on the fifth edition of the WHO Classification of Lymphoid Neoplasms of the Haematological System. According to the proliferation rates and clinical course, lymph nodes are divided into indolent and invasive lymphomatous lymph nodes[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The study was approved by the Ethics Committee under ethics number 2022-SR-058. All methods were performed in accordance with the relevant guidelines and regulations. Two sonographers performed the three ultrasound examinations on the patients at the same time.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCDFI\u003c/h2\u003e \u003cp\u003eCDFI was performed on the Aixplorer ultrasound system (SuperSonic Imagine,Aix-en-Provence, France) equipped with an SL15-4 linear transducer. The sampling frame was sized to completely encapsulate the mass. The color gain was adjusted to a level where low velocity vascular flow in the target lesion can be detected with minimal background noise. The velocity scale for color Doppler examination was 10 cm/s. Multi-sectional scanning was used to show the maximum vascular flow in the target lesion. If lymphatic hilar structures were present, they need to be adequately displayed. Patients took a supine position, breathed calmly, and fully exposed the area to be examined. The patterns of CDFI were categorized as the following four types[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]: (1) hilar; (2) peripheral; (3) mixed: the existence of both hilar and peripheral flow signal or scattered short rod-shaped blood flow signals; and (4) absent. The resistance index (RI) of blood flow should be measured at different sites[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Besides, the sampling volumes were all adjusted to the smallest size to avoid bias caused by different volumes sizes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAngioPLUS\u003c/h2\u003e \u003cp\u003eAngioPLUS was also performed on the Aixplorer ultrasound system with SL15-4 linear transducer. The color gain and sampling frame were adjusted in line with that of the color Doppler, while the scale was set at 3cm/s. The same lymph nodes as described above were selected for AngioPLUS. Referring to the previous literature[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], we assessed the microvascular condition within the lymphoma in terms of AngioPLUS amount, distribution of vessels, and Four-tier vascularity score. The number of vessels in the lymphoma could be qualitatively defined as follows: (1). Absent; (2). Minimal: 1\u0026ndash;2 vessels within the mass or at the edge of the mass; (3). Moderate: 3\u0026ndash;4 vessels within the mass or at the edge of the mass; (4). Marked: 5 or more penetrating vessels in the mass; The distribution of blood vessels was defined as: (1). Absent; (2). Vessels in the rim; (3). Internal blood flow: punctate or perforating vessels exist in the mass; (4). Combined. For four-tier vascularity score, we referred to the scoring method designed by Min Ji Son et al[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003e(1). Score 1: no vessels; central or peripheral punctate vessels;\u003c/p\u003e \u003cp\u003e(2). Score 2: 1 or 2 peripheral vessels that do not enter the nodes;\u003c/p\u003e \u003cp\u003e(3). Score 3: 3 or more peripheral vessels, or 1\u0026ndash;2 penetrating vessels;\u003c/p\u003e \u003cp\u003e(4). Score 4: 3 or more penetrating vessels or disrupted internal blood flow.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCEUS\u003c/h2\u003e \u003cp\u003eThe LogiqE9 ultrasound machine (GE Medical Systems, Milwaukee, WI, USA) with a 9L linear transducer was used to perform the CEUS examination in MSK GEN mode. The mechanical index (MI) and thermal index (TI) was set at 0.14, 0.0 respectively. Then 5ml of 0.9% saline was added into the contrast medium (SonoVue, Bracco, Milan, Italian) and shaken forcefully to make emulsion-like microbubbles for preparation. The patient was positioned as above, and the same lymphoma section as above is selected for observation. Afterward, 2.4 ml of contrast medium was injected rapidly into the patient's elbow vein, followed by 5 ml of saline. The timer built into the machine started simultaneously and recorded the angiography process in real-time for approximately 60s. During this procedure, the probe was kept fixed. After the angiography, the dynamic video was saved, and the patient was closely observed for any discomfort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCEUS imaging analysis\u003c/h2\u003e \u003cp\u003eThe characteristics of lymphomas in CEUS included enhancement mode, boundary, intensity, distribution, and necrosis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. (1) Enhancement intensity was divided into no enhancement, low enhancement (lower than surrounding normal tissue), moderate enhancement (equal to the surrounding normal tissue), high enhancement (higher than surrounding normal tissue, but lower than surrounding arteries), and intense enhancement (equal to the surrounding arteries). (2) Enhancement distribution was classified as hilar, central (enhanced from peripheral to the interior), centrifugal (enhanced from the center to peripheral), mixed (simultaneously enhanced at the margins and the center or diffuse enhancement), and peripheral. (3) Enhancement boundary was divided into clear and unclear. (4) Enhancement patterns: homogeneous and heterogeneous.\u003c/p\u003e \u003cp\u003eObserve the process of lymphoma angiography and intercept the period from 1 second before the start of enhancement to 40 seconds of enhancement for TIC analysis, using GE LogiqE9 quantification software. The entire enhanced lymph node was selected as the region of interest (ROI). It was essential to avoid surrounding tissues and blood vessels when outlining the ROI. The parameters provided by TIC analysis had to be measured three times and averaged, including arrival time (ATM); time to peak (TP); △T\u0026thinsp;=\u0026thinsp;TTP-ATM; area under the gamma curve (Area); curve gradient (Grad); base intensity (BI); peak intensity (PI) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHistologic Analysis\u003c/h2\u003e \u003cp\u003eExperienced hematopathologists reviewed all tissue specimens at our institution. The pathological diagnosis was confirmed for all patients based on the fifth edition of the World Health Organization Classification of Lymphoid Neoplasms of the Haematological System.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eSPSS software (version 21.0; IBM Corporation, NY, USA) was used for data analysis. The quantitative parameters were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Statistical analysis between the two groups was done using independent samples t-test for quantitative parameters and chi-square test for qualitative parameters. Regression analysis was used to diagnose image characteristics and quantitative parameters jointly. The diagnostic value of different ultrasound techniques was analyzed by the area under the receiver-operating characteristic (ROC) with the Medcalc 18.2.1.0 software. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was statistically significant. Observer consistency was assessed using intra-group correlation (ICC) and kappa for continuous and categorical variables. Consistency was considered poor when ICC/kappa was 0-0.4; 0.4\u0026ndash;0.59, fair; 0.6\u0026ndash;0.74, good; and 0.75-1, excellent[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eICC\u003c/h2\u003e \u003cp\u003eICC and kappa values showed excellent inter-observer agreement (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConsistency of the observers with regard to US features of lymphomas.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeatures\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICC/Kappa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFeatures\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eICC/Kappa\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatterns of CDFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmount of vessels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistribution of vessels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e△T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour-tier vascularity score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhancement intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhancement distribution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e△I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhancement boundary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNecrosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhancement pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eClinical features\u003c/h2\u003e \u003cp\u003eEighty-two patients (37 males and 45 females; average age, 60.3 years; range, 28\u0026ndash;88 years) with 82 lymphomatous lymph nodes were enrolled in our research. Of the 82 lymphomatous lymph nodes, there were 54 cases of invasive lymphoma (45 cases of diffuse large B-cell lymphoma, DLBCL; 3 cases of anaplastic large cell lymphoma, ALCL; 6 cases of grade III follicular lymphoma) and 28 cases of indolent lymphoma (13 cases of I-II follicular lymphoma, FL; 11 cases of nodal marginal zone lymphoma, MZL; 2 cases of lymphoplasmacytic lymphoma, LPL; and 2 cases of B-Cell Lymphoproliferative Disease, BCLD). Besides, 54 enlarged lymph nodes were in the neck, 17 in the inguinal region, and 11 in the axillary.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCDFI and AngioPLUS\u003c/h2\u003e \u003cp\u003eCharacteristics of CDFI and AngioPLUS in invasive lymphoma and indolent lymph nodes are compared in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There was a significant difference in the characteristics of internal vascular distribution between the two groups. In invasive lymphoma, it mainly presented as \u0026ldquo;mixed\u0026rdquo; blood flow (25/54, 46.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and an absence of blood flow (9/54, 16.7%), whereas half of the indolent lymphoma (50.0%) manifested as \u0026ldquo;hilar\u0026rdquo; type of blood flow (P\u0026thinsp;=\u0026thinsp;0.002) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Besides, \u0026ldquo;marginal\u0026rdquo; blood supply was only present in invasive lymphomas (10/54, 18.5%). The RI of invasive lymphoma (0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09, range 0.51\u0026ndash;0.84) was higher than that of indolent lymphomas (0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07, range 0.41\u0026ndash;0.69) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The optimal cut-off value of RI was 0.625, with the sensitivity, specificity, accuracy and the area under the curve (AUC) of 67.4%, 84.6%, 81.3% and 0.813 respectively. Likewise, interms of AngioPLUS, the distribution of microvasculature of invasive lymphomas (11/54, 20.4%) was more likely to show marginal vessels than indolent lymphomas (1/28, 3.6%). However, there was no statistical significance regarding AngioPLUS amount and Four-tier vascularity score in the lymph nodes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCDFI and AngioPLUS in 82 Invasive and Indolent lymphomas.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePathology type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvasive lymphoma\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndolent lymphoma\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRI\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ePatterns of CDFI\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003cp\u003ehilar\u003c/p\u003e \u003cp\u003eMixed\u003c/p\u003e \u003cp\u003ePeripheral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003cp\u003e9(16.7%)\u003c/p\u003e \u003cp\u003e10(18.5%)\u003c/p\u003e \u003cp\u003e25(46.3%)\u003c/p\u003e \u003cp\u003e10(18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003cp\u003e1(3.6%)\u003c/p\u003e \u003cp\u003e14(50.0%)\u003c/p\u003e \u003cp\u003e13(46.4%)\u003c/p\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmount of vessels\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003eMarked\u003c/p\u003e \u003cp\u003e\u003cb\u003eDistribution of vessels\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(3.7%)\u003c/p\u003e \u003cp\u003e10(18.5%)\u003c/p\u003e \u003cp\u003e12(22.2%)\u003c/p\u003e \u003cp\u003e30(55.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e1(3.6%)\u003c/p\u003e \u003cp\u003e7(25.0%)\u003c/p\u003e \u003cp\u003e20(71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003cp\u003eInternal vascularity\u003c/p\u003e \u003cp\u003eVessels in rim\u003c/p\u003e \u003cp\u003eCombined\u003c/p\u003e \u003cp\u003e\u003cb\u003eFour-tier vascularity score\u003c/b\u003e\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(3.7%)\u003c/p\u003e \u003cp\u003e7(13.0%)\u003c/p\u003e \u003cp\u003e11(20.4%)\u003c/p\u003e \u003cp\u003e34(63.0%)\u003c/p\u003e \u003cp\u003e6(11.1%)\u003c/p\u003e \u003cp\u003e10(18.5%)\u003c/p\u003e \u003cp\u003e16(29.6%)\u003c/p\u003e \u003cp\u003e22(40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e10(35.7%)\u003c/p\u003e \u003cp\u003e1(3.6%)\u003c/p\u003e \u003cp\u003e17(60.7%)\u003c/p\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e2(7.1%)\u003c/p\u003e \u003cp\u003e12(42.9%)\u003c/p\u003e \u003cp\u003e14(50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCEUS\u003c/h2\u003e \u003cp\u003eQuantitative results of CEUS are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For the optimization of the threshold values for ATM (15.058s), differences were observed between the two groups, with the AUC of 0.636, the sensitivity of 53.6%, and the specificity of 83.3%, respectively (P\u0026thinsp;=\u0026thinsp;0.043). There were no statistical differences for the remaining parameters. Qualitative findings of CEUS are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The results showed that the majority of invasive (43/54, 79.7%) and indolent (28/28, 100%) lymphomas displayed hyperenhancement, and no statistical difference was found between them (P\u0026thinsp;=\u0026thinsp;0.141). Concerning enhancement distribution, invasive lymphomas (19/54, 35.2% vs. 4/28,14.3%) showed more of a centripetal enhancement distribution. Besides, \u0026ldquo;marginal\u0026rdquo; enhancement (P\u0026thinsp;=\u0026thinsp;0.028) and necrosis (p\u0026thinsp;=\u0026thinsp;0.026) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) were only seen in invasive lymphomas.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQualitative results of CEUS.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eInvasive lymphoma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIndolent lymphoma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.55\u0026ndash;21.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.88\u0026ndash;21.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e13.84\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.22\u0026ndash;38.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e23.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.81\u0026ndash;36.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e24.21\u0026thinsp;\u0026plusmn;\u0026thinsp;6.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e△T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.67\u0026ndash;23.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.44\u0026thinsp;\u0026plusmn;\u0026thinsp;3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.61\u0026ndash;16.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e10.38\u0026thinsp;\u0026plusmn;\u0026thinsp;2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-70.90to -54.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-63.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-70.50to -57.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e-63.82\u0026thinsp;\u0026plusmn;\u0026thinsp;3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-60.64to -34.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-46.35\u0026thinsp;\u0026plusmn;\u0026thinsp;5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-56.70to -32.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e-46.46\u0026thinsp;\u0026plusmn;\u0026thinsp;6.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e△I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.96\u0026ndash;26.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.82\u0026thinsp;\u0026plusmn;\u0026thinsp;3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.60-30.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e17.36\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.442\u0026ndash;3.802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u0026ndash;3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.41-567.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e329.36\u0026thinsp;\u0026plusmn;\u0026thinsp;103.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117.37-795.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e328.23\u0026thinsp;\u0026plusmn;\u0026thinsp;143.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the invasive and indolent lymphoma qualitative parameters using CEUS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePathology type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvasive lymphoma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndolent lymphoma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhancement intensity\u003c/p\u003e \u003cp\u003enone\u003c/p\u003e \u003cp\u003eweak\u003c/p\u003e \u003cp\u003emoderate\u003c/p\u003e \u003cp\u003ehigh\u003c/p\u003e \u003cp\u003eintense\u003c/p\u003e \u003cp\u003eEnhancement pattern\u003c/p\u003e \u003cp\u003ehomogeneous\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e3(5.5%)\u003c/p\u003e \u003cp\u003e7(13.0%)\u003c/p\u003e \u003cp\u003e16(29.6%)\u003c/p\u003e \u003cp\u003e28(51.9%)\u003c/p\u003e \u003cp\u003e23(42.6%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e11(39.3%)\u003c/p\u003e \u003cp\u003e17(60.7%)\u003c/p\u003e \u003cp\u003e18(64.3%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eheterogeneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31(57.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10(35.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnhancement distribution\u003c/b\u003e\u003c/p\u003e \u003cp\u003ehilar\u003c/p\u003e \u003cp\u003ecentral\u003c/p\u003e \u003cp\u003ecentrifugal\u003c/p\u003e \u003cp\u003emixed\u003c/p\u003e \u003cp\u003ePeripheral\u003c/p\u003e \u003cp\u003e\u003cb\u003eEnhancement boundary\u003c/b\u003e\u003c/p\u003e \u003cp\u003eclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(20.4%)\u003c/p\u003e \u003cp\u003e19(35.2%)\u003c/p\u003e \u003cp\u003e4(7.4%)\u003c/p\u003e \u003cp\u003e15(27.8%)\u003c/p\u003e \u003cp\u003e5(9.3%)\u003c/p\u003e \u003cp\u003e25(46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(39.3%)\u003c/p\u003e \u003cp\u003e4(14.3%)\u003c/p\u003e \u003cp\u003e6(21.4%)\u003c/p\u003e \u003cp\u003e7(25.0%)\u003c/p\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e17(60.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunclear\u003c/p\u003e \u003cp\u003e\u003cb\u003eNecrosis\u003c/b\u003e\u003c/p\u003e \u003cp\u003eyes\u003c/p\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29(53.7%)\u003c/p\u003e \u003cp\u003e11(20.4%)\u003c/p\u003e \u003cp\u003e43(79.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11(39.3%)\u003c/p\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003cp\u003e28(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe combination of Ultrasound techniques\u003c/h2\u003e \u003cp\u003eThe two groups' sensitivity, specificity, and accuracy of single and multiple combined imaging techniques were compared (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The results indicated that the combination of the three had the highest diagnostic efficacy (AUC\u0026thinsp;=\u0026thinsp;0.941), with diagnostic sensitivity, specificity of 90.7%, 85.7%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In contrast, CDFI combined with CEUS had the highest diagnostic sensitivity of 0.981. And there was no statistically significant difference in diagnostic efficacy between CDFI combined with CEUS and the combination of the three primary ultrasonographic Vascular imaging techniques (p\u0026thinsp;=\u0026thinsp;0.261) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC analysis: invasive lymphoma vs. indolent lymphoma.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUROC value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCI 95%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCDFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.714\u0026ndash;0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAngioPLUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.556\u0026ndash;0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCEUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.794\u0026ndash;0.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.861\u0026ndash;0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCDFI\u0026thinsp;+\u0026thinsp;AngioPLUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.714\u0026ndash;0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAngioPLUS\u0026thinsp;+\u0026thinsp;CEUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.799\u0026ndash;0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u0026thinsp;+\u0026thinsp;AngioPLUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.887\u0026ndash;0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA precise comparison of the diagnostic accuracy of different ultrasound techniques.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDFI\u003c/p\u003e \u003cp\u003evs\u003c/p\u003e \u003cp\u003eAngioPLUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCDFI\u003c/p\u003e \u003cp\u003evs\u003c/p\u003e \u003cp\u003eCEUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u003c/p\u003e \u003cp\u003evs\u003c/p\u003e \u003cp\u003eCDFI\u0026thinsp;+\u0026thinsp;AngioPLUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u003c/p\u003e \u003cp\u003evs\u003c/p\u003e \u003cp\u003eAngioPLUS\u0026thinsp;+\u0026thinsp;CEUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u003c/p\u003e \u003cp\u003evs\u003c/p\u003e \u003cp\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u0026thinsp;+\u0026thinsp;AngioPLUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAngioPLUS\u0026thinsp;+\u0026thinsp;CDFI\u003c/p\u003e \u003cp\u003evs\u003c/p\u003e \u003cp\u003eCDFI\u0026thinsp;+\u0026thinsp;CEUS\u0026thinsp;+\u0026thinsp;AngioPLUS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifference\u0026nbsp;between\u0026nbsp;areas\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e95%CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.034 to 0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.035 to 0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.040 to 0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.006 to 0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.013 to 0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.046 to 0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere is growing evidence of a correlation between the type of vascular condition and the aggressiveness of lymphomas[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. To identify signs of transformation and to identify potential biopsy sites, this retrospective study was designed to clarify invasive and indolent Lymphomatous lymph nodes through Ultrasonographic Vascular imaging, which finally impact the selection of treatment programmes.\u003c/p\u003e \u003cp\u003eThe three ultrasound techniques, including CDFI, AngiPLUS, and CEUS, are all capable of showing vascular distribution. The results indicated that indolent lymphomas presented more often with \"hilar\" and \u0026ldquo;centrifugal\u0026rdquo; blood flow types, while invasive lymphomas had a greater distribution of \u0026ldquo;mixed\u0026rdquo; and \u0026ldquo;central\u0026rdquo;. This is consistent with previous research findings[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Besides, \u0026ldquo;peripheral\u0026rdquo; blood flow type was only found in invasive lymphomas. In line with this, Giovagnorio et al[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] found that six lymphomas showing \u0026ldquo;peripheral\u0026rdquo; vessels pathologically were all confirmed as high-grade invasive lymphoma. In conclusion, there is a correlation between the type of vascular distribution and the tissue aggressiveness of the lymphoma. In terms of biological behavior, lymphoma center is initially infiltrated by tumor cells. But indolent lymphoma is slow to develop, so the surrounding area may remain untouched for a long time. As the inside-out invasion of the tumor cells, microinfiltrates may have developed in the surrounding areas, but CDFI cannot detect the microinfiltrates[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Thus, early lymphomas and indolent lymphomas were more likely to present a \u0026ldquo;hilar\u0026rdquo; distribution. In invasive lymphomas, tumor cells can even reach the lymph nodes from the external side, when the disease has its origin in another lymph node of the cluster and thereafter invades the rest of the nodes, similar to metastasis, which explains why invasive lymphomas show a predominance of \"mixed\" and \"peripheral\" distribution[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe RI values were higher in invasive lymphoma and lower in indolent lymphoma, with optimal cut-off value of 0.625, providing sensitivity, specificity, and accuracy of 67.4%, 84.6%, and 81.3% respectively. Likewise, in the JIANG et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]study, the RI cut-off value was 0.595, providing a sensitivity, specificity, and accuracy of 85%, 79%, and 81.5%. In molecular biology, angiogenesis and translocation of vessels occur in the course of multiplication and infiltration of malignant tumor cells. This process is accompanied either by the destruction of the basement membrane of the blood vessels or by the migration and proliferation of endothelial cells, leading to the narrowing of blood vessels and an increase in blood flow resistance[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In contrast, in early-stage lymphoma or indolent lymphoma, the biological behavior of the lymphoma cells and the morphology of the vessels are similar to that of normal and, therefore, may have a lower RI. Consequently, as the aggressiveness of the lymphoma increases, the RI increases accordingly[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn CEUS, necrosis was only observed in invasive lymphomas. Although the rate of necrosis in lymphomas is low, necrosis can occur when the growth rate of tumor cells exceeds the rate of blood supply. The presence of necrosis, in turn, is often a late event in the invasion of lymph nodes and is highly suggestive of tumor aggressiveness[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The previous paper has noted that massive necrosis suggests complete lymph node invasion by neoplastic tissue [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the quantitative parameters of CEUS, ATM is shorter in invasive lymphomas (\u0026lt;\u0026thinsp;15.058), with a low AUC of 0.636, poor sensitivity of 53.6%, and high specificity of 83.3%, respectively. This probably is related to the fact that the more advanced the stage of the tumor, or the more aggressive it is, the more vascular the tumor contains. As a result, there is an increase in blood flow velocity within the tumor and, accordingly, a shorter ATM[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, in the previous study by Jiang et al[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], they did not find any meaningful quantitative parameters in the differential diagnosis of invasive and indolent lymphomas by CEUS, given that their sample size of indolent lymphomas was only 12 cases.\u003c/p\u003e \u003cp\u003eAlthough the number of vessels was not statistically different in our study, it is still an indicator we need to keep an eye on. Rich blood supply is the hallmark of malignant lymphoma[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our study, both the indolent and invasive lymphomas had an abundant number of microvessels, and there was no statistical difference between them. Consistent with this, most lymphomas showed high enhancement in CEUS, especially indolent lymphomas, all of which exhibit hyperenhancement. Likewise, in the study by MA et al[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], four indolent lymphomas they included all showed a rapid homogenous hyper-enhanced pattern in CEUS, noting that CEUS imaging of indolent lymphomas was only affected by blood flow. Although there is massive angiogenesis within both invasive and indolent lymphomas, the vessels within the former are more immature, straggly, and tiny[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, Over-angiogenesis is an independent marker of poorer survival in part of indolent lymphomas and may promote transformation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Promisingly, the prediction of transformation of indolent lymphoma by angiography is a study direction.\u003c/p\u003e \u003cp\u003eAngiPLUS improves the detection of abnormal blood flow distribution in malignant lymphomas and increases the diagnostic sensitivity (87%)[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. With AngioPLUS, 18% of the lymphomas (10 cases of invasive lymphoma, 5 cases of indolent lymphoma) displayed a more complex distribution in our study. Relative to CDFI and AngioPLUS, the CEUS had the highest diagnostic specificity of 87.9%. It was also found that CEUS is less sensitive for diagnosis than AngioPLUS, which is consistent with the results obtained by Kratzer et al.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] in their comparative study of AngioPLUS and CEUS in breast tumors. It may be that excessive contrast concentration does not match the injection rate and the purpose of the contrast, resulting in high and blurred contrast images of the target area and reduced fine resolution and contrast resolution[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Besides, the combination of the three techniques has the highest diagnostic efficacy (AUC\u0026thinsp;=\u0026thinsp;0.941), with a sensitivity of 90.7%, specificity of 85.7%. CDFI combined with CEUS had the highest diagnostic sensitivity of 98.1%. Unexpectedly, there was no statistically significant difference between CDFI combined with CEUS and the combination of the three. Therefore, we recommend using CDFI in combination with CEUS to differentiate invasive and indolent lymphomas for the highest sensitivity and excellent diagnostic efficacy.\u003c/p\u003e \u003cp\u003eHowever, our study has limitations. Firstly, the sample size was relatively small, especially for indolent lymphomas. Secondly, selection bias is due to selecting only superficial lymph nodes. For the cases of deep lymph node enlargement, extra-nodal infiltration, and hepatosplenic infiltration, this is still where the limitations of ultrasonography lie. Thirdly, the parameters of TIC may be affected by many factors, including the dose of contrast, the machine, the patient's metabolism, and the speed of contrast agent injection. Therefore, ultrasonographic vascular imaging can currently only be an aid in identifying invasive and indolent lymphomatous lymph nodes. It still requires a large sample size for further study.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eObtaining accurate pathological tissue for the early identification of transformed lymphoma before the onset of clinical symptoms is an ongoing endeavour for clinicians. Our study demonstrated that Ultrasonographic Vascular imaging can help identifying invasive and indolent lymphomatous lymph nodes, and CDFI combined with CEUS has the highest diagnostic sensitivity, which can guide clinicians to make more accurate diagnosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStatement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects and/or their legal guardian.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the patients who participated in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWenjuan Lu\u003csup\u003e1a\u003c/sup\u003e, Lin Li\u003csup\u003e1a\u003c/sup\u003e, Hongyan Deng\u003csup\u003eb\u003c/sup\u003e, Wenqin Chen\u003csup\u003ea\u003c/sup\u003e, Hua Shu\u003csup\u003eb\u003c/sup\u003e, Pingyang Zhang\u003csup\u003e*\u003c/sup\u003e\u003csup\u003ea\u003c/sup\u003e and Xinhua Ye\u003csup\u003e*\u003c/sup\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAffiliation:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eDepartment of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u0026nbsp;\u003c/sup\u003eDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eContributions:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception. Study design, material preparation, data collection and analysis were performed by W.L., L.L., P.Z. and X.Y. The first draft of the manuscript was written by W.L. and L.L. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFirst Authors:\u003c/em\u003e\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWenjuan Lu and Lin Lihavecontributed equally to this work and share first authorship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCorresponding authors:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence toPingyang Zhang\u003csup\u003e*\u003c/sup\u003e\u003csup\u003ea\u003c/sup\u003e and Xinhua Ye\u003csup\u003e*\u003c/sup\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePingyang Zhang\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China. E-mail: [email protected];\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eXinhua Ye*:\u003c/strong\u003eDepartment of Ultrasound, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China. E-mail: [email protected]; Tel: 86-025-13952002732.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol adheres to the 1964 Helsinki Declaration and its successive emendations and was approved by the local ethics committee (approval ID:\u0026nbsp;2022-SR-058). Written informed consent was obtained from the patient for publication of this study and any accompanying images.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eR. Alaggio, C. Amador, I. Anagnostopoulos, et al., The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms, Leukemia 36(7) (2022) 1720\u0026ndash;1748. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41375-022-01620-2\u003c/span\u003e\u003cspan address=\"10.1038/s41375-022-01620-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM.E. Mayerhoefer, L. Umutlu, H. 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Barr, Artifacts in contrast-enhanced ultrasound: a pictorial essay, Abdom Radiol (NY) 43(4) (2018) 977\u0026ndash;997. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00261-017-1417-8\u003c/span\u003e\u003cspan address=\"10.1007/s00261-017-1417-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Color Doppler flow, angio plus, CEUS, lymphoma, aggressiveness","lastPublishedDoi":"10.21203/rs.3.rs-4488051/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4488051/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to explore whether superficial invasive lymphomas and indolent lymphomas could be identified by Ultrasonographic vascular imaging.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eA retrospectively study enrolled 82 lymphoma patients. According to proliferation rates and clinical course, the lymph nodes were classified as invasive and indolent lymphomatous lymph nodes. All patients underwent ultrasound (US) with three effective techniques: color Doppler flow imaging (CDFI), angio plus ultrasound imaging (AngioPLUS), and contrast-enhanced ultrasound (CEUS). Qualitative and quantitative parameters from the two groups were compared. Finally, the area under the receiver-operating characteristic (ROC) and regression analysis were used to compare the differences between the two groups and determine the diagnostic efficiency of the three techniques for differentiating invasive lymphoma from indolent lymphoma.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe types of blood flow distribution between invasive and indolent lymphomatous lymph nodes were statistically different in all three Ultrasound techniques. In CDFI, invasive or indolent lymphomatous lymph nodes were determined by resistance index (RI) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In CEUS, the differences between the two groups in necrosis and arrival time (ATM) (p\u0026thinsp;=\u0026thinsp;0.026, 0.043) were statistically significant. Finally, CDFI combined with CEUS had the highest diagnostic sensitivity of 98.1%. Interobserver agreements for qualitative parameters were all excellent.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eUltrasonographic Vascular imaging is an aid in identifying invasive and indolent lymphomatous lymph nodes, and CDFI combined with CEUS had the highest diagnostic sensitivity, which can guide clinicians to make more accurate diagnosis and better treatment for patients.\u003c/p\u003e","manuscriptTitle":"Identification of superficial invasive and indolent lymphomatous lymph nodes by multiple Ultrasonographic vascular imaging","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-17 16:50:23","doi":"10.21203/rs.3.rs-4488051/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-07T13:08:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-08T18:53:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203455096678724266323022040716371316283","date":"2024-12-07T16:30:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329370002285505714306488389977139834384","date":"2024-12-06T20:29:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-20T17:16:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65852246436339277002723945225404662670","date":"2024-07-08T01:36:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-04T12:40:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-26T12:28:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-05T02:03:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-03T03:54:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-28T04:35:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b26dfb62-e938-4a56-a621-f7b70468c3f5","owner":[],"postedDate":"June 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33257317,"name":"Biological sciences/Biological techniques"},{"id":33257318,"name":"Biological sciences/Cancer"},{"id":33257319,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-03-24T16:02:08+00:00","versionOfRecord":{"articleIdentity":"rs-4488051","link":"https://doi.org/10.1038/s41598-025-93545-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-03-22 15:57:42","publishedOnDateReadable":"March 22nd, 2025"},"versionCreatedAt":"2024-06-17 16:50:23","video":"","vorDoi":"10.1038/s41598-025-93545-w","vorDoiUrl":"https://doi.org/10.1038/s41598-025-93545-w","workflowStages":[]},"version":"v1","identity":"rs-4488051","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4488051","identity":"rs-4488051","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}