HDlive Flow Silhouette Mode for Assessment of Tumor Vascularity in Advanced Cervical Cancer

INTRODUCTION

There have been several studies on two-dimensional (2D) and three-dimensional (3D) color/power Doppler ultrasound evaluations of tumor vascularity in advanced cervical cancer patients.^1–6 However, these results were inconsistent except for one factor: the histologic type. All studies suggested that tumor vascularity was not correlated with histologic characteristics of cervical cancer.

There have been several reports on the use of the HDlive flow silhouette mode for the diagnosis of fetal heart anomalies^7,8 and gynecologic disorders.^9–11 The unique advantages of this technique are that it can differentiate overlapping blood vessels and help understand the spatial relationships among blood vessels. To the best of our knowledge, there has been no report on the HDlive flow silhouette mode for assessing tumor vascularity in advanced cervical cancer. The aim of the present study was to present our experience in assessing the difference of tumor vascularity in advanced cervical cancer patients with different histologic types using this technique.

MATERIALS AND METHODS

Thirteen women with advanced cervical cancer (one each of cervical cancer stage IIA, three of stage IIB, four of stage IIIB, one of stage IVA, and four of stage IVB) were studied using the HDlive flow silhouette mode (Voluson E10, GE Healthcare Japan, Tokyo, Japan) with a mechnical transvaginal 3.7–17.5 MHz transducer (Table 1). The patients were staged according to International Federation of Gynecology and Obstetrics guidelines.¹² Eleven patients had squamous cell carcinoma (SCC), and two had GAS. This study was approved by the Kagawa University Graduate School of Medicine Ethics Committee, and the standardized written informed consent was obtained from all women.

Initially, 2D sonography and color/power Doppler were used to examine the uterus. Then, on changing to 3D color/power Doppler, scanning of the region of interest was performed and the resulting data were stored on the hard drive of the ultrasound device for future analysis. A representative vascular tree volume of the uterine cervix was generated using the HDlive flow silhouette mode. When blood velocity exceeded a threshold, dependent on the pulse repetition frequency (PRP) and high-pass filter of the device, the signal was detected. By setting the PRF as 0.9 kHz and wall motion filter as “low,” sensitivity was maximized. The 3D volume box was placed over the uterine cervix at 120° (fixed angle). Volume acquisition was performed in a period of 16 seconds or less. All volume data were analyzed, and we extracted optimal images for subsequent analysis. The HDlive flow silhouette mode was used for 3D reconstruction. One examiner (TH) conducted all HDlive flow silhouette mode examinations.

Tumor vascularity was assessed using the subjective grading system (grade I, minimal blood flow pattern; grade II, moderate blood flow pattern; and grade III, abundant blood flow pattern) (Fig. 1). The HDlive flow silhouette mode image for each patient was assigned to grades I, II, or III.

The IBM SPSS statistical software version 22 for Windows (IBM SPSS Inc., Chicago, IL, USA) was used in all cases. The amount of tumor vascularity between SCC and GMC groups was compared using χ² analysis with a contingency table (3 × 2). A value of p < 0.05 was considered significant.

RESULTS

The average age of patients was 58 ± 13.1 y.o. (mean ± SD). The tumor size in each patient is shown in Table 1. The number of patients with grade I was 2 (15.4%), that of grade II was 4 (30.8%), and that of grade III was 7 (53.8%) (Table 1).

The number of patients with grade I was 0, that of grade II was 4 (36.4%), and that of grade III was 7 (63.6%) in the SCC group, whereas that of grade I was 2 (100%) in the GAS group (p = 0.0128) (Table 2).

DISCUSSION

Alcazar et al.³ reported that subjective impressions of the amount of flow using 2D color Doppler was correlated with some tumor features in cervical cancers. However, the whole-view assessment of tumor vascularity in advanced cervical cancer patients was difficult because of the 2D character of conventional color/power Doppler. Tanaka et al.¹³ found that a 3D power Doppler (HDlive flow) frontal view of the cervix, like a colposcopic view of the cervix seen through the vagina, was the most appropriate, unique image to assess the tumor vascularity of advanced cervical cancer patients. However, the complexity and crowding of tumor vessels still could not be evaluated even if using HDlive flow. In the present study, the HDlive flow silhouette mode could clearly show the tumor vascularity of advanced cervical cancer patients because this technique can differentiate overlapping blood vessels and help understand the spatial relationships among blood vessels. Consequently, a new grading system of tumor vascularity using the HDlive flow silhouette mode in advanced cervical cancer patients could be devised. Further studies involving a larger sample size are needed to confirm the validity of this grading system using the HDlive flow silhouette mode for the assessment of tumor vascularity in advanced cervical cancer patients.

Gastric-type mucinous carcinoma of the uterine cervix is a rare variant of mucinous carcinoma of the uterine cervix associated with aggressive clinical behavior, chemoresistance, and poorer outcomes compared with usual-type endocervical carcinoma.^14–17 In the present study, GAS showed a poorly vascularized mass, whereas SCC demonstrated moderate to abundant blood flow in the mass. These results suggest that the poor vascularity is one of the clinicopathological features of GAS. However, these vascular patterns in the present study should be considered with some degree of caution because of the small number of patients studied. Further studies involving a larger sample size, especially GAS and usual-type endocervical carcinoma patients, are needed to ascertain the tumor vascularity in advanced cervical cancer patients.

AUTHORS’ CONTRIBUTIONS

All the authors take responsibility for the paper as published. Tamaki Tanaka: protocol/project development, data collection, and manuscript editing. Kenji Kanenishi: protocol/project development and manuscript editing. Tomoya Yamashita: data collection and manuscript editing. Nobuhiro Mori: data collection, statistical analysis, and manuscript editing. Toshiyuki Hata: protocol/project development, data collection/analysis, and manuscript writing.

REFERENCES

1. Tepper R, Zalel Y, et al. Transvaginal color Doppler ultrasound in the assessment of invasive cervical carcinoma. Gynecol Oncol 1996;60:26–29. DOI: 10.1006/gyno.1996.0006.

2. Wu YC, Yuan CC, et al. Power Doppler angiographic appearance and blood flow velocity waveforms in invasive cervical carcinoma. Gynecol Oncol 2000;79:181–186. DOI: 10.1006/gyno.2000.5889.

3. Alcazar JL, Castillo G, et al. Intratumoral blood flow in cervical cancer as assessed by transvaginal color Doppler ultrasonography: Correlation with tumor characteristics. Int J Gynecol Cancer 2003;13:510–514. DOI: 10.1136/ijgc-00009577-200307000-00016.

4. Testa AC, Ferrandina G, et al. Color Doppler velocimetry and three-dimensional color power angiography of cervical carcinoma. Ultrasound Obstet Gynecol 2004;24:445–452. DOI: 10.1002/uog.1703.

5. Alcazar JC, Jurado M, et al. Tumor vascularization in cervical cancer by 3-dimensional power Doppler angiography. Correlation with tumor characteristics. Int J Gynecol Cancer 2010;20:393–397. DOI: 10.1111/IGC.0b013e3181d159f9.

6. Belitsos P, Papoutsis D, et al. Three-dimensional power Doppler ultrasound for the study of cervical cancer and precancerous lesions. Ultrasound Obstet Gynecol 2012;40:576–581. DOI: 10.1002/uog.11134.

7. Ito M, AboEllail MAM, et al. HDlive Flow silhouette mode and spatiotemporal image correlation for diagnosing congenital heart disease. Ultrasound Obstet Gynecol 2017;50:411–415. DOI: 10.1002/uog.17519.

8. Hata T, Ito M, et al. HDlive Flow silhouette mode for diagnosis of ectopia cordis with a left ventricular diverticulum at 15 weeks’ gestation. J Ultrasound Med 2018;37(10):2465–2467. DOI: 10.1002/jum.14583.

9. Hata T, Kanenishi K, et al. HDliveFlow silhouette mode for the diagnosis of uterine sarcoma. Donald School J Ultrasound Obstet Gynecol 2017;11:259–260. DOI: 10.5005/jp-journals-10009-1530.

10. Tenkumo C, Kanenishi K, et al. HDliveFlow silhouette mode for the diagnosis of uterine enhanced myometrial vascularity/arteriovenous malformations. J Med Ultrasonics 2018;45:349–352. DOI: 10.1007/s10396-017-0823-4.

11. Hata T, Kanenishi K, et al. HDliveFlow silhouette mode with HDlive silhouette mode for diagnosis of molar pregnancy. Ultrasound Obstet Gynecol 2018;52(4):552–554. DOI: 10.1002/uog.19106.

12. Pecorelli S, Benedet JL, et al. FIGO staging of gynecologic cancer. 1994–1997 FIGO Committee on Gynecologic Oncology. International Federation of Gynecology and Obstetrics. Int J Gynaecol Obstet 1999;64:5–10. DOI: 10.1016/S0020-7292(98)00234-3.

13. Tanaka T, AboEllail MAM, et al. HDliveFlow with HDlive silhouette mode for diagnosis of malignant tumors of uterine cervix. Donald School J Ultrasound Obstet Gynecol 2016;10:409–412. DOI: 10.5005/jp-journals-10009-1493.

14. Kojima A, Mikami Y, et al. Gastric morphology and immunophenotype predict poor outcome in mucinous adenocarcinoma of the uterine cervix. Am J Surg Pathol 2007;31:664–672. DOI: 10.1097/01.pas.0000213434.91868.b0.

15. Karamurzin YS, Kiyokawa T, et al. Gastric-type endocervical adenocarcinoma. An aggressive tumor with unusual metastatic patterns and poor prognosis. Am J Surg Pathol 2015;39:1449–1457. DOI: 10.1097/PAS.0000000000000532.

16. Kojima A, Shimada M, et al. Chemoresistance of gastric-type mucinous carcinoma of the uterine cervix. A study of the Sankai Gynecology Study Group. Int J Gynecol Cancer 2018;28:99–106. DOI: 10.1097/IGC.0000000000001145.

17. Park KJ, Kim MH, et al. Gastric-type adenocarcinoma of the uterine cervix. Magnetic resonance imaging features, clinical outcomes, and prognostic factors. Int J Gynecol Cancer 2018;28(6):1203–1210. DOI: 10.1097/IGC.0000000000001275.