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Decreased capillary density in renal cell carcinoma

Evidence from a case report with micro-computerized tomography

Lin, Tzu-Chun MDa,b,c; Chen, Huey-Yi MD, PhDa,d; Yang, You-Rong MDd; Liu, Po-Len PhDe; Chen, Yung-Hsiang PhDa,d,f,*; Chen, Wen-Chi MD, PhDa,d,*

Section Editor(s): NA.,

doi: 10.1097/MD.0000000000016910
Research Article: Clinical Case Report
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Rationale: Conventional computerized tomography (CT) examination can differentiate renal cortical tumor from urothelial carcinoma on the basis of the highly contrast-enhanced vessels in renal cortical tumors. However, the capillary distribution of renal cell carcinoma (RCC) has been under-investigated. Here, we present a micro-CT image of tumor tissue in a patient with RCC.

Patient concerns: The patient was a 72-year-old woman with a past history of diabetes mellitus and hypertension. She did not have tumor-related symptoms.

Diagnosis and interventions: The tumor was diagnosed using abdominal CT during her yearly routine health check. After radical nephrectomy, the tumor was subjected to pathological examination and micro-CT imaging. Pathological analysis confirmed a clear cell renal carcinoma. The capillary distribution of the tumor was significantly lesser than that of the normal cortex on micro-CT image.

Lessons: Microvessels of RCC can be detected by micro-CT. We also found that the distribution of microvessels was uneven and lower than that in the normal cortex in this case. For a more general diagnosis, more micro-CT images of RCC tumors are needed.

aGraduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University

bDepartment of Dermatology, Chung Shan Medical University Hospital

cInstitute of Medicine, School of Medicine, Chung Shan Medical University

dDepartments of Obstetrics and Gynecology, Urology, and Medical Research, China Medical University Hospital, Taichung

eDepartment of Respiratory Therapy, College of Medicine, Kaohsiung Medical University, Kaohsiung

fDepartment of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan.

Correspondence: Yung-Hsiang Chen, China Medical University, No. 91, Hsueh-Shih Road, Taichung 40402, Taiwan (e-mail: yhchen@mail.cmu.edu.tw); Wen-Chi Chen, China Medical University, No. 91, Hsueh-Shih Road, Taichung 40402, Taiwan (e-mail: wgchen@mail.cmu.edu.tw).

Abbreviations: CT = computerized tomography, OV = object volume, RCC = renal cell carcinoma, TV = total VOI volume of whole sample.

How to cite this article: Lin TC, Chen HY, Yang YR, Liu PL, Chen YH, Chen WC. Decreased capillary density in renal cell carcinoma. Medicine 2019;98:36(e16910).

The authors alone are responsible for the content and writing of the paper.

Informed written consent was obtained from the patient for publication of this case report and accompanying images.

This study is supported in part by China Medical University (CMU106-S-32) and Taiwan Ministry of Science and Technology (MOST 107-2314-B-039-036 and MOST 107-2320-B-039-034).

The authors have no conflicts of interest to disclose.

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Received December 17, 2018

Received in revised form June 24, 2019

Accepted July 29, 2019

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0

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1 Introduction

Clear cell type renal cell carcinoma (RCC) is the most frequently seen renal malignancy.[1,2] Some of the highly vascularized tumors respond to targeted antiangiogenic therapy.[3] However, some do not, owing to the complexity of the vasculature. The prognosis may be correlated to the differentiation of vessels: undifferentiated vasculature shows a poorer prognosis than highly differentiated vasculature.[3] Qian studied the microvessel density of tumors and found that the uneven pericyte coverage in clear cell RCC indicates a poor prognosis.[4] A positron emission tomography study showed that blood perfusion is reduced in RCC when compared with normal renal tissue.[5] However, a meta-analysis of the prognostic role of microvessel density in patients with RCC by Cheng et al found that microvessel density is not reliably associated with the survival time of the patients, but survival time depends on vessel differentiation.[6] The factor responsible for the unreliability of microvessel density as a prognostic factor may be the uneven distribution of microvessels. Although microvessel density is not a reliable prognostic factor, imaging diagnosis of RCC is still based on detecting its highly vascularized structure by enhanced contrast computerized tomography (CT).

We performed micro-CT for the study of small animals. On micro-CT scanning of the fruit fly's Malphigian tubules, small crystals can be viewed and measured.[7] The aim of this study is to apply micro-CT to investigate the distribution of microvessels in patients with clear cell type RCC.

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2 Case report

A kidney sample was obtained from a patient with RCC suspected on CT before surgery (Fig. 1A and B). The patient was a 72-year-old woman with a past history of diabetes mellitus and hypertension. The tumor was found during her yearly routine health check; she had not yet presented clinical symptoms. After radical nephrectomy, a 1 cm3 sample was excised from the tumor side along the calyx. A same-sized sample was also excised from a grossly normal cortex. Each sample was stored in a formaldehyde solution for subsequent examination. The kidney was submitted for pathological analysis.

Figure 1

Figure 1

The 2 samples were incubated for 2 hours each in 70%, 80%, and 90% ethanol and then overnight in 100% ethanol. The samples were subsequently transferred to 100% hexamethyldisilazane for a further 2 hours, before air-drying. Two samples (control and tumor, http://links.lww.com/MD/D209) were prepared for further scanning by micro-CT. A Bruker Skyscan 1272 (Kontich, Belgium) was used to scan the samples at 1.8-μm resolution. CT scanning of the control and tumor samples was performed at 40 kVp voltage, 250 μA current, and 1000 ms exposure time, without a filter. The rotation step was 0.1 per image, 3 images were averaged. Reconstruction of sections was carried out using GPU-based scanner software (NRecon).

Specific regions of interest were selected using DataViewer (Skyscan) for further analysis and illustration. CT-analyzer (Skyscan) was used to analyze the object volume (OV) and 3D morphometric indices. CTVox (Version 3.0, Skyscan) was used to provide 3D images. The grey threshold of the capillaries was set in a range of 90 to 255 on the tumor and normal cortex according to the morphology on micro-CT. We calculated the total volume of image volume of the whole sample (TV) and the OV of capillaries with diameters from 5 to 10 microns.[8] The percentage of vessels in each sample was defined as OV/TV. The distributions of capillaries in the tumor and normal cortex can, therefore, be compared.

Pathological analysis confirmed a clear cell type of RCC, Fuhrman's grade 2 (Fig. 2A and B). Micro-CT images of the normal and tumor cortices, labeled in red (120–255, scale bar = 250 μm), are shown in Figure 3.

Figure 2

Figure 2

Figure 3

Figure 3

We compared the distribution percentages of total capillaries in the tumor and normal cortices in a range of 120 to 255 (Table 1 and Fig. 4). There was a large decrease in capillary distribution in the tumor cortex – (0.044%) compared with the normal cortex (2.729%). An uneven distribution of microvessles was also noted in tumor tissue. There were areas of high and low capillary density. The patient is under regular follow-up on an outpatient basis, and no local recurrence or metastasis has been found on CT examination.

Table 1

Table 1

Figure 4

Figure 4

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3 Discussion

We found a marked decrease in capillary distribution in RCC on micro-CT image analysis. The capillary distribution in the tumor was 0.044% of the total volume, which was much lower than that in the normal renal cortex (2.73%). The lack of blood perfusion may be a tumor mass effect and therefore may be a cause of tumor necrosis. A subsequent event is high vascular endothelial growth factor expression in the tumor via the paracrine system.[9] The primary treatment for our patient was radical nephrectomy without targeted therapy. Therefore, RCC can be clinically diagnosed using CT imaging on the basis of a high vascular density. However, a lower density of capillary vessels was evident on micro-CT imaging. The capillary density was difficult to identify on abdominal CT.

The diagnosis of RCC relies on the vascularity seen in a tumor image obtained from abdominal CT, and this is a well-known diagnostic tool.[10] Like nephroureterectomy for the removal of renal urothelial cell carcinoma, which is highly prevalent in Taiwan, radical nephrectomy is indicated for RCC.[11] Therefore, a preoperative imaging study is very important for choosing the surgical treatment. The cell pathology is also important for the prediction of tumor prognosis and for planning further treatment.[12] The highly vascularized tumors of RCC can be treated by targeted therapy because of their highly expressed vascular endothelial growth factor receptor when the tumor has metastasized.[13] The relationship between low capillary distribution on the tumor and metastasis remains unknown. As our patient did not under targeted therapy, the clinical effect of targeted therapy on a lower capillary volume tumor is unclear. We suggest a further study on the response to targeted therapy on the basis of capillary distribution.

The uneven distribution of microvessels in the tumor indicates that predicting prognosis by density maybe not be reliable. In our patient, both high- and low-density microvessels coexisted in the tumor tissue. Therefore, predicting the prognosis using the density of microvessels might be difficult.

The resolution of micro-CT in this study was higher than that of micro-CT for progressive kidney disease. This study had a resolution of 1800 nm (1.8 μm), based on density. This resolution can be used to identify microvessels with a capillary diameter of 5 to 10 μm.[14]

There is evidence of less vascularity and uneven distribution of RCC tumor microvessles found from micro-CT. Limitations of this study are that it is a single case report with small area scanning and limited cell type. However, to our best knowledge, this is the first survey of capillary distribution of RCC using micro-CT.

In conclusion, we found that the distribution of microvessels was uneven and lower than that in the normal cortex by micro-CT. Because treatment for advanced RCC is based on vascularity in the majority of targeted therapies, the result of this imaging study may provide direction for the study of the poor response to targeted therapy in advanced RCC.

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Author contributions

Conceptualization: Huey-Yi Chen, Wen-Chi Chen.

Data curation: Yung-Hsiang Chen, Wen-Chi Chen.

Formal analysis: Huey-Yi Chen, Yung-Hsiang Chen, Wen-Chi Chen.

Funding acquisition: Wen-Chi Chen.

Investigation: Tzu-Chun Lin, Huey-Yi Chen, You-Rong Yang, Po-Len Liu, Yung-Hsiang Chen, Wen-Chi Chen.

Methodology: Tzu-Chun Lin, Huey-Yi Chen, You-Rong Yang, Yung-Hsiang Chen, Wen-Chi Chen.

Project administration: Wen-Chi Chen.

Resources: Wen-Chi Chen.

Supervision: Yung-Hsiang Chen, Wen-Chi Chen.

Validation: Tzu-Chun Lin, Po-Len Liu, Yung-Hsiang Chen, Wen-Chi Chen.

Writing – original draft: Wen-Chi Chen.

Writing – review and editing: Yung-Hsiang Chen, Wen-Chi Chen.

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References

[1]. Shen Z, Yang C, Bao X, et al. Giant sellar metastasis from renal cell carcinoma: a case report and literature review. Medicine (Baltimore) 2018;97:e13376.
[2]. Zahoor H, Pavicic PG Jr, Przybycin C, et al. Evaluation of T cell infiltration in matched biopsy and nephrectomy samples in renal cell carcinoma. Medicine (Baltimore) 2018;97:e12344.
[3]. Ferda J, Hora M, Hes O, et al. Assessment of the kidney tumor vascular supply by two-phase MDCT-angiography. Eur J Radiol 2007;62:295–301.
[4]. Qian CN, Huang D, Wondergem B, et al. Complexity of tumor vasculature in clear cell renal cell carcinoma. Cancer 2009;115:2282–9.
[5]. Anderson H, Yap JT, Wells P, et al. Measurement of renal tumour and normal tissue perfusion using positron emission tomography in a phase II clinical trial of razoxane. Br J Cancer 2003;89:262–7.
[6]. Cheng SH, Liu JM, Liu QY, et al. Prognostic role of microvessel density in patients with renal cell carcinoma: a meta-analysis. Int J Clin Exp Pathol 2014;7:5855–63.
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[8]. Hill CA, Richtsmeier JT. A quantitative method for the evaluation of three-dimensional structure of temporal bone pneumatization. J Hum Evol 2008;55:682–90.
[9]. Nicol D, Hii SI, Walsh M, et al. Vascular endothelial growth factor expression is increased in renal cell carcinoma. J Urol 1997;157:1482–6.
[10]. Sunela KL, Lehtinen ET, Kataja MJ, et al. Development of renal cell carcinoma (RCC) diagnostics and impact on prognosis. BJU Int 2014;113:228–35.
[11]. Mirza KM, Taxy JB, Antic T. Radical nephrectomy for renal cell carcinoma: its contemporary role related to histologic type, tumor size, and nodal status: a retrospective study. Am J Clin Pathol 2016;145:837–42.
[12]. Hsieh JJ, Purdue MP, Signoretti S, et al. Renal cell carcinoma. Nat Rev Dis Primers 2017;3:17009.
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Keywords:

capillary distribution; micro-computerized tomography; renal cell carcinoma

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