Tumor Vascularity in Renal Masses: Correlation of Arterial Spin-Labeled and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Assessments

doi:10.1016/j.clgc.2015.08.007

Clinical Genitourinary Cancer

Volume 14, Issue 1, February 2016, Pages e25-e36

https://doi.org/10.1016/j.clgc.2015.08.007 Get rights and content

Abstract

Background

The objective of this study was to investigate potential correlations between perfusion using arterial spin-labeled (ASL) magnetic resonance imaging (MRI) and dynamic contrast-enhanced (DCE) MRI-derived quantitative measures of vascularity in renal masses > 2 cm and to correlate these with microvessel density (MVD) in clear cell renal cell carcinoma (ccRCC).

Patients and Methods

Informed written consent was obtained from all patients before imaging in this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, prospective study. Thirty-six consecutive patients scheduled for surgery of a known renal mass > 2 cm underwent 3T ASL and DCE MRI. ASL perfusion measures (P_ASL) of mean, peak, and low perfusion areas within the mass were correlated to DCE-derived volume transfer constant (K^trans), rate constant (Kep), and fractional volume of the extravascular extracellular space (Ve) in the same locations using a region of interest analysis. MRI data were correlated to MVD measures in the same tumor regions in ccRCC. Spearman correlation was used to evaluate the correlation between P_ASL and DCE-derived measurements, and MVD. P < .05 was considered statistically significant.

Results

Histopathologic diagnosis was obtained in 36 patients (25 men; mean age 58 ± 12 years). P_ASL correlated with K^trans (ρ = 0.48 and P = .0091 for the entire tumor and ρ = 0.43 and P = .03 for the high flow area, respectively) and Kep (ρ = 0.46 and P = .01 for the entire tumor and ρ = 0.52 and P = .008 for the high flow area, respectively). P_ASL (ρ = 0.66; P = .0002), K^trans (ρ = 0.61; P = .001), and Kep (ρ = 0.64; P = .0006) also correlated with MVD in high and low perfusion areas in ccRCC.

Conclusion

P_ASL correlated with the DCE-derived measures of vascular permeability and flow, K^trans and Kep, in renal masses > 2 cm in size. Both measures correlated to MVD in clear cell histology.

Introduction

Kidney cancer is among the 10 most common cancers in men and women with more than 65,000 new cases and > 13,000 deaths in the US in 2013.¹ The 3 most common subtypes of renal cell carcinoma (RCC) are clear cell (ccRCC), papillary (pRCC), and chromophobe (chrRCC), which account for 60%-70%, 15%-20%, and 6%-11% of all RCCs, respectively.2, 3 Additionally, renal oncocytomas (ROs) and angiomyolipomas (AMLs) are benign masses that are also commonly observed in clinical practice.⁴ Evaluation of tumor vascularity with magnetic resonance imaging (MRI) has been proposed as a method to characterize renal masses5, 6, 7, 8, 9, 10, 11 and response to treatment in metastatic RCC patients.12, 13, 14

Preliminary studies have shown that MRI can be used to differentiate among the most common histopathologic subtypes of RCC using multiphasic contrast-enhanced MRI protocols consisting of images acquired before and after (typically 2-3 acquisitions) the administration of a bolus of a gadolinium-based contrast agent.10, 11, 15 A more comprehensive quantitative analysis of tumor vascularity can be achieved using dynamic contrast-enhanced (DCE) acquisitions with a higher temporal and lower spatial resolution with subsequent analysis of these imaging data sets with pharmacokinetic models such as the one proposed by Tofts and Kermode.¹⁶ Quantitative parametric maps can be then generated such as those for the volume transfer constant (K^trans), the rate constant (Kep), and the fractional volume of the extravascular extracellular (Ve) and vascular (Vp) space.16, 17 However, direct measurement of tumor perfusion using DCE MRI is challenging because of the unknown relative contributions of blood flow and vascular permeability to tissue enhancement.¹⁸

Arterial spin-labeled (ASL) MRI provides a means to determine tissue perfusion (in mL per minute per 100 g of tissue) without injection of contrast agents.19, 20, 21, 22, 23 With ASL MRI, the arterial blood is used as an endogenous contrast, by virtue of magnetic labeling of the blood before entering the tissue of interest with radiofrequency pulses and gradient fields.24, 25 The tissue signal intensity difference between images acquired with and without arterial labeling is proportional to the perfusion in the tissue (ie, blood flow). Advantages of ASL MRI as a quantitative technique include the lack of contrast administration and the virtually negligible contribution of vascular permeability to the measurements of tissue perfusion.²⁶ Furthermore, this technique has been validated in animals using microspheres²⁷ and in the normal human brain using H₂O¹⁵ positron emission tomography.²⁸ In a previous study the feasibility of characterization of renal masses using a pseudo-continuous ASL (pCASL) acquisition at 1.5T was reported.⁵ However, the sensitivity of ASL MRI for detecting low levels of perfusion (ie, < 50 mL/100 g/min) in renal masses was limited.⁵

A noninvasive method to measure tumor vascularity in renal masses could be valuable, for example, in the longitudinal follow-up of small renal masses during active surveillance. However, despite the existing literature that has proposed DCE-MRI and ASL MRI approaches to measure tumor vascularity in RCC, these techniques provide different measures related to the intrinsic vascular characteristics of the tumor. Specifically, ASL MRI offers a measure of tissue perfusion whereas DCE-derived parametric maps such as K^trans and Kep are a product of tumor vascular permeability and blood flow. To our knowledge, the potential relationship between these measurements and their correlation with tumor histology and vascularity measurements at pathology has not been reported. The latter would be particularly relevant in ccRCC because: (1) the known relationship between the molecular alterations in the Von Hippel–Lindau-hypoxia inducible factor pathway and tumor angiogenesis in this histologic subtype²⁹; (2) the relationship between tumor vascularity and tumor aggressiveness and potential to metastasize30, 31, 32; and (3) the characteristic heterogeneity of ccRCC.³³

The purpose of this study was twofold: (1) to investigate potential correlations between the measurements of tumor perfusion in renal masses > 2 cm in size using ASL MRI and the quantitative measures of vascularity derived from DCE MRI; and (2) to correlate these measures with microvessel density (MVD) in ccRCC.

Section snippets

Patient Population

The institutional review board approved this Health Insurance Portability and Accountability Act-compliant prospective study. Written informed consent was obtained from all patients before imaging. Between January 2012 and February 2014, 36 consecutive patients (25 men, 11 women; mean age ± SD, 58 ± 12 years) scheduled for surgical resection of a known renal mass participated in this study. Exclusion criteria comprised inability to undergo an MRI examination (eg, known unsafe indwelling device,

Results

Thirty-six patients with 36 masses were enrolled in this study. One patient with an LG ccRCC ended the MRI examination after the ASL acquisition and was excluded from the ASL/DCE correlation analysis. The mean maximum tumor diameter was 5.3 ± 2.4 cm and did not differ among different tumor types (P = .22; Table 1).

Discussion

The development of new blood vessels (ie, angiogenesis) has been linked to the ability of ccRCC, the most common malignant tumor of the kidney, to grow and metastasize.31, 32 A quantitative, noninvasive measure of tumor vascularity could have different clinical applications including the assessment of tumor biology in patients who undergo active surveillance. Similarly, the assessment of tumor vascularity with ASL and DCE MRI approaches appear to have promise in the assessment of tumor response

Conclusion

Arterial spin-labeled perfusion quantifications showed significant correlation with DCE-derived measures of tumor vascularity such as K^trans and Kep. This correlation was, however, moderate, likely because of intrinsic differences in the vascular measures provided by these techniques. ASL and DCE-derived analyses correlated with histopathologic MVD measures, which supports the use of these techniques for the noninvasive assessment of tumor vascularity in vivo in renal masses > 2 cm in size.

Disclosure

Ivan Dimitrov is an employee of Phillip Healthcare. Naira Muradyan is an employee of iCAD. The remaining authors have stated that they have no conflicts of interest.

Acknowledgments

NIH RO1 Grant R01CA154475.

References (50)

D.J. Waters et al.
Unilateral simultaneous renal angiomyolipoma and oncocytoma
J Urol
(1986)
K.D. Mertz et al.
Automated immunofluorescence analysis defines microvessel area as a prognostic parameter in clear cell renal cell cancer
Hum Pathol
(2007)
Cancer Facts & Figures 2013
(2013)
J.C. Cheville et al.
Comparisons of outcome and prognostic features among histologic subtypes of renal cell carcinoma
Am J Surg Pathol
(2003)
S. Durinck et al.
Spectrum of diverse genomic alterations define non-clear cell renal carcinoma subtypes
Nat Genet
(2015)
R.S. Lanzman et al.
Arterial spin-labeling MR imaging of renal masses: correlation with histopathologic findings
Radiology
(2012)
V. Masarapu et al.
Initial experience with arterial spin-labeling MR imaging to assess histology of renal masses
Quant Imaging Med Surg
(2013)
I. Pedrosa et al.
Arterial spin labeling MR imaging for characterisation of renal masses in patients with impaired renal function: initial experience
Eur Radiol
(2012)
K. Sasiwimonphan et al.
Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging
Radiology
(2012)
M. Scialpi et al.
Small renal masses: assessment of lesion characterization and vascularity on dynamic contrast-enhanced MR imaging with fat suppression
AJR Am J Roentgenol
(2000)

M.R. Sun et al.

Renal cell carcinoma: dynamic contrast-enhanced MR imaging for differentiation of tumor subtypes–correlation with pathologic findings

Radiology

(2009)

H. Chandarana et al.

Histogram analysis of whole-lesion enhancement in differentiating clear cell from papillary subtype of renal cell cancer

Radiology

(2012)

C. de Bazelaire et al.

Magnetic resonance imaging-measured blood flow change after antiangiogenic therapy with PTK787/ZK 222584 correlates with clinical outcome in metastatic renal cell carcinoma

Clin Cancer Res

(2008)

K.T. Flaherty et al.

Pilot study of DCE-MRI to predict progression-free survival with sorafenib therapy in renal cell carcinoma

Cancer Biol Ther

(2008)

O.M. Hahn et al.

Dynamic contrast-enhanced magnetic resonance imaging pharmacodynamic biomarker study of sorafenib in metastatic renal carcinoma

J Clin Oncol

(2008)

N. Campbell et al.

MRI phenotype in renal cancer: is it clinically relevant?

Top Magn Reson Imaging

(2014)

P.S. Tofts et al.

Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts

Magn Reson Med

(1991)

P.S. Tofts

Modeling tracer kinetics in dynamic Gd-DTPA MR imaging

J Magn Reson Imaging

(1997)

D.L. Buckley

Uncertainty in the analysis of tracer kinetics using dynamic contrast-enhanced T1-weighted MRI

Magn Reson Med

(2002)

D.A. Roberts et al.

Renal perfusion in humans: MR imaging with spin tagging of arterial water

Radiology

(1995)

L. Maccotta et al.

The efficiency of adiabatic inversion for perfusion imaging by arterial spin labeling

NMR Biomed

(1997)

D.C. Alsop et al.

Multisection cerebral blood flow MR imaging with continuous arterial spin labeling

Radiology

(1998)

M. Fenchel et al.

Perfusion MR imaging with FAIR true FISP spin labeling in patients with and without renal artery stenosis: initial experience

Radiology

(2006)

R.S. Lanzman et al.

Quantification of renal allograft perfusion using arterial spin labeling MRI: initial results

Eur Radiol

(2010)

J.A. Detre et al.

Perfusion imaging

Magn Reson Med

(1992)

Cited by (43)

On the application of pseudo-continuous arterial spin labeled MRI for pulmonary perfusion imaging
2023, Magnetic Resonance Imaging
To evaluate different approaches for the effective assessment of pulmonary perfusion with a pseudo-continuous arterial spin labeled (pCASL) MRI.
Four different approaches were evaluated: 1) Cardiac-triggered inferior vena cava (IVC) labeling; 2) IVC labeling with cardiac-triggered acquisition; 3) Right pulmonary artery (RPA) labeling with cardiac-triggered acquisition; and 4) Cardiac-triggered RPA labeling with background suppression (BGS). Each approach was evaluated in 5 healthy volunteers (n = 20) using coefficient of variation (COV) across averages. Approach 4 was also compared against a flow alternating inversion recovery (FAIR).
The IVC labeling (Approach 1) achieved perfusion-weighted images of both lungs, although this approach was more sensitive to variations in heart rate. Cardiac-triggered acquisitions using IVC (Approach 2) and RPA (Approach 3) labeling improved signal consistencies, but were incompatible with BGS. The cardiac-triggered RPA labeling with BGS (Approach 4) achieved a COV of 0.34 ± 0.03 (p < 0.05 compared to IVC labeling approaches) and resulted in perfusion value of 434 ± 64 mL/100 g/min, which was comparable to 451 ± 181 mL/100 g/min measured by FAIR (p = 0.82).
Pulmonary perfusion imaging using pCASL-MRI is highly sensitive to cardiac phase, and requires approaches to minimize flow-induced signal variations. Cardiac-triggered RPA labeling with BGS achieves reduced COV and enables robust pulmonary perfusion imaging.
Magnetic Resonance Imaging Radiomics Analyses for Prediction of High-Grade Histology and Necrosis in Clear Cell Renal Cell Carcinoma: Preliminary Experience
2021, Clinical Genitourinary Cancer
Percutaneous renal mass biopsy results can accurately diagnose clear cell renal cell carcinoma (ccRCC); however, their reliability to determine nuclear grade in larger, heterogeneous tumors is limited. We assessed the ability of radiomics analyses of magnetic resonance imaging (MRI) to predict high-grade (HG) histology in ccRCC.
Seventy patients with a renal mass underwent 3 T MRI before surgery between August 2012 and August 2017. Tumor length, first-order statistics, and Haralick texture features were calculated on T2-weighted and dynamic contrast-enhanced (DCE) MRI after manual tumor segmentation. After a variable clustering algorithm was applied, tumor length, washout, and all cluster features were evaluated univariably by receiver operating characteristic curves. Three logistic regression models were constructed to assess the predictability of HG ccRCC and then cross-validated.
At univariate analysis, area under the curve values of length, and DCE texture cluster 1 and cluster 3 for diagnosis of HG ccRCC were 0.7 (95% confidence interval [CI], 0.58-0.82, false discovery rate P = .008), 0.72 (95% CI, 0.59-0.84, false discovery rate P = .004), and 0.75 (95% CI, 0.63-0.87, false discovery rate P = .0009), respectively. At multivariable analysis, area under the curve for model 1 (tumor length only), model 2 (length + DCE clusters 3 and 4), and model 3 (DCE cluster 1 and 3) for diagnosis of HG ccRCC were 0.67 (95% CI, 0.54-0.79), 0.82 (95% CI, 0.71-0.92), and 0.81 (95% CI, 0.70-0.91), respectively.
Radiomics analysis of MRI images was superior to tumor size for the prediction of HG histology in ccRCC in our cohort.
Radiomics in Kidney Cancer: MR Imaging
2019, Magnetic Resonance Imaging Clinics of North America
Investigating the correlation of arterial spin labeling and dynamic contrast enhanced perfusion in primary tumor of nasopharyngeal carcinoma
2018, European Journal of Radiology
Citation Excerpt :
In the previous studies [15,37], the correlation of TBF and DCE-MRI varied among different regions of tumor due to the heterogeneous vascularity within tumor. Study on HNSCC showed higher correlation level observed in peripheral (r = 0.70) and relatively lower correlation level in central (r = 0.65) [15], and another study on clear cell renal cell carcinoma (ccRCC) showed that BF by ASL correlated with Ktrans of the entire tumor (r = 0.48) and that of high perfusion area (r = 0.43), respectively [37]. The heterogeneity of perfusion property observed among tumors indicates that the location of ROI drawn on tumor may impact the level of correlation detected.
This prospective study aimed to investigate the correlation between two perfusion methods: arterial spin labeling (ASL) and dynamic contrast enhanced (DCE) technique in patients with nasopharyngeal carcinoma (NPC) and to optimize ASL protocol.
Forty-five newly diagnosed NPC patients underwent MR examinations with both 3D pseudo-continuous ASL (pCASL) and DCE-MRI sequences. Tumor blood flow (TBF) derived in pCASL with three post-labeling delay (PLD) times (i.e. 1.0 s, 1.5 s, and 2.0 s) and DCE derived parameters including MaxSlop, contrast enhancement ratio (CER), Initial area under the gadolinium curve (IAUGC), K^trans, K_ep and V_e were measured by two independent observers, and their correlation coefficients were investigated using Spearman test.
Inter-observer reproducibility (ICC = 0.931–0.998) was observed to be excellent. Positive correlations between mean, maximum and minimum value of TBFs with different PLDs and DCE-MRI parameters (except V_e) were respectively observed (r = 0.308–0.688, P = 0.000–0.040).
pCASL may be an alternative method for DCE-MRI in assessing the perfusion level in NPC in the future.
Imaging of Solid Renal Masses
2018, Urologic Clinics of North America
Fundamentals of functional imaging II: emerging MR techniques and new methods of analysis
2018, Radiologia
La resonancia magnética (RM) integra en los protocolos multiparamétricos clínicos actuales información estructural, fisiológica y metabólica del cáncer. Existen técnicas emergentes, como ASL, BOLD, RM elastografía, CEST e hiperpolarización, que aportan un nuevo tipo de información y que están cerca de su integración en la clínica diaria. Además, existe un gran interés en el estudio de la heterogeneidad tumoral con imagen como factor pronóstico y de resistencia al tratamiento. Para ello, se están aplicando nuevos métodos de análisis de los protocolos multiparamétricos, y a su vez se están desarrollando nuevos biomarcadores oncológicos integrando la información de la RM con los datos clínicos, analíticos, genéticos e histológicos, gracias a la aplicación del big data y la inteligencia artificial. En esta revisión se analizan varias técnicas emergentes de RM que permiten evaluar las características fisiológicas, metabólicas y mecánicas del cáncer, así como sus principales aplicaciones clínicas. Además, se resumen los métodos de análisis más novedosos de la información radiológica funcional en oncología.
Current multiparameter MRI protocols integrate structural, physiological, and metabolic information about cancer. Emerging techniques such as arterial spin-labeling (ASL), blood oxygen level dependent (BOLD), MR elastography, chemical exchange saturation transfer (CEST), and hyperpolarization provide new information and will likely be integrated into daily clinical practice in the near future. Furthermore, there is great interest in the study of tumor heterogeneity as a prognostic factor and in relation to resistance to treatment, and this interest is leading to the application of new methods of analysis of multiparametric protocols. In parallel, new oncologic biomarkers that integrate the information from MR with clinical, laboratory, genetic, and histologic findings are being developed, thanks to the application of big data and artificial intelligence. This review analyzes different emerging MR techniques that are able to evaluate the physiological, metabolic, and mechanical characteristics of cancer, as well as the main clinical applications of these techniques. In addition, it summarizes the most novel methods of analysis of functional radiologic information in oncology.

View all citing articles on Scopus

View full text

Original StudyTumor Vascularity in Renal Masses: Correlation of Arterial Spin-Labeled and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Assessments

Abstract

Background

Patients and Methods

Results

Conclusion

Introduction

Section snippets

Patient Population

Results

Discussion

Conclusion

Disclosure

Acknowledgments

J Urol

Hum Pathol

Cancer Facts & Figures 2013

Comparisons of outcome and prognostic features among histologic subtypes of renal cell carcinoma

Am J Surg Pathol

Spectrum of diverse genomic alterations define non-clear cell renal carcinoma subtypes

Nat Genet

Arterial spin-labeling MR imaging of renal masses: correlation with histopathologic findings

Radiology

Initial experience with arterial spin-labeling MR imaging to assess histology of renal masses

Quant Imaging Med Surg

Arterial spin labeling MR imaging for characterisation of renal masses in patients with impaired renal function: initial experience

Eur Radiol

Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging

Radiology

Small renal masses: assessment of lesion characterization and vascularity on dynamic contrast-enhanced MR imaging with fat suppression

AJR Am J Roentgenol

Renal cell carcinoma: dynamic contrast-enhanced MR imaging for differentiation of tumor subtypes–correlation with pathologic findings

Radiology

Histogram analysis of whole-lesion enhancement in differentiating clear cell from papillary subtype of renal cell cancer

Radiology

Magnetic resonance imaging-measured blood flow change after antiangiogenic therapy with PTK787/ZK 222584 correlates with clinical outcome in metastatic renal cell carcinoma

Clin Cancer Res

Pilot study of DCE-MRI to predict progression-free survival with sorafenib therapy in renal cell carcinoma

Cancer Biol Ther

Dynamic contrast-enhanced magnetic resonance imaging pharmacodynamic biomarker study of sorafenib in metastatic renal carcinoma

J Clin Oncol

MRI phenotype in renal cancer: is it clinically relevant?

Top Magn Reson Imaging

Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts

Magn Reson Med

Modeling tracer kinetics in dynamic Gd-DTPA MR imaging

J Magn Reson Imaging

Uncertainty in the analysis of tracer kinetics using dynamic contrast-enhanced T1-weighted MRI

Magn Reson Med

Renal perfusion in humans: MR imaging with spin tagging of arterial water

Radiology

The efficiency of adiabatic inversion for perfusion imaging by arterial spin labeling

NMR Biomed

Multisection cerebral blood flow MR imaging with continuous arterial spin labeling

Radiology

Perfusion MR imaging with FAIR true FISP spin labeling in patients with and without renal artery stenosis: initial experience

Radiology

Quantification of renal allograft perfusion using arterial spin labeling MRI: initial results

Eur Radiol

Perfusion imaging

Magn Reson Med

Original Study
Tumor Vascularity in Renal Masses: Correlation of Arterial Spin-Labeled and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Assessments