The value of blood oxygenation level-dependent (BOLD) MR imaging in differentiation of renal solid mass and grading of renal cell carcinoma (RCC): analysis based on the largest cross-sectional area versus the entire whole tumour

High-resolution and highly accelerated MRI T2 mapping as a tool to characterise renal tumour subtypes and grades

BACKGROUND

Clinical imaging tools to probe aggressiveness of renal masses are lacking, and T2-weighted imaging as an integral part of magnetic resonance imaging protocol only provides qualitative information. We developed high-resolution and accelerated T2 mapping methods based on echo merging and using k-t undersampling and reduced flip angles (TEMPURA) and tested their potential to quantify differences between renal tumour subtypes and grades.

METHODS

Twenty-four patients with treatment-naïve renal tumours were imaged: seven renal oncocytomas (RO); one eosinophilic/oncocytic renal cell carcinoma; two chromophobe RCCs (chRCC); three papillary RCCs (pRCC); and twelve clear cell RCCs (ccRCC). Median, kurtosis, and skewness of T2 were quantified in tumours and in the normal-adjacent kidney cortex and were compared across renal tumour subtypes and between ccRCC grades.

RESULTS

High-resolution TEMPURA depicted the tumour structure at improved resolution compared to conventional T2-weighted imaging. The lowest median T2 values were present in pRCC (high-resolution, 51 ms; accelerated, 45 ms), which was significantly lower than RO (high-resolution; accelerated, p = 0.012) and ccRCC (high-resolution, p = 0.019; accelerated, p = 0.008). ROs showed the lowest kurtosis (high-resolution, 3.4; accelerated, 4.0), suggestive of low intratumoural heterogeneity. Lower T2 values were observed in higher compared to lower grade ccRCCs (grades 2, 3 and 4 on high-resolution, 209 ms, 151 ms, and 106 ms; on accelerated, 172 ms, 160 ms, and 102 ms, respectively), with accelerated TEMPURA showing statistical significance in comparison (p = 0.037).

CONCLUSIONS

Both high-resolution and accelerated TEMPURA showed marked potential to quantify differences across renal tumour subtypes and between ccRCC grades.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03741426 . Registered on 13 November 2018.

RELEVANCE STATEMENT

The newly developed T2 mapping methods have improved resolution, shorter acquisition times, and promising quantifiable readouts to characterise incidental renal masses.

Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization

Solid renal masses (SRMs) are increasingly detected and encompass both benign and malignant masses, with renal cell carcinoma (RCC) being the most common malignant SRM. Most patients with SRMs will undergo management without a priori pathologic confirmation. There is an unmet need to noninvasively diagnose and characterize RCCs, as significant variability in clinical behavior is observed and a wide range of differing management options exist. Cross-sectional imaging modalities, including magnetic resonance imaging (MRI), are increasingly used for SRM characterization. Multiparametric (mp) MRI techniques can provide insight into tumor biology by probing different physiologic/pathophysiologic processes noninvasively. These include sequences that probe tissue microstructure, including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and T₁ relaxometry; oxygen metabolism (blood oxygen level dependent [BOLD-MRI]); as well as vascular flow and perfusion (dynamic contrast-enhanced MRI [DCE-MRI] and arterial spin labeling [ASL]). In this review, we will discuss each mpMRI method in terms of its principles, roles, and discuss the results of human studies for SRM assessment. Future validation of these methods may help to enable a personalized management approach for patients with SRM in the emerging era of precision medicine. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: 2.

EARLY ASSESSMENT OF RENAL TRANSPLANTS USING BOLD-MRI: PROMISING RESULTS

Non-invasive evaluation of renal transplant function is essential to minimize and manage renal rejection. A computer-assisted diagnostic (CAD) system was developed to evaluate kidney function post-transplantation. The developed CAD system utilizes the amount of blood-oxygenation extracted from 3D (2D + time) blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) to estimate renal function. BOLD-MRI scans were acquired at five different echo-times (2, 7, 12, 17, and 22) ms from 15 transplant patients. The developed CAD system first segments kidneys using the level-sets method followed by estimation of the amount of deoxyhemoglobin, also known as apparent relaxation rate (R2*). These R2* estimates were used as discriminatory features (global features (mean R2*) and local features (pixel-wise R2*)) to train and test state-of-the-art machine learning classifiers to differentiate between non-rejection (NR) and acute renal rejection. Using a leave-one-out cross-validation approach along with an artificial neural network (ANN) classifier, the CAD system demonstrated 93.3% accuracy, 100% sensitivity, and 90% specificity in distinguishing AR from non-rejection . These preliminary results demonstrate the efficacy of the CAD system to detect renal allograft status non-invasively.

How rapid advances in imaging are defining the future of precision radiation oncology

Imaging has an essential role in the planning and delivery of radiotherapy. Recent advances in imaging have led to the development of advanced radiotherapy techniques—including image-guided radiotherapy, intensity-modulated radiotherapy, stereotactic body radiotherapy and proton beam therapy. The optimal use of imaging might enable higher doses of radiation to be delivered to the tumour, while sparing normal surrounding tissues. In this article, we review how the integration of existing and novel forms of computed tomography, magnetic resonance imaging and positron emission tomography have transformed tumour delineation in the radiotherapy planning process, and how these advances have the potential to allow a more individualised approach to the cancer therapy. Recent data suggest that imaging biomarkers that assess underlying tumour heterogeneity can identify areas within a tumour that are at higher risk of radio-resistance, and therefore potentially allow for biologically focussed dose escalation. The rapidly evolving concept of adaptive radiotherapy, including artificial intelligence, requires imaging during treatment to be used to modify radiotherapy on a daily basis. These advances have the potential to improve clinical outcomes and reduce radiation-related long-term toxicities. We outline how recent technological advances in both imaging and radiotherapy delivery can be combined to shape the future of precision radiation oncology.

Experimental imaging in orthotopic renal cell carcinoma xenograft models: comparative evaluation of high-resolution 3D ultrasonography, in-vivo micro-CT and 9.4T MRI

In this study, we aimed to comparatively evaluate high-resolution 3D ultrasonography (hrUS), in-vivo micro-CT (μCT) and 9.4T MRI for the monitoring of tumor growth in an orthotopic renal cell carcinoma (RCC) xenograft model since there is a lack of validated, non-invasive imaging tools for this purpose. 1 × 10⁶ Caki-2 RCC cells were implanted under the renal capsule of 16 immunodeficient mice. Local and systemic tumor growth were monitored by regular hrUS, μCT and MRI examinations. Cells engrafted in all mice and gave rise to exponentially growing, solid tumors. All imaging techniques allowed to detect orthotopic tumors and to precisely calculate their volumes. While tumors appeared homogenously radiolucent in μCT, hrUS and MRI allowed for a better visualization of intratumoral structures and surrounding soft tissue. Examination time was the shortest for hrUS, followed by μCT and MRI. Tumor volumes determined by hrUS, μCT and MRI showed a very good correlation with each other and with caliper measurements at autopsy. 10 animals developed pulmonary metastases being well detectable by μCT and MRI. In conclusion, each technique has specific strengths and weaknesses, so the one(s) best suitable for a specific experiment may be chosen individually.

Multiparametric magnetic resonance imaging in mucosal primary head and neck cancer: a prospective imaging biomarker study

BACKGROUND

Radical radiotherapy, with or without concomitant chemotherapy forms the mainstay of organ preservation approaches in mucosal primary head and neck cancer. Despite technical advances in cancer imaging and radiotherapy administration, a significant proportion of patients fail to achieve a complete response to treatment. For those patients who do achieve a complete response, acute and late toxicities remain a cause of morbidity. A critical need therefore exists for imaging biomarkers which are capable of informing patient selection for both treatment intensification and de-escalation strategies.

METHODS/DESIGN

A prospective imaging study has been initiated, aiming to recruit patients undergoing radical radiotherapy (RT) or chemoradiotherapy (CRT) for mucosal primary head and neck cancer (MPHNC). Eligible patients are imaged using FDG-PET/CT before treatment, at the end of week 3 of treatment and 12 weeks after treatment completion according to local imaging policy. Functional MRI using diffusion weighted (DWI), blood oxygen level-dependent (BOLD) and dynamic contrast enhanced (DCE) sequences is carried out prior to, during and following treatment. Information regarding treatment outcomes will be collected, as well as physician-scored and patient-reported toxicity.

DISCUSSION

The primary objective is to determine the correlation of functional MRI sequences with tumour response as determined by FDG-PET/CT and clinical findings at 12 weeks post-treatment and with local control at 12 months post-treatment. Secondary objectives include prospective correlation of functional MRI and PET imaging with disease-free survival and overall survival, defining the optimal time points for functional MRI assessment of treatment response, and determining the sensitivity and specificity of functional MRI sequences for assessment of potential residual disease following treatment. If the study is able to successfully characterise tumours based on their functional MRI scan characteristics, this would pave the way for further studies refining treatment approaches based on prognostic and predictive imaging data.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12616000534482 (26 April 2016).

Correlation between BOLD-MRI and HIF expression level in renal carcinoma

Occupying about 2%~3% of all malignant tumors, renal carcinoma is the most common primary cancer in kidney. The oxidative level of tumor cells is of vital role for optimizing treatment plan, evaluating efficacy and predicting prognosis. This study thus investigated the R2(*) value in mouse renal carcinoma model and the correlation between tumor hypoxia and expression level of hypoxia inducible factor-1 (HIF-1). A total of 20 BALB/C nude mice (4~6 weeks old) were inoculated with human ACHN renal carcinoma cells to generate renal cancer model. After the tumor diameter reached 0.5 cm, all animals were examined by BOLD-MRI, both under normal inhalation (R2a(*)) and carbogen treatment (R2b(*)). The alternation of R2(*) values (ΔR2(*)=R2a(*) - R2b(*)) was calculated. Mice were then sacrificed for Immunohistochemical (IHC) staining targeting HIF-1α and HIF-2α. The positive score of HIF was then analyzed for its correlation with R2(*) value. In 18 mice finished both experiments, Pearson correlation analysis revealed significant negative correlation between R2a(*) and ΔR2(*) (r=-0.48, P<0.05) and positive relationship between ΔR2(*) and HIF-2α (r=0.38, P<0.05). HIF-1α level, however, did not correlated with tumor R(*) values. The positive correlation between ΔR2(*) and HIF-2α, but not HIF-1α, suggested potential role of combined BOLD-MRI technique and HIF-1α staining in clinical diagnosis of renal carcinoma. HIF-2α may work as biological marker for renal cancer.