Early response monitoring of receptor tyrosine kinase inhibitor therapy in metastatic renal cell carcinoma using [F-18]fluorothymidine-positron emission tomography-magnetic resonance

Non-invasive molecular imaging of kidney diseases

In nephrology, differential diagnosis or assessment of disease activity largely relies on the analysis of glomerular filtration rate, urinary sediment, proteinuria and tissue obtained through invasive kidney biopsies. However, currently available non-invasive functional parameters, and most serum and urine biomarkers, cannot capture intrarenal molecular disease processes specifically. Moreover, although histopathological analyses of kidney biopsy samples enable the visualization of pathological morphological and molecular alterations, they only provide information about a small part of the kidney and do not allow longitudinal monitoring. These limitations not only hinder understanding of the dynamics of specific disease processes in the kidney, but also limit the targeting of treatments to active phases of disease and the development of novel targeted therapies. Molecular imaging enables non-invasive and quantitative assessment of physiological or pathological processes by combining imaging technologies with specific molecular probes. Here, we discuss current preclinical and clinical molecular imaging approaches in nephrology. Non-invasive visualization of the kidneys through molecular imaging can be used to detect and longitudinally monitor disease activity and can therefore provide companion diagnostics to guide clinical trials, as well as the safe and effective use of drugs.

Systemic treatment of the metastatic renal cell carcinoma: usefulness of the apparent diffusion coefficient of diffusion-weighted MRI in prediction of early therapeutic response

Accurate prediction of early treatment response to systemic therapy (ST) with tyrosine kinase inhibitors (TKI) in patients with metastatic renal cell carcinoma (mRCC) could help avoid ineffective and expensive treatment with serious side effects. Neither RECIST v.1.1 nor Choi criteria successfully discriminate between patients with mRCC who received ST having a short or long time to progression (TTP). There is no biomarker, which is able to predict early therapeutic response to TKIs application in patients with mRCC. The goal of our study was to investigate the potential of apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) of MRI in prediction of early therapeutic response to ST with pazopanib in patients with mRCC. The retrospective study enrolled 32 adult patients with conventional mRCC who received pazopanib (mean duration-7.5 ± 3.45). The mean duration of follow-up was 11.85 ± 4.34 months. In all patients as baseline examination and 1 month after treatment, 1.5T MRI including DWI sequence was performed followed by ADC measurement of the main renal lesion. For assessment of the therapeutic response, RECIST 1.1 is used. Partial response (PR), stable disease (SD) and progressive disease (PD) were observed in 12 (37.50%), 10 (31.25%) and 10 (31.25%) cases with mean TTP of 10.33 ± 2.06 months (95% confidence interval, CI = 9.05-11.61), 7.40 ± 2.50 months (95% CI = 5.61-9.19) and 4.20 ± 1.99 months (95% CI = 2.78-5.62) accordingly (p < 0.05). There was no difference in change of main lesions' longest size 1 month after ST in patients with PR, SD and PD. Comparison of mean ADC values before and 1 month after systemic treatment showed significant decrease by 19.11 ± 10.64% (95% CI = 12.35-25.87) and by 7.66 ± 6.72% (95% CI = 2.86-12.47) in subgroups with PR and SD, respectively (p < 0.05). There was shorter TTP in patients with mRCC if ADC of the main renal lesion 1 month after the ST increased from the baseline less than 1.73% compared to patients with ADC levels above this threshold: 5.29 ± 3.45 versus 9.50 ± 2.04 months accordingly (p < 0.001). Overall, our findings highlighted the use of ADC as a predictive biomarker for early therapeutic response assessment. Use of ADC will be effective and useful for reliable prediction of responders and non-responders to systemic treatment with pazopanib.

¹⁸F-FDG PET/CT for Monitoring of Treatment Response in Breast Cancer

Changes in tumor metabolic activity have been shown to be an early indicator of treatment effectiveness for breast cancer, mainly in the neoadjuvant setting. The histopathologic response at the completion of chemotherapy has been used as the reference standard for assessment of the accuracy of (18)F-FDG PET in predicting a response during systemic treatment. Although a pathologic complete response (pCR) remains an important positive prognostic factor for an individual patient, a recent metaanalysis could validate pCR as a surrogate marker for patient outcomes only in aggressive breast cancer subtypes. For establishment of the clinical application of metabolic treatment response studies, larger series of specific breast cancer subtypes-including hormone receptor-positive, human epidermal growth factor receptor 2-positive, and triple-negative breast cancers-are necessary. In addition, thresholds for relative changes in (18)F-FDG uptake to distinguish between responding and nonresponding tumors need to be validated for different systemic treatment approaches, with progression-free survival and overall survival as references. A PET-based treatment stratification is applicable clinically only if valid alternative therapies are available. Of note, patients who do not achieve a pCR might still benefit from neoadjuvant therapy enabling breast-conserving surgery. In the metastatic setting, residual tumor metabolic activity after the initiation of systemic therapy is an indicator of active disease, whereas a complete resolution of metabolic activity is predictive of a successful treatment response.

Radiomics Analysis on FLT-PET/MRI for Characterization of Early Treatment Response in Renal Cell Carcinoma: A Proof-of-Concept Study

Studying early response to cancer treatment is significant for patient treatment stratification and follow-up. Although recent advances in positron emission tomography (PET) and magnetic resonance imaging (MRI) allow for evaluation of tumor response, a quantitative objective assessment of treatment-related effects offers localization and quantification of structural and functional changes in the tumor region. Radiomics, the process of computerized extraction of features from radiographic images, is a new strategy for capturing subtle changes in the tumor region that works by quantifying subvisual patterns which might escape human identification. The goal of this study was to demonstrate feasibility for performing radiomics analysis on integrated PET/MRI to characterize early treatment response in metastatic renal cell carcinoma (RCC) undergoing sunitinib therapy. Two patients with advanced RCC were imaged using an integrated PET/MRI scanner. [18 F] fluorothymidine (FLT) was used as the PET radiotracer, which can measure the degree of cell proliferation. Image acquisitions included test/retest scans before sunitinib treatment and one scan 3 weeks into treatment using [18 F] FLT-PET, T2-weighted (T2w), and diffusion-weighted imaging (DWI) protocols, where DWI yielded an apparent diffusion coefficient (ADC) map. Our framework to quantitatively characterize treatment-related changes involved the following analytic steps: 1) intraacquisition and interacquisition registration of protocols to allow voxel-wise comparison of changes in radiomic features, 2) correction and pseudoquantification of T2w images to remove acquisition artifacts and examine tissue-specific response, 3) characterization of information captured by T2w MRI, FLT-PET, and ADC via radiomics, and 4) combining multiparametric information to create a map of integrated changes from PET/MRI radiomic features. Standardized uptake value (from FLT-PET) and ADC textures ranked highest for reproducibility in a test/retest evaluation as well as for capturing treatment response, in comparison to high variability seen in T2w MRI. The highest-ranked radiomic feature yielded a normalized percentage change of 63% within the RCC region and 17% in a spatially distinct normal region relative to its pretreatment value. By comparison, both the original and postprocessed T2w signal intensity appeared to be markedly less sensitive and specific to changes within the tumor. Our preliminary results thus suggest that radiomics analysis could be a powerful tool for characterizing treatment response in integrated PET/MRI.