Intraindividual In Vivo Comparison of Gadolinium Contrast Agents for Pharmacokinetic Analysis Using Dynamic Contrast Enhanced Magnetic Resonance Imaging:

High-Grade Soft-Tissue Sarcomas: Can Optimizing Dynamic Contrast-Enhanced MRI Postprocessing Improve Prognostic Radiomics Models?

BACKGROUND

Heterogeneity on pretreatment dynamic contrast-enhanced (DCE)-MRI of sarcomas may be prognostic, but the best technique to capture this characteristic remains unknown.

PURPOSE

To investigate the best method to extract prognostic data from baseline DCE-MRI.

STUDY TYPE

Retrospective, single-center.

POPULATION

Fifty consecutive uniformly-treated adults with nonmetastatic high-grade sarcomas.

FIELD STRENGTH/SEQUENCE

1.5T; T₂ -weighted-imaging, fat-suppressed fast spoiled gradient echo DCE-MRI.

ASSESSMENT

Ninety-two radiomics features (RFs) were extracted at each DCE-MRI phase (11, from t = 0-88 sec). Relative changes in RFs (rRFs) since the acquisition baseline were calculated (11 × 92 rRFs). Curves of rRF as function of time postinjection were integrated (92 integrated-rRFs [irRFs]). K^trans and area under the time-intensity curve at 88-sec parametric maps were computed and 2 × 92 parametric-RFs (pRFs) were extracted. Five DCE-MRI-based radiomics models were built on: an RFs subset (32 sec, 64 sec, 88 sec); all rRFs; all irRFs; and all pRFs. Two models were elaborated as reference, on: conventional radiological features; and T₂ -WI RFs.

STATISTICAL TESTS

A common machine-learning approach was applied to radiomics models. Features with P < 0.05 at univariate analysis were entered in a LASSO-penalized Cox regression including bootstrapped 10-fold cross-validation. The resulting radiomics scores (RScores) were dichotomized per their median and entered in multivariate Cox models for predicting metastatic relapse-free survival. Models were compared with integrative area under the curve (AUC) and concordance index.

RESULTS

Only dichotomized RScores from models based on rRFs subset, all rRFS and irRFS correlated with prognostic (P = 0.0107-0.0377). The models including all rRFs and irRFs had the highest c-index (0.83), followed by the radiological model. The radiological model had the highest integrative AUC (0.87), followed by models including all rRFs and irRFs. The radiological and full rRFs models were significantly better than the T₂ -based radiomics model (P = 0.02).

DATA CONCLUSION

The initial DCE-MRI of STS contains prognostic information. It seems more relevant to make predictions on rRFs instead of pRFs. Evidence Level: 3 Technical Efficacy: 3 J. Magn. Reson. Imaging 2020;52:282-297.

Pharmacokinetic modeling of dynamic contrast-enhanced MRI using a reference region and input function tail

PURPOSE

Quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) requires an arterial input function (AIF) which is difficult to measure. We propose the reference region and input function tail (RRIFT) approach which uses a reference tissue and the washout portion of the AIF.

METHODS

RRIFT was evaluated in simulations with 100 parameter combinations at various temporal resolutions (5-30 s) and noise levels (σ = 0.01-0.05 mM). RRIFT was compared against the extended Tofts model (ETM) in 8 studies from patients with glioblastoma multiforme. Two versions of RRIFT were evaluated: one using measured patient-specific AIF tails, and another assuming a literature-based AIF tail.

RESULTS

RRIFT estimated the transfer constant K trans and interstitial volume v e with median errors within 20% across all simulations. RRIFT was more accurate and precise than the ETM at temporal resolutions slower than 10 s. The percentage error of K trans had a median and interquartile range of -9 ± 45% with the ETM and -2 ± 17% with RRIFT at a temporal resolution of 30 s under noiseless conditions. RRIFT was in excellent agreement with the ETM in vivo, with concordance correlation coefficients (CCC) of 0.95 for K trans , 0.96 for v e , and 0.73 for the plasma volume v p using a measured AIF tail. With the literature-based AIF tail, the CCC was 0.89 for K trans , 0.93 for v e and 0.78 for v p .

CONCLUSIONS

Quantitative DCE-MRI analysis using the input function tail and a reference tissue yields absolute kinetic parameters with the RRIFT method. This approach was viable in simulation and in vivo for temporal resolutions as low as 30 s.

Intra-individual comparison of different gadolinium-based contrast agents in the quantitative evaluation of C6 glioma with dynamic contrast-enhanced magnetic resonance imaging

This experiment aimed to compare the ionic (Gadodiamide, Gd-DTPA-BMA) and non-ionic (Gadopentetate dimeglumine, Gd-DTPA) gadolinium-based contrast agents (GBCA) in the quantitative evaluation of C6 glioma with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A C6 glioma model was established in 12 Wistar rats, and magnetic resonance (MR) scans were performed six days after tumor implantation. Imaging was performed using a 3.0-T MR scanner with a 7-inch handmade circular coil. Pre-contrast T1 mapping and dynamic contrast-enhanced T1WI after a bolus injection (0.2 mL s^-1) of GBCA at 0.4 mmol kg^-1 were performed. Each rat received two DCE-MRI scans, 24 h apart. The first and second scans were performed using Gd-DTPA-BMA and Gd-DTPA, respectively. Image data were processed using the Patlak model. Both K ^trans and V _p maps were generated. Tumors were manually segmented on all 3D K ^trans and V _p maps. Pixel counts and mean values were recorded for use in a paired t-test. Three radiologists independently performed the tumor segmentation and value calculation. The agreements from different observers were subjective to the intra-class correlation coefficient (ICC). Readers demonstrated that the pixel counts of tumors in K ^trans maps were higher with Gd-DTPA-BMA than with Gd-DTPA (P&lt;0.001, all readers). Although the K ^trans values were higher with Gd-DTPA-BMA than with Gd-DTPA, there was no statistical significance (P&gt;0.05, all readers). The pixel counts of tumors in V _p maps, as well as V _p values, showed no obvious difference between the two agents (P&gt;0.05, all readers). Excellent interobserver measurement reproducibility and reliability were demonstrated in the ICC tests. The Gd-DTPA-BMA contrast agent had significantly higher pixel counts of glioma in the K ^trans maps, and an increased tendency for average K ^trans values, indicating that DCE-MRI with Gd-DTPA-BMA may be more suitable and sensitive for the evaluation of glioma.

Assessment of DCE-MRI parameters for brain tumors through implementation of physiologically-based pharmacokinetic model approaches for Gd-DOTA

Dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) is used for detailed characterization of pathology of lesions sites, such as brain tumors, by quantitative analysis of tracer's data through the use of pharmacokinetic (PK) models. A key component for PK models in DCE-MRI is the estimation of the concentration-time profile of the tracer in a nearby vessel, referred as Arterial Input Function (AIF). The aim of this work was to assess through full body physiologically-based pharmacokinetic (PBPK) model approaches the PK profile of gadoteric acid (Gd-DOTA) and explore potential application for parameter estimation in DCE-MRI based on PBPK-derived AIFs. The PBPK simulations were generated through Simcyp(®) platform and the predicted PK parameters for Gd-DOTA were compared with available clinical data regarding healthy volunteers and renal impairment patients. The assessment of DCE-MRI parameters was implemented by utilizing similar virtual profiles based on gender, age and weight to clinical profiles of patients diagnosed with glioblastoma multiforme. The PBPK-derived AIFs were then used to compute DCE-MRI parameters through the Extended Tofts Model and compared with the corresponding ones derived from image-based AIF computation. The comparison involved: (i) image measured AIF of patients vs AIF of in silico profile, and, (ii) population average AIF vs in silico mean AIFs. The results indicate that PBPK-derived AIFs allowed the estimation of comparable imaging biomarkers with those calculated from typical DCE-MRI image analysis. The incorporation of PBPK models and potential utilization of in silico profiles to real patient data, can provide new perspectives in DCE-MRI parameter estimation and data analysis.

Feasibility for detecting liver metastases in dogs using gadobenate dimeglumine-enhanced magnetic resonance imaging

Early detection of liver metastases may improve the prognosis for successful treatment in dogs with primary tumors. Hepatobiliary-specific contrast agents have been shown to allow an increase in magnetic resonance imaging (MRI) detection of liver metastases in humans. The purpose of this prospective study was to test the feasibility for using one of these agents, gadobenate dimeglumine, to detect liver metastases in dogs. Ten consecutive dogs known to have a primary tumor were recruited for inclusion in the study. All dogs were scanned using the same protocol that included a T2-weighted respiratory-triggered sequence, T1 VIBE, diffusion-weighted imaging, and 3D-FLASH before and after dynamic injection of gadobenate dimeglumine contrast medium. Delayed imaging was performed less than 30 min after injection and up to 60 min in two cases. Histological analysis of liver lesions identified in delayed phases was performed for each case and confirmed metastatic origin. In all cases, lesion number detected in hepatobiliary contrast-enhanced sequences was statistically higher than in other sequences. Optimal lesion detection occurred with a 3D-FLASH sequence acquired in the transverse plane and less than 30 min after injection. Findings indicated that gabobenate dimeglumine enhanced MRI is a feasible technique for detecting liver metastases in dogs.

Brain tumours at 7T MRI compared to 3T--contrast effect after half and full standard contrast agent dose: initial results

OBJECTIVES

To compare the contrast agent effect of a full dose and half the dose of gadobenate dimeglumine in brain tumours at 7 Tesla (7 T) MR versus 3 Tesla (3T).

METHODS

Ten patients with primary brain tumours or metastases were examined. Signal intensities were assessed in the lesion and normal brain. Tumour-to-brain contrast and lesion enhancement were calculated. Additionally, two independent readers subjectively graded the image quality and artefacts.

RESULTS

The enhanced mean tumour-to-brain contrast and lesion enhancement were significantly higher at 7 T than at 3T for both half the dose (91.8 ± 45.8 vs. 43.9 ± 25.3 [p = 0.010], 128.1 ± 53.7 vs. 75.5 ± 32.4 [p = 0.004]) and the full dose (129.2 ± 50.9 vs. 66.6 ± 33.1 [p = 0.002], 165.4 ± 54.2 vs. 102.6 ± 45.4 [p = 0.004]). Differences between dosages at each field strength were also significant. Lesion enhancement was higher with half the dose at 7 T than with the full dose at 3T (p = .037), while the tumour-to-brain contrast was not significantly different. Subjectively, contrast enhancement, visibility, and lesion delineation were better at 7 T and with the full dose. All parameters were rated as good, at the least.

CONCLUSION

Half the routine contrast agent dose at 7 T provided higher lesion enhancement than the full dose at 3T which indicates the possibility of dose reduction at 7 T.

KEY POINTS

• The contrast effect of gadobenate dimeglumine was assessed at 7 T and 3T. • In brain tumours, contrast effect was higher at 7 T than at 3T. • Tumour-to-brain contrast at 7 T half dose and 3T full dose were comparable. • 7 T half dose lesion enhancement was higher than 3T full dose enhancement. • Our results indicate the possibility of contrast agent dose reduction at 7 T.

Advances in diagnostic radiology

Recent advances in diagnostic radiology are discussed on the basis of current publications in Investigative Radiology. Publications in the journal during 2009 and 2010 are reviewed, evaluating developments by modality and anatomic region. Technological advances continue to play a major role in the evolution and clinical practice of diagnostic radiology, and as such constitute a major publication focus. In the past 2 years, this includes advances in both magnetic resonance and computed tomography (in particular, the advent of dual energy computed tomography). An additional major focus of publications concerns contrast media, and in particular continuing research involving nephrogenic systemic fibrosis, its etiology, and differentiation of the gadolinium chelates on the basis of in vivo stability.