Objectives
To determine the diagnostic performance, cut-off values, and optimal drive frequency range for staging hepatic fibrosis using tomoelastography by multifrequency MR elastography of the ...liver and spleen.
Methods
This prospective study consecutively enrolled a total of 61 subjects between June 2014 and April 2017: 45 patients with chronic liver disease and proven stage of fibrosis and 16 healthy volunteers. Tomoelastography was performed at 1.5 T using six drive frequencies from 35 to 60 Hz. Cut-off values and AUC were calculated. Shear wave speed (in m/s) of the liver and spleen was assessed separately and in combination as a surrogate of stiffness.
Results
For compound multifrequency processing of the liver, cut-off and AUC values by fibrosis stage were as follows: F1, 1.52 m/s and 0.89; F2, 1.55 m/s and 0.94; F3, 1.67 m/s and 0.98; and F4, 1.72 m/s and 0.98. Diagnostic performance of the best single drive frequencies (45 Hz, 55 Hz, 60 Hz) was similar (mean AUC = 0.95, respectively). Combined analysis of the liver and spleen slightly improved performance at 60 Hz in F4 patients (mean AUC = 0.97 vs. 0.95,
p
= 0.03). Full-field-of-view elastograms displayed not only the liver and spleen but also small anatomical structures including the pancreas and major vessels.
Conclusion
Tomoelastography provides full-field-of-view elastograms with unprecedented detail resolution and excellent diagnostic accuracy for staging hepatic fibrosis. Our analysis of single-frequency tomoelastography suggests that scan time can be further reduced in future studies, making tomoelastography easier to implement in clinical routine.
Key Points
• Tomoelastography provides full-field-of-view elastograms of the abdomen with unprecedented detail resolution and excellent diagnostic accuracy for staging hepatic fibrosis.
• Diagnostic performance of single-frequency tomoelastography at higher frequencies (45 Hz, 55 Hz, 60 Hz) and compound multifrequency processing are equivalent for staging hepatic fibrosis.
• Combined assessment of hepatic and splenic stiffness slightly improves diagnostic performance for staging hepatic fibrosis.
Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based ...image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography, yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient, MRE magnitude, shear wave speed, and loss angle maps). Combinations of these data were used to train Dense U-nets with manually segmented masks of the entire prostate gland (PG), central zone (CZ), and peripheral zone (PZ) in 30 patients and to validate them in 10 patients. Dice score (DS), sensitivity, specificity, and Hausdorff distance were determined. We found that segmentation based on MRE magnitude maps alone (DS, PG: 0.93 ± 0.04, CZ: 0.95 ± 0.03, PZ: 0.77 ± 0.05) was more accurate than magnitude maps combined with T2w and DWI_b (DS, PG: 0.91 ± 0.04, CZ: 0.91 ± 0.06, PZ: 0.63 ± 0.16) or T2w alone (DS, PG: 0.92 ± 0.03, CZ: 0.91 ± 0.04, PZ: 0.65 ± 0.08). Automatically tabulated MRE values were not different from ground-truth values (P>0.05). In conclusion, MRE combined with Dense U-net segmentation allows tabulation of quantitative imaging markers without manual analysis and independent of other MRI sequences and can thus contribute to PCa detection and classification.
•Tomoelastography allows noise-robust shear wave inversion for multifrequency MRE.•High resolution mechanical property maps with unseen anatomical details are obtained.•Mechanical properties of small ...abdominal tissues were analyzed for the first time.
Palpation is one of the most sensitive, effective diagnostic practices, motivating the quantitative and spatially resolved determination of soft tissue elasticity parameters by medical ultrasound or MRI. However, this so-called elastography often suffers from limited anatomical resolution due to noise and insufficient elastic deformation, currently precluding its use as a tomographic modality on its own. We here introduce an efficient way of processing wave images acquired by multifrequency magnetic resonance elastography (MMRE), which relies on wave number reconstruction at different harmonic frequencies followed by their amplitude-weighted averaging prior to inversion. This results in compound maps of wave speed, which reveal variations in tissue elasticity in a tomographic fashion, i.e. an unmasked, slice-wise display of anatomical details at pixel-wise resolution. The method is demonstrated using MMRE data from the literature including abdominal and pelvic organs such as the liver, spleen, uterus body and uterus cervix. Even in small regions with low wave amplitudes, such as nucleus pulposus and spinal cord, elastic parameters consistent with literature values were obtained. Overall, the proposed method provides a simple and noise-robust strategy of in-plane wave analysis of MMRE data, with a pixel-wise resolution producing superior detail to MRE direct inversion methods.
Display omitted
Cerebral viscoelastic constants can be measured in a noninvasive, image-based way by magnetic resonance elastography (MRE) for the detection of neurological disorders. However, MRE brain maps of ...viscoelastic constants are still limited by low spatial resolution. Here we introduce three-dimensional multifrequency MRE of the brain combined with a novel reconstruction algorithm based on a model-free multifrequency inversion for calculating spatially resolved viscoelastic parameter maps of the human brain corresponding to the dynamic range of shear oscillations between 30 and 60 Hz. Maps of two viscoelastic parameters, the magnitude and the phase angle of the complex shear modulus, |G*| and φ, were obtained and normalized to group templates of 23 healthy volunteers in the age range of 22 to 72 years. This atlas of the anatomy of brain mechanics reveals a significant contrast in the stiffness parameter |G*| between different anatomical regions such as white matter (WM; 1.252±0.260 kPa), the corpus callosum genu (CCG; 1.104±0.280 kPa), the thalamus (TH; 1.058±0.208 kPa) and the head of the caudate nucleus (HCN; 0.649±0.101 kPa). φ, which is sensitive to the lossy behavior of the tissue, was in the order of CCG (1.011±0.172), TH (1.037±0.173), CN (0.906±0.257) and WM (0.854±0.169). The proposed method provides the first normalized maps of brain viscoelasticity with anatomical details in subcortical regions and provides useful background data for clinical applications of cerebral MRE.
Viscoelasticity is a sensitive measure of the microstructural constitution of soft biological tissue and is increasingly used as a diagnostic marker, e.g. in staging liver fibrosis or characterizing ...breast tumors. In this study, multifrequency magnetic resonance elastography was used to investigate the in vivo viscoelasticity of healthy human brain in 55 volunteers (23 females) ranging in age from 18 to 88 years. The application of four vibration frequencies in an acoustic range from 25 to 62.5 Hz revealed for the first time how physiological aging changes the global viscosity and elasticity of the brain. Using the rheological springpot model, viscosity and elasticity are combined in a parameter μ that describes the solid-fluid behavior of the tissue and a parameter α related to the tissue's microstructure. It is shown that the healthy adult brain undergoes steady parenchymal ‘liquefaction’ characterized by a continuous decline in μ of 0.8% per year (P<0.001), whereas α remains unchanged. Furthermore, significant sex differences were found with female brains being on average 9% more solid-like than their male counterparts rendering women more than a decade ‘younger’ than men with respect to brain mechanics (P=0.016). These results set the background for using cerebral multifrequency elastography in diagnosing subtle neurodegenerative processes not detectable by other diagnostic methods.
Spatial heterogeneity of hepatic fibrosis in primary sclerosing cholangitis (PSC) in comparison to viral hepatitis was assessed as a potential new biomarker using MR elastography (MRE). In this ...proof-of-concept study, we hypothesized a rather increased heterogeneity in PSC and a rather homogeneous distribution in viral hepatitis. Forty-six consecutive subjects (PSC: n = 20, viral hepatitis: n = 26) were prospectively enrolled between July 2014 and April 2017. Subjects underwent multifrequency MRE (1.5 T) using drive frequencies of 35-60 Hz and generating shear-wave speed (SWS in m/s) maps as a surrogate of stiffness. The coefficient of variation (CV in %) was determined to quantify fibrosis heterogeneity. Mean SWS and CV were 1.70 m/s and 21% for PSC, and 1.84 m/s and 18% for viral hepatitis. Fibrosis heterogeneity was significantly increased for PSC (P = 0.04) while no difference was found for SWS of PSC and viral hepatitis (P = 0.17). Global hepatic stiffness was similar in PSC and viral hepatitis groups, but spatial heterogeneity may reveal spatial patterns of stiffness changes towards enhanced biophysics-based diagnosis by MRI.
MR elastography (MRE) enables the noninvasive determination of the viscoelastic behavior of human internal organs based on their response to oscillatory shear stress. An experiment was developed that ...combines multifrequency shear wave actuation with broad-band motion sensitization to extend the dynamic range of a single MRE examination. With this strategy, multiple wave images corresponding to different driving frequencies are simultaneously received and can be analyzed by evaluating the dispersion of the complex modulus over frequency. The technique was applied on the brain and liver of five healthy volunteers. Its repeatability was tested by four follow-up studies in each volunteer. Five standard rheological models (Maxwell, Voigt, Zener, Jeffreys and fractional Zener model) were assessed for their ability to reproduce the observed dispersion curves. The three-parameter Zener model was found to yield the most consistent results with two shear moduli mu(1) = 0.84 +/- 0.22 (1.36 +/- 0.31) kPa, mu(2) = 2.03 +/- 0.19 (1.86 +/- 0.34) kPa and one shear viscosity of eta = 6.7 +/- 1.3 (5.5 +/- 1.6) Pa s (interindividual mean +/- SD) in brain (liver) experiments. Significant differences between the rheological parameters of brain and liver were found for mu(1) and eta (P < 0.05), indicating that human brain is softer and possesses a higher viscosity than liver.
Objectives
To prospectively investigate the stiffness and fluidity of pancreatic ductal adenocarcinoma (PDAC) and autoimmune pancreatitis (AIP) with tomoelastography, and to evaluate its diagnostic ...performance in distinguishing the two entities.
Methods
Tomoelastography provided high-resolution maps of shear wave speed (
c
in m/s) and phase angle (
φ
in rad), allowing mechanical characterization of the stiffness and fluidity properties of the pancreas. Forty patients with untreated PDAC and 33 patients with untreated AIP who underwent diagnostic pancreatic MRI at 3-T together with multifrequency MR elastography and tomoelastography data processing were prospectively enrolled. Ten healthy volunteers served as controls. Two radiologists and a technician measured pancreatic stiffness and fluidity independently. The two radiologists also independently evaluated the patients’ conventional MR sequences using the following diagnostic score: 1, definitely PDAC; 2, probably PDAC; 3, indeterminate; 4, probably AIP; and 5, definitely AIP. Interobserver agreement was assessed. Stiffness and fluidity of PDAC, AIP, and healthy pancreas, as well as diagnostic performance of tomoelastography and conventional MRI, were compared.
Results
AIP showed significantly lower stiffness and fluidity than PDAC and significantly higher stiffness and fluidity than healthy pancreas. Pancreatic fluidity was not influenced by secondary obstructive changes. The intraclass correlation coefficient for pancreatic stiffness and fluidity by the 3 readers was near-perfect (0.951–0.979, all
p
< 0.001). Both stiffness and fluidity allowed distinguishing PDAC from AIP. AUCs were 0.906 for stiffness, 0.872 for fluidity, and 0.842 for conventional MRI.
Conclusions
Pancreatic stiffness and fluidity both allow differentiation of PDAC and AIP with high accuracy.
Key Points
•
AIP showed significantly lower stiffness and fluidity than PDAC and significantly higher stiffness and fluidity than healthy pancreas.
•
Both stiffness and fluidity allowed distinguishing PDAC from AIP.
•
Pancreatic fluidity could distinguish malignancy from non-malignant secondary obstructive changes.
PDF
