Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

Background

We investigated whether features derived from texture analysis (TA) can distinguish breast density (BD) in spiral photon-counting breast computed tomography (PC-BCT).

Methods

In this retrospective single-centre study, we analysed 10,000 images from 400 PC-BCT examinations of 200 patients. Images were categorised into four-level density scale (a–d) using Breast Imaging Reporting and Data System (BI-RADS)-like criteria. After manual definition of representative regions of interest, 19 texture features (TFs) were calculated to analyse the voxel grey-level distribution in the included image area. ANOVA, cluster analysis, and multinomial logistic regression statistics were used. A human readout then was performed on a subset of 60 images to evaluate the reliability of the proposed feature set.

Results

Of the 19 TFs, 4 first-order features and 7 second-order features showed significant correlation with BD and were selected for further analysis. Multinomial logistic regression revealed an overall accuracy of 80% for BD assessment. The majority of TFs systematically increased or decreased with BD. Skewness (rho -0.81), as a first-order feature, and grey-level nonuniformity (GLN, -0.59), as a second-order feature, showed the strongest correlation with BD, independently of other TFs. Mean skewness and GLN decreased linearly from density a to d. Run-length nonuniformity (RLN), as a second-order feature, showed moderate correlation with BD, but resulted in redundant being correlated with GLN. All other TFs showed only weak correlation with BD (range -0.49 to 0.49, p < 0.001) and were neglected.

Conclusion

TA of PC-BCT images might be a useful approach to assess BD and may serve as an observer-independent tool.

Differentiation of inflammatory from degenerative changes in the sacroiliac joints by machine learning supported texture analysis

PURPOSE

To compare the diagnostic performance of texture analysis (TA) against visual qualitative assessment in the differentiation of spondyloarthritis (SpA) from degenerative changes in the sacroiliac joints (SIJ).

METHOD

Ninety patients referred for suspected inflammatory lower back pain from the rheumatology department were retrospectively included at our university hospital institution. MRI at 3 T of the lumbar spine and SIJ was performed with oblique coronal T1-weighted (w), fluid-sensitive fat-saturated (fs) TIRM and fsT1w intravenously contrast-enhanced (CE) images. Subjects were divided into three age- and gender-matched groups (30 each) based on definite clinical diagnosis serving as clinical reference standard with either degenerative, inflammatory (SpA) or no changes of the SIJ. SIJ were rated qualitatively by two independent radiologists and quantitatively by region-of-interest-based TA with 304 features subjected to machine learning logistic regression with randomized ten-fold selection of training and validation data. Qualitative and quantitative results were evaluated for diagnostic performance and compared against clinical reference standard.

RESULTS

Agreement of radiologist's diagnose with clinical reference was fair for both readers (κ = 0.32 and 0.44). ROC statistics revealed significant outperformance of TA compared to qualitative ratings for differentiation of SpA from remainder (AUC = 0.89 vs. 0.75), SpA from degenerative (AUC = 0.91 vs. 0.67) and TIRM-positive SpA (i.e. with bone marrow edema) from remainder cases (AUC = 0.95 vs. 0.76). T1w-CE images were the most important discriminator for detection of SpA.

CONCLUSIONS

TA is superior to qualitative assessment for the differentiation of inflammatory from degenerative changes of the SIJ. Intravenous CE-images increase diagnostic yield in quantitative TA.

Advanced diffusion imaging of abdominal organs in different hydration states of the human body: stability of biomarkers

BACKGROUND

MR diffusion weighted imaging (DWI) may provide important information regarding the pathophysiology of parenchymal abdominal organs. The purpose of our study was to investigate the stability of imaging biomarkers of diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in abdominal parenchymal organs regarding two body hydration states.

METHODS

Ten healthy volunteers twice underwent DWI of abdominal organs using a double-refocused spin-echo echo-planar imaging sequences with 11 different b-values (ranging from 0 to 1,500 s/mm2): after 4 h of fluid deprivation; 45 min following 1000 ml of water intake. Four different diffusion models were evaluated and compared: standard DWI, DKI with mono-exponential fitting, multistep algorithm with variable b-value threshold for IVIM, combined IVIM-Kurtosis; in four abdominal organs: kidneys, liver, spleen and psoas muscle.

RESULTS

Diffusion parameters from all four models remained similar for the renal parenchyma before and after the water challenge. Significant differences were found for the liver, spleen, and psoas muscle. The largest effects were seen for: the liver parenchyma after the water challenge by means of IVIM model's true diffusion (p < 0.02); the spleen, for IVIM's perfusion fraction (p < 0.03), the psoas muscle for the ADC value (p < 0.02).

CONCLUSIONS

Herein, we showed that diffusion parameters of the kidney remain remarkably stable regarding the hydration status. This may be attributed to the kidney-specific compensatory mechanisms. For the liver, spleen and psoas muscle the diffusion parameters were sensitive to changes of the hydration. This phenomenon needs to be considered when evaluating diffusion data of these organs.

[Imaging of the peripheral nervous system]

Imaging of the peripheral nervous system Abstract. With the technical advances in imaging achieved in recent years, the significance of radiology in everyday clinical practice has become definitely increased. This also applies to the diagnosis and evaluation of neuropathies. Highly sensitive electrophysiology is increasingly complemented by specific imaging. Therapy-relevant information from imaging includes the localization and cause, but also the distribution pattern of a neuropathy. Neurography helps to increase diagnostic certainty and is an important part in management of patients with neuropathy. In this article we would like to present the possibilities and the value of different imaging modalities including ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI).

Diagnostic performance of machine learning applied to texture analysis-derived features for breast lesion characterisation at automated breast ultrasound: a pilot study

Background

Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise ABUS findings; and to compare ML to the analysis of single texture features for lesion classification.

Methods

This ethically approved retrospective pilot study included 54 women with benign (n = 38) and malignant (n = 32) solid breast lesions who underwent ABUS. After manual region of interest placement along the lesions’ margin as well as the surrounding fat and glandular breast tissue, 47 texture features (TFs) were calculated for each category. Statistical analysis (ANOVA) and a support vector machine (SVM) algorithm were applied to the texture feature to evaluate the accuracy in distinguishing (i) lesions versus normal tissue and (ii) benign versus malignant lesions.

Results

Skewness and kurtosis were the only TF significantly different among all the four categories (p < 0.000001). In subsets (i) and (ii), a maximum area under the curve of 0.86 (95% confidence interval [CI] 0.82–0.88) for energy and 0.86 (95% CI 0.82–0.89) for entropy were obtained. Using the SVM algorithm, a maximum area under the curve of 0.98 for both subsets was obtained with a maximum accuracy of 94.4% in subset (i) and 90.7% in subset (ii).

Conclusions

TA in combination with ML might represent a useful diagnostic tool in the evaluation of breast imaging findings in ABUS. Applying ML techniques to TFs might be superior compared to the analysis of single TF.

Electronic supplementary material

The online version of this article (10.1186/s41747-019-0121-6) contains supplementary material, which is available to authorized users.

Diffusion tensor imaging of the abdominal organs: Influence of oriented intravoxel flow compartments

Water flow in partially oriented intravoxel compartments mimics an anisotropic fast-diffusion regime, which contributes to the signal attenuation in diffusion-weighted images. In the abdominal organs, this flow may reflect physiological fluid movements (eg, tubular urine flow in kidneys, or bile flow through the liver) and have a clinical relevance. This study investigated the influence of anisotropic intravoxel water flow on diffusion tensor imaging (DTI) of the abdominal organs. Diffusion-weighted images were acquired in five healthy volunteers using an EPI sequence with diffusion preparation (TR/TE: 1000 ms/71 ms; b-values: 0, 10, 20, 40, 70, 120, 250, 450, 700, 1000 s/mm² ; 12 noncollinear diffusion-encoding directions). DTI of liver and kidneys was performed assuming (i) monoexponential decay of the diffusion-weighted signal, and (ii) accounting for potential anisotropy of the fast-diffusion compartments using a tensorial generalization of the IVIM model. Additionally, potential dependency of the metrics of the tensors from the anatomical location was evaluated. Significant differences in the metrics of the diffusion tensor (DT) were found in both liver and kidneys when comparing the two models. In both organs, the trace and the fractional anisotropy of the DT were significantly higher in the monoexponential model than when accounting for perfusion. The comparison of areas of the liver proximal to the hilum with distal regions and of renal cortex with the medulla also proved a location dependency of the size of the fast-diffusion compartments. Pseudo-diffusion correction in DTI enables the assessment of the solid parenchyma regardless of the organ perfusion or other pseudo-diffusive fluid movements. This may have a clinical relevance in the assessment of parenchymal pathologies (eg, liver fibrosis). The fast pseudo-diffusion components present a detectable anisotropy, which may reflect the hepatic microcirculation or other sources of mesoscopic fluid movement in the abdominal organs.

Correction for fast pseudo-diffusive fluid motion contaminations in diffusion tensor imaging

In this prospective study, we quantified the fast pseudo-diffusion contamination by blood perfusion or cerebrospinal fluid (CSF) intravoxel incoherent movements on the measurement of the diffusion tensor metrics in healthy brain tissue. Diffusion-weighted imaging (TR/TE = 4100 ms/90 ms; b-values: 0, 5, 10, 20, 35, 55, 80, 110, 150, 200, 300, 500, 750, 1000, 1300 s/mm², 20 diffusion-encoding directions) was performed on a cohort of five healthy volunteers at 3 Tesla. The projections of the diffusion tensor along each diffusion-encoding direction were computed using a two b-value approach (2b), by fitting the signal to a monoexponential curve (mono), and by correcting for fast pseudo-diffusion compartments using the biexponential intravoxel incoherent motion model (IVIM) (bi). Fractional anisotropy (FA) and mean diffusivity (MD) of the diffusion tensor were quantified in regions of interest drawn over white matter areas, gray matter areas, and the ventricles. A significant dependence of the MD from the evaluation method was found in all selected regions. A lower MD was computed when accounting for the fast-diffusion compartments. A larger dependence was found in the nucleus caudatus (bi: median 0.86 10^-3 mm²/s, Δ2b: -11.2%, Δmono: -14.4%; p = 0.007), in the anterior horn (bi: median 2.04 10^-3 mm²/s, Δ2b: -9.4%, Δmono: -11.5%, p = 0.007) and in the posterior horn of the lateral ventricles (bi: median 2.47 10^-3 mm²/s, Δ2b: -5.5%, Δmono: -11.7%; p = 0.007). Also for the FA, the signal modeling affected the computation of the anisotropy metrics. The deviation depended on the evaluated region with significant differences mainly in the nucleus caudatus (bi: median 0.15, Δ2b: +39.3%, Δmono: +14.7%; p = 0.022) and putamen (bi: median 0.19, Δ2b: +3.1%, Δmono: +17.3%; p = 0.015). Fast pseudo-diffusive regimes locally affect diffusion tensor imaging (DTI) metrics in the brain. Here, we propose the use of an IVIM-based method for correction of signal contaminations through CSF or perfusion.

Volumetric assessment of solid pulmonary nodules on ultralow-dose CT: a phantom study

Background

To reduce the radiation exposure from chest computed tomography (CT), ultralow-dose CT (ULDCT) protocols performed at sub-millisievert levels were previously tested for the evaluation of pulmonary nodules (PNs). The purpose of our study was to investigate the effect of ULDCT and iterative image reconstruction on volumetric measurements of solid PNs.

Methods

CT datasets of an anthropomorphic chest phantom containing solid microspheres were obtained with a third-generation dual-source CT at standard dose, 1/8th, 1/20th and 1/70th of standard dose [CT volume dose index (CTDI_vol): 0.03-2.03 mGy]. Semi-automated volumetric measurements were performed on CT datasets reconstructed with filtered back projection (FBP) and advanced modelled iterative reconstruction (ADMIRE), at strength level 3 and 5. Absolute percentage error (APE) evaluated measurement accuracy related to the effective volume. Scan repetition differences were evaluated using Bland-Altman analysis. Two-way analysis of variance (ANOVA) assessed influence of different scan parameters on APE. Proportional differences (PDs) tested the effect of dose settings and reconstruction algorithms on volumetric measurements, as compared to the standard protocol (standard dose-FBP).

Results

Bland-Altman analysis revealed small mean interscan differences of APE with narrow limits of agreement (-0.1%±4.3% to -0.3%±3.8%). Dose settings (P<0.001), reconstruction algorithms (P<0.001), nodule diameters (P<0.001) and nodule density (P=0.011) had statistically significant influence on APE. Post-hoc Bonferroni tests showed slightly higher APE when scanning with 1/70th of standard dose [mean difference: 3.4%, 95% confidence interval (CI): 2.5-4.3%; P<0.001], and for image reconstruction with ADMIRE5 (mean difference: 1.8%, 95% CI: 1.0-2.5%; P<0.001). No significant differences for scanning with 1/20th of standard dose (P=0.42), and image reconstruction with ADMIRE3 (P=0.19) were found. Scanning with 1/70th of standard dose and image reconstruction with FBP showed the widest range of PDs (-16.8% to 23.4%) compared to standard dose-FBP.

Conclusions

Our phantom study showed no significant difference between nodule volume measurements on standard dose CT (CTDI_vol: 2 mGy) and ULDCT with 1/20th of standard dose (CTDI_vol: 0.10 mGy).

Can texture analysis in ultrashort echo-time MRI distinguish primary graft dysfunction from acute rejection in lung transplants? A multidimensional assessment in a mouse model

BACKGROUND

Differentiation of early postoperative complications affects treatment options after lung transplantation.

PURPOSE

To assess if texture analysis in ultrashort echo-time (UTE) MRI allows distinction of primary graft dysfunction (PGD) from acute transplant rejection (ATR) in a mouse lung transplant model.

STUDY TYPE

Longitudinal.

ANIMAL MODEL

Single left lung transplantation was performed in two cohorts of six mice (strain C57BL/6) receiving six syngeneic (strain C57BL/6) and six allogeneic lung transplants (strain BALB/c (H-2K^d )).

FIELD STRENGTH/SEQUENCE

4.7T small-animal MRI/eight different UTE sequences (echo times: 50-5000 μs) at three different postoperative timepoints (1, 3, and 7 days after transplantation).

ASSESSMENT

Nineteen different first- and higher-order texture features were computed on multiple axial slices for each combination of UTE and timepoint (24 setups) in each mouse. Texture features were compared for transplanted (graft) and contralateral native lungs between and within syngeneic and allogeneic cohorts. Histopathology served as a reference.

STATISTICAL TESTS

Nonparametric tests and correlation matrix analysis were used.

RESULTS

Pathology revealed PGD in the syngeneic and ATR in the allogeneic cohort. Skewness and low-gray-level run-length features were significantly different between PGD and ATR for all investigated setups (P < 0.03). These features were significantly different between graft and native lung in ATR for most setups (minimum of 20/24 setups; all P < 0.05). The number of significantly different features between PGD and ATR increased with elapsing postoperative time. Differences in significant features were highest for an echo-time of 1500 μs.

DATA CONCLUSION

Our findings suggest that texture analysis in UTE-MRI might be a tool for the differentiation of PGD and ATR in the early postoperative phase after lung transplantation.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:108-116.

MRI texture analysis for differentiation of malignant and benign hepatocellular tumors in the non-cirrhotic liver

Purpose

To find potentially diagnostic texture analysis (TA) features and to evaluate the diagnostic accuracy of two-dimensional (2D) magnetic resonance (MR) TA for differentiation between hepatocellular carcinoma (HCC) and benign hepatocellular tumors in the non-cirrhotic liver in an exploratory MR-study.

Materials and methods

108 non-cirrhotic patients (62 female; 41.5 ± 18.3 years) undergoing preoperative contrast-enhanced MRI were retrospectively included in this multi-center-study. TA including gray-level histogram, co-occurrence and run-length matrix features (total 19 features) was performed by two independent readers. Native fat-saturated-T1w and T2w as well as arterial and portal-venous post contrast-enhanced 2D-image-slices were assessed. Conventional reading was performed by two separate independent readers. Differences in TA features between HCC and benign lesions were investigated using independent sample t-tests. Logistic regression analysis was performed to obtain the optimal number/combination of TA-features and diagnostic accuracy of TA analysis. Sensitivity and specificity of the better performing radiologist were compared to TA analysis.

Results

The highest number of significantly differing TA-features (n = 5) was found using the arterial-phase images including one gray-level histogram (skewness, p = 0.018) and four run-length matrix features (all, p < 0.02). The optimal binary logistic regression model for TA-features of the arterial-phase images contained 13 parameters with an accuracy of 84.5% (sensitivity 84.1%, specificity 84.9%) and area-under-the-curve of 0.92 (95%-confidence-interval 0.85–0.98) for diagnosis of HCC. Conventional reading yielded a significantly lower sensitivity (63.6%, p = 0.027) and no significant difference in specificity (94.6%, p = 0.289) at best.

Conclusion

2D-TA of MR images is a feasible objective method that may help to distinguish HCC from benign hepatocellular tumors in the non-cirrhotic liver. Most promising results were found in TA features in the arterial phase images.

Distinction between phyllodes tumor and fibroadenoma in breast ultrasound using deep learning image analysis

Purpose

To evaluate the accuracy of a deep learning software (DLS) in the discrimination between phyllodes tumors (PT) and fibroadenomas (FA).

Methods

In this IRB-approved, retrospective, single-center study, we collected all ultrasound images of histologically secured PT (n = 11, 36 images) and a random control group with FA (n = 15, 50 images). The images were analyzed with a DLS designed for industrial grade image analysis, with 33 images withheld from training for validation purposes. The lesions were also interpreted by four radiologists. Diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). Sensitivity, specificity, negative and positive predictive values were calculated at the optimal cut-off (Youden Index).

Results

The DLS was able to differentiate between PT and FA with good diagnostic accuracy (AUC = 0.73) and high negative predictive value (NPV = 100%). Radiologists showed comparable accuracy (AUC 0.60–0.77) at lower NPV (64–80%). When performing the readout together with the DLS recommendation, the radiologist’s accuracy showed a non-significant tendency to improve (AUC 0.75–0.87, p = 0.07).

Conclusion

Deep learning based image analysis may be able to exclude PT with a high negative predictive value. Integration into the clinical workflow may enable radiologists to more confidently exclude PT, thereby reducing the number of unnecessary biopsies.

Transient steatosis assessed by magnetic resonance imaging predicts outcome after extended hepatectomy in mice

RATIONALE AND OBJECTIVES

Posthepatectomy liver failure (PHLF) remains challenging to diagnose and difficult to treat. The extent of transient regeneration-associated steatosis (TRAS) differs between successful liver regeneration and PHLF. This study aims to quantify TRAS by magnetic resonance imaging (MRI) after hepatectomy in mice.

MATERIALS AND METHODS

Mice (C57BL/6) underwent either extended hepatectomy (EH) or standard hepatectomy (SH). Serial MRI on postoperative days 1-7 was used to compare TRAS and liver remnant growth between groups. Survival was also assessed.

RESULTS

EH was associated with decreased survival and impaired proliferation when compared to SH (p = 0.02 and p = 0.03). MRI showed increased TRAS 48 h after EH compared to SH (11.8 ± 6% vs. 4.3 ± 2%, p < 0.001). Compared to EH survivors, death after EH was associated with increased TRAS 48 h postoperatively (16.4 ± 6% vs. 9.2 ± 5%, p = 0.02).

CONCLUSIONS

EH is associated with increased TRAS and inferior outcomes when compared to SH. MRI may help to predict PHLF after hepatectomy.

Radiomics of liver MRI predict metastases in mice

Background

The purpose of this study was to investigate whether any texture features show a correlation with intrahepatic tumor growth before the metastasis is visible to the human eye.

Methods

Eight male C57BL6 mice (age 8–10 weeks) were injected intraportally with syngeneic MC-38 colon cancer cells and two mice were injected with phosphate-buffered saline (sham controls). Small animal magnetic resonance imaging (MRI) at 4.7 T was performed at baseline and days 4, 8, 12, 16, and 20 after injection applying a T2-weighted spin-echo sequence. Texture analysis was performed on the images yielding 32 texture features derived from histogram, gray-level co-occurrence matrix, gray-level run-length matrix, and gray-level size-zone matrix. The features were examined with a linear regression model/Pearson correlation test and hierarchical cluster analysis. From each cluster, the feature with the lowest variance was selected.

Results

Tumors were visible on MRI after 20 days. Eighteen features from histogram and the gray-level-matrices exhibited statistically significant correlations before day 20 in the experiment group, but not in the control animals. Cluster analysis revealed three distinct clusters of independent features. The features with the lowest variance were Energy, Short Run Emphasis, and Gray Level Non-Uniformity.

Conclusions

Texture features may quantitatively detect liver metastases before they become visually detectable by the radiologist.

Magnetisation transfer as a biomarker for chronic airway fibrosis in a mouse lung transplantation model

Background

Chronic airway fibrosis (CAF) is the most prevalent complication in human lung transplant recipients. The aim of the study is to evaluate magnetisation transfer (MT) as a biomarker of developing CAF of lung transplants in a mouse model.

Methods

Lung transplantation was performed in 48 mice, applying major or minor histocompatibility mismatches between strains for the induction of CAF. MT measurements were performed in vivo with systematic variation of off-resonance frequencies and flip angle of the MT prepulse. MT ratios (MTRs) were compared for lungs showing CAF and without CAF.

Results

Seven out of 24 animals (29%) showed a pattern of CAF at histology. All mice developing CAF also showed signs of acute rejection, whereas none of the lungs showed signs of other post-transplant complications. After lung transplantation, pulmonary infiltration was a frequent finding (14 out of 24) exhibiting a higher MTR (24.8% ± 4.5%) compared to well-ventilated lungs (12.3% ± 6.9%, p = 0.001) at 8000 Hz off-resonance frequency, 3000° flip angle. In infiltrated lung tissue exhibiting CAF, lower MTR values (21.8% ± 5.7%) were found compared to infiltrated lungs showing signs of acute rejection alone (26.5% ± 2.9%, p = 0.028), at 8000 Hz, 3000° flip angle. The highest MTR values were observed at 3000° flip angle, using a 1000 Hz off-resonance frequency.

Conclusion

MTR might serve as a tool for the detection of CAF in infiltrated lung tissue.

Cardiac-gated intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for the investigation of intracranial cerebrospinal fluid dynamics in the lateral ventricle: a feasibility study

PURPOSE

Intravoxel incoherent motion (IVIM) in diffusion-weighted magnetic resonance imaging (DW-MRI) attributes the signal attenuation to the molecular diffusion and to a faster pseudo-diffusion. Purpose of the study was to demonstrate the feasibility of IVIM for the investigation of intracranial cerebrospinal fluid (CSF) dynamics.

METHODS

Cardiac-gated DW-MRI images with fifteen b-values (0-1300s/mm²) along three orthogonal directions (mediolateral (ML), anteroposterior (AP), and craniocaudal (CC)) were acquired during maximum systole and diastole in 10 healthy volunteers (6 males, mean age 36 ± 15 years). A pixel-wise bi-exponential fitting with an iterative nonparametric algorithm was carried out to calculate the following parameters: diffusion coefficient (D), fast diffusion coefficient (D*), and fraction of fast diffusion (f). Region of interest measurements were performed in both lateral ventricles. Comparison of IVIM parameters was performed among two cardiac cycle acquisitions and among the diffusion-encoding directions using a paired Student's t test.

RESULTS

f significantly (p < 0.05) depended on the diffusion-encoding direction and on the cardiac cycle (diastole AP 0.30 ± 0.13, ML 0.22 ± 0.12, CC 0.26 ± 0.17; systole AP 0.45 ± 0.17, ML 0.34 ± 0.15, CC 0.40 ± 0.21). Neither a cardiac cycle nor a direction dependency was found among mean D values (which is in line with the expected intraventricular isotropic diffusion) and D* values (p > 0.05 each).

CONCLUSION

The fraction of fast diffusion from IVIM is feasible to detect a direction-dependent and cardiac-dependent pulsatile CSF flow within the lateral ventricles allowing for quantitative monitoring of CSF dynamics. This technique might provide opportunities to further investigate the pathophysiology of various neurological disorders involving altered CSF dynamics.

Prediction of small for size syndrome after extended hepatectomy: Tissue characterization by relaxometry, diffusion weighted magnetic resonance imaging and magnetization transfer

This study aimed to monitor the course of liver regeneration by multiparametric magnetic-resonance imaging (MRI) after partial liver resection characterizing Small-for-Size Syndrome (SFSS), which frequently leads to fatal post-hepatectomy liver failure (PLF). Twenty-two C57BL/6 mice underwent either conventional 70% partial hepatectomy (cPH), extended 86% partial hepatectomy (ePH) or SHAM operation. Subsequent MRI scans on days 0, 1, 2, 3, 5 and 7 in a 4.7T MR Scanner quantified longitudinal and transverse relaxation times, apparent diffusion coefficient (ADC) and the magnetization-transfer ratio (MTR) of the regenerating liver parenchyma. Histological examination was performed by hematoxylin-eosin staining. After hepatectomy, an increase of T1 time was detected being larger for ePH on day 1: 18% for cPH vs. 40% for ePH and on day 2: 24% for cPH vs. 49% for ePH. An increase in T2 time, again greater in ePH was most pronounced on day 5: 21% for cPH vs. 41% for ePH. ADC and MTR showed a decrease on day 1: 21% for ePH vs. 13% for cPH for ADC, 15% for ePH vs. 11% for cPH for MTR. Subsequently, all MR parameters converged towards initial values in surviving animals. Dying PLF animals exhibited the strongest increase of T1 relaxation time and most prominent decreases of ADC and MTR. The retrieved MRI biomarkers indicate SFSS and potentially developing PLF at an early stage, likely reflecting cellular hypertrophy with extended water content and concomitantly diluted cellular components as features of liver regeneration, appearing more intense in ePH as compared to cPH.

Is there evidence for more than two diffusion components in abdominal organs? - A magnetic resonance imaging study in healthy volunteers

The most commonly applied model for the description of diffusion-weighted imaging (DWI) data in perfused organs is bicompartmental intravoxel incoherent motion (IVIM) analysis. In this study, we assessed the ground truth of underlying diffusion components in healthy abdominal organs using an extensive DWI protocol and subsequent computation of apparent diffusion coefficient 'spectra', similar to the computation of previously described T₂ relaxation spectra. Diffusion datasets of eight healthy subjects were acquired in a 3-T magnetic resonance scanner using 68 different b values during free breathing (equidistantly placed in the range 0-1005 s/mm² ). Signal intensity curves as a function of the b value were analyzed in liver, spleen and kidneys using non-negative least-squares fitting to a distribution of decaying exponential functions with minimum amplitude energy regularization. In all assessed organs, the typical slow- and fast-diffusing components of the IVIM model were detected [liver: true diffusion D = (1.26 ± 0.01) × 10^-3 mm² /s, pseudodiffusion D* = (270 ± 44) × 10^-3 mm² /s; kidney cortex: D = (2.26 ± 0.07) × 10^-3 mm² /s, D* = (264 ± 78) × 10^-3 mm² /s; kidney medulla: D = (1.57 ± 0.28) × 10^-3 mm² /s, D* = (168 ± 18) × 10^-3 mm² /s; spleen: D = (0.91 ± 0.01) × 10^-3 mm² /s, D* = (69.8 ± 0.50) × 10^-3 mm² /s]. However, in the liver and kidney, a third component between D and D* was found [liver: D' = (43.8 ± 5.9) × 10^-3 mm² /s; kidney cortex: D' = (23.8 ± 11.5) × 10^-3 mm² /s; kidney medulla: D' = (5.23 ± 0.93) × 10^-3 mm² /s], whereas no third component was detected in the spleen. Fitting with a diffusion kurtosis model did not lead to a better fit of the resulting curves to the acquired data compared with apparent diffusion coefficient spectrum analysis. For a most accurate description of diffusion properties in the liver and the kidneys, a more sophisticated model seems to be required including three diffusion components.

Texture analysis of acute myocardial infarction with CT: First experience study

Objective

To investigate the feasibility and accuracy of texture analysis to distinguish through objective and quantitative image information between healthy and infarcted myocardium with computed tomography (CT).

Materials and methods

Twenty patients (5 females; mean age 56±10years) with proven acute myocardial infarction (MI) and 20 patients (8 females; mean age 42±15years) with no cardiac abnormalities (hereafter termed controls) underwent contrast-enhanced cardiac CT. Short axis CT images of the left ventricle (LV) were reconstructed at the slice thicknesses 1mm, 2mm, and 5mm. Two independent, blinded readers segmented the LV in controls and patients. Texture analysis was performed yielding first-level features based on the histogram (variance, skewness, kurtosis, entropy), second-level features based on the gray-level co-occurrence matrix (GLCM) (contrast, correlation, energy and homogeneity), and third-level features based on the gray-level run-length matrix (GLRLM).

Results

Inter-and intrareader agreement was good to excellent for all histogram (intraclass correlation coefficient (ICC):0.70–0.93) and for all GLCM features (ICC:0.66–0.99), and was variable for the GLRLM features (ICC:-0.12–0.99). Univariate analysis showed significant differences between patients and controls for 2/4 histogram features, 3/4 GLCM and for 6/11 GLRLM features and all assessed slice thicknesses (all,p<0.05). In a multivariate logistic regression model, the single best variable from each level, determined by ROC analysis, was included stepwise. The best model included kurtosis (OR 0.08, 95%CI:0.01–0.65,P = 0.018) and short run high gray-level emphasis (SRHGE, OR 0.97, 95%CI:0.94–0.99,P = 0.007), with an area-under-the-curve (AUC) of 0.90 (95%CI:0.80–0.99). The best results for kurtosis and SRHGE (AUC = 0.78) were obtained at a 5mm slice thickness. A cut-off value of 14.4 for kurtosis+0.013*SRHGE predicted acute MI with a sensitivity of 95% (specificity 55%).

Conclusion

Our study illustrates the feasibility of texture analysis for distinguishing healthy from acutely infarcted myocardium with cardiac CT using objective, quantitative features, with most reproducible and accurate results at a short axis slice thickness of 5mm.

MRI texture features may predict differentiation and nodal stage of cervical cancer: a pilot study

Background

Texture analysis in oncological magnetic resonance imaging (MRI) may yield surrogate markers for tumor differentiation and staging, both of which are important factors in the treatment planning for cervical cancer.

Purpose

To identify texture features which may predict tumor differentiation and nodal status in diffusion-weighted imaging (DWI) of cervical carcinoma

Material and Methods

Twenty-three patients were enrolled in this prospective, institutional review board (IRB)-approved study. Pelvic MRI was performed at 3-T including a DWI echo-planar sequence with b-values 40, 300, and 800 s/mm². Apparent diffusion coefficient (ADC) maps were used for region of interest (ROI)-based texture analysis (32 texture features) of tumor, muscle, and fat based on histogram and gray-level matrices (GLM). All features confounded by the ROI size (linear model) were excluded. The remaining features were examined for correlations with histological differentiation (Spearman) and nodal status (Kruskal–Wallis). Hierarchical cluster analysis was used to identify correlations between features. A P value < 0.05 was considered statistically significant.

Results

Mean age was 55 years (range = 37–78 years). Biopsy revealed two well-differentiated, eight moderately differentiated, two moderately to poorly differentiated tumors, and five poorly differentiated tumors. Six tumors could not be graded. Lymph nodes were involved in 11 patients. Three GLM features correlated with the differentiation: LRHGE (ϱ = 0.53, P = 0.03), ZP (ϱ = –0.49, P < 0.05), and SZE (ϱ = –0.51, P = 0.04). Two histogram features, skewness (0.65 vs. 1.08, P = 0.04) and kurtosis (0.53 vs. 1.67, P = 0.02), were higher in patients with positive nodal status. Cluster analysis revealed several co-correlations.

Conclusion

We identified potentially predictive GLM features for histological tumor differentiation and histogram features for nodal cancer stage.

Assessment of Cervical Cancer with a Parameter-Free Intravoxel Incoherent Motion Imaging Algorithm

Objective

To evaluate the feasibility of a parameter-free intravoxel incoherent motion (IVIM) approach in cervical cancer, to assess the optimal b-value threshold, and to preliminarily examine differences in the derived perfusion and diffusion parameters for different histological cancer types.

Materials and Methods

After Institutional Review Board approval, 19 female patients (mean age, 54 years; age range, 37–78 years) gave consent and were enrolled in this prospective magnetic resonance imaging study. Clinical staging and biopsy results were obtained. Echo-planar diffusion weighted sequences at 13 b-values were acquired at 3 tesla field strength. Single-sliced region-of-interest IVIM analysis with adaptive b-value thresholds was applied to each tumor, yielding the optimal fit and the optimal parameters for pseudodiffusion (D^*), perfusion fraction (F_p) and diffusion coefficient (D). Monoexponential apparent diffusion coefficient (ADC) was calculated for comparison with D.

Results

Biopsy revealed squamous cell carcinoma in 10 patients and adenocarcinoma in 9. The b-value threshold (median [interquartile range]) depended on the histological type and was 35 (22.5–50) s/mm² in squamous cell carcinoma and 150 (100–150) s/mm² in adenocarcinoma (p < 0.05). Comparing squamous cell vs. adenocarcinoma, D^* (45.1 [25.1–60.4] × 10⁻³ mm²/s vs. 12.4 [10.5–21.2] × 10⁻³ mm²/s) and F_p (7.5% [7.0–9.0%] vs. 9.9% [9.0–11.4%]) differed significantly between the subtypes (p < 0.02), whereas D did not (0.89 [0.75–0.94] × 10⁻³ mm²/s vs. 0.90 [0.82–0.97] × 10⁻³ mm²/s, p = 0.27). The residuals did not differ (0.74 [0.60–0.92] vs. 0.94 [0.67–1.01], p = 0.32). The ADC systematically underestimated the magnitude of diffusion restriction compared to D (p < 0.001).

Conclusion

The parameter-free IVIM approach is feasible in cervical cancer. The b-value threshold and perfusion-related parameters depend on the tumor histology type.

Non-parametric intravoxel incoherent motion analysis of the thyroid gland

Purpose

To implement a protocol for intravoxel incoherent motion (IVIM) of the thyroid, to determine base parameters in healthy volunteers, and to provide preliminary experience on clinical applicability in one patient.

Materials and methods

Eight healthy volunteers underwent 3T MRI using a diffusion weighted echo-planar imaging sequence with 12 different b-values between 0–800 s/mm². The IVIM parameters diffusion coefficient D, pseudo-diffusion coefficient D*, perfusion fraction F_p, and the optimal b-values thresholds were calculated for each thyroid lobe, muscle tissue and the cerebrospinal fluid (CSF) using a non-parametric multi-step algorithm and compared with a Student's t-test. A p-value <0.05 was considered significant.

Results

Mean values for healthy thyroid tissue were: D 1.01 ± 0.13 × 10⁻³ mm²/s, D* 71.0 ± 52.5 × 10⁻³ mm²/s and F_p 17.1 ± 4.2%; for muscle: D 0.50 ± 0.21 × 10⁻³ mm²/s, D* 58.3 ± 99.2 × 10⁻³ mm²/s and F_p 26.5 ± 9.3%; and for CSF D 2.18 ± 0.93 × 10⁻³ mm²/s, D* 99.2 ± 41.2 × 10⁻³ mm²/s and F_p 74.6 ± 12.7%. The optimal b-value threshold separating diffusion and perfusion effects in thyroid ranged between 0–70 s/mm². Healthy thyroid tissue showed similar F_p compared to muscle, both lower than CSF.

Conclusions

The proposed IVIM protocol provides surrogate markers on cellular diffusion restriction and perfusion; thereby providing a more comprehensive description of tissue properties compared to conventional DWI.

Diffusion-weighted imaging of the abdomen: Impact of b-values on texture analysis features

The purpose of this work was to systematically assess the impact of the b-value on texture analysis in MR diffusion-weighted imaging (DWI) of the abdomen. In eight healthy male volunteers, echo-planar DWI sequences at 16 b-values ranging between 0 and 1000 s/mm² were acquired at 3 T. Three different apparent diffusion coefficient (ADC) maps were computed (0, 750/100, 390, 750 s/mm² /all b-values). Texture analysis of rectangular regions of interest in the liver, kidney, spleen, pancreas, paraspinal muscle and subcutaneous fat was performed on DW images and the ADC maps, applying 19 features computed from the histogram, grey-level co-occurrence matrix (GLCM) and grey-level run-length matrix (GLRLM). Correlations between b-values and texture features were tested with a linear and an exponential model; the best fit was determined by the smallest sum of squared residuals. Differences between the ADC maps were assessed with an analysis of variance. A Bonferroni-corrected p-value less than 0.008 (=0.05/6) was considered statistically significant. Most GLCM and GLRLM-derived texture features (12-18 per organ) showed significant correlations with the b-value. Four texture features correlated significantly with changing b-values in all organs (p < 0.008). Correlation coefficients varied between 0.7 and 1.0. The best fit varied across different structures, with fat exhibiting mostly exponential (17 features), muscle mostly linear (12 features) and the parenchymatous organs mixed feature alterations. Two GLCM features showed significant variability in the different ADC maps. Several texture features vary systematically in healthy tissues at different b-values, which needs to be taken into account if DWI data with different b-values are analyzed. Histogram and GLRLM-derived texture features are stable on ADC maps computed from different b-values.

Silica-Coated Nonstoichiometric Nano Zn-Ferrites for Magnetic Resonance Imaging and Hyperthermia Treatment

Large-scale and reproducible synthesis of nanomaterials is highly sought out for successful translation into clinics. Flame aerosol technology with its proven capacity to manufacture high purity materials (e.g., light guides) up to kg h^-1 is explored here for the preparation of highly magnetic, nonstoichiometric Zn-ferrite (Zn_0.4 Fe_2.6 O₄ ) nanoparticles coated in situ with a nanothin SiO₂ layer. The focus is on their suitability as magnetic multifunctional theranostic agents analyzing their T2 contrast enhancing capability for magnetic resonance imaging (MRI) and their magnetic hyperthermia performance. The primary particle size is closely controlled from 5 to 35 nm evaluating its impact on magnetic properties, MRI relaxivity, and magnetic heating performance. Most importantly, the addition of Zn in the flame precursor solution facilitates the growth of spinel Zn-ferrite crystals that exhibit superior magnetic properties over iron oxides typically made in flames. These properties result in strong MRI T2 contrast agents as shown on a 4.7 T small animal MRI scanner and lead to a more efficient heating with alternating magnetic fields. Also, by injecting Zn_0.4 Fe_2.6 O₄ nanoparticle suspensions into pork tissue, MR-images are acquired at clinically relevant concentrations. Furthermore, the nanothin SiO₂ shell facilitates functionalization with polymers, which improves the biocompatibility of the theranostic system.

Simultaneous multi-slice echo planar diffusion weighted imaging of the liver and the pancreas: Optimization of signal-to-noise ratio and acquisition time and application to intravoxel incoherent motion analysis

PURPOSE

To optimize and test a diffusion-weighted imaging (DWI) echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation in the liver and pancreas regarding acquisition time (TA), number of slices, signal-to-noise ratio (SNR), image quality (IQ), apparent diffusion coefficient (ADC) quantitation accuracy, and feasibility of intravoxel incoherent motion (IVIM) analysis.

MATERIALS AND METHODS

Ten healthy volunteers underwent DWI of the upper abdomen at 3T. A SMS DWI sequence with CAIPIRINHA unaliasing technique (acceleration factors 2/3, denoted AF2/3) was compared to standard DWI-EPI (AF1). Four schemes were evaluated: (i) reducing TA, (ii) keeping TA identical with increasing number of averages, (iii) increasing number of slices with identical TA (iv) increasing number of b-values for IVIM. Acquisition schemes i-iii were evaluated qualitatively (reader score) and quantitatively (ADC values, SNR).

RESULTS

In scheme (i) no differences in SNR were observed (p=0.321-0.038) with reduced TA (AF2 increase in SNR/time 75.6%, AF3 increase SNR/time 102.4%). No SNR improvement was obtained in scheme (ii). Increased SNR/time could be invested in acquisition of more and thinner slices or higher number of b-values. Image quality scores were stable for AF2 but decreased for AF3. Only for AF3, liver ADC values were systematically lower.

CONCLUSION

SMS-DWI of the liver and pancreas provides substantially higher SNR/time, which either may be used for shorter scan time, higher slice resolution or IVIM measurements.

Separation of collagen-bound and porous bone water transverse relaxation in mice: proposal of a multi-step approach

The separation and quantification of collagen-bound water (CBW) and pore water (PW) components of the cortical bone signal are important because of their different contribution to bone mechanical properties. Ultrashort TE (UTE) imaging can be used to exploit the transverse relaxation from CBW and PW, allowing their quantification. We tested, for the first time, the feasibility of UTE measurements in mice for the separation and quantification of the transverse relaxation of CBW and PW in vivo using three different approaches for T2 * determination. UTE sequences were acquired at 4.7 T in six mice with 10 different TEs (50-5000 μs). The transverse relaxation time T2 * of CBW (T2 *cbw ) and PW (T2 *pw ) and the CBW fraction (bwf) were computed using a mono-exponential (i), a standard bi-exponential (ii) and a new multi-step bi-exponential (iii) approach. Regions of interest were drawn at multiple levels of the femur and vertebral body cortical bone for each mouse. The sum of the normalized squared residuals (Res) and the homogeneity of variance were tested to compare the different methods. In the femur, approach (i) yielded mean T2 * ± standard deviation (SD) of 657 ± 234 μs. With approach (ii), T2 *cbw , T2 *pw and bwf were 464 ± 153 μs, 15 777 ± 10 864 μs and 57.6 ± 9.9%, respectively. For approach (iii), T2 *cbw , T2 *pw and bwf were 387 ± 108 μs, 7534 ± 2765 μs and 42.5 ± 6.2%, respectively. Similar values were obtained from vertebral bodies. Res with approach (ii) was lower than with the two other approaches (p < 0.007), but T2 *pw and bwf variance was lower with approach (iii) than with approach (ii) (p < 0.048). We demonstrated that the separation and quantification of cortical bone water components with UTE sequences is feasible in vivo in mouse models. The direct bi-exponential approach exhibited the best approximation to the measured signal curve with the lowest residuals; however, the newly proposed multi-step algorithm resulted in substantially lower variability of the computed parameters. Copyright © 2016 John Wiley & Sons, Ltd.

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

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The novel IVIM algorithm accounts for regional differences in the separation of the perfusion and the diffusion components.

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The algorithm improves the reliability of IVIM parameters.

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The algorithm improves the correlation with CBF in healthy volunteers and patients.

Diffusional kurtosis MRI of the lower leg: changes caused by passive muscle elongation and shortening

Diffusional kurtosis MRI (DKI) quantifies the deviation of water diffusion from a Gaussian distribution. We investigated the influence of passive elongation and shortening of the lower leg muscles on the DKI parameters D (diffusion coefficient) and K (kurtosis). After approval by the local ethics committee, eight healthy volunteers (age, 29.1 ± 2.9 years) underwent MRI of the lower leg at 3 T. Diffusion-weighted images were acquired with 10 different b values at three ankle positions (passive dorsiflexion 10°, neutral position 0°, passive plantar flexion 40°). Parametrical maps of D and K were obtained by voxel-wise fitting of the signal intensities using a non-linear Levenberg-Marquardt algorithm. D and K were measured in the tibialis anterior, medial and lateral gastrocnemius, and soleus muscles. In the neutral position, D and K values were in the range between 1.66-1.79 × 10(-3) mm(2) /s and 0.21-0.39, respectively. D and K increased with passive shortening, and decreased with passive elongation, which could also be illustrated on the parametrical maps. In dorsiflexion, D (p < 0.01) and K (p = 0.036) were higher in the tibialis anterior than in the medial gastrocnemius. In plantar flexion, the opposite was found for K (p = 0.035). DKI parameters in the lower leg muscles are significantly influenced by the ankle joint position, indicating that the diffusion of water molecules in skeletal muscle deviates from a Gaussian distribution depending on muscle tonus. Copyright © 2016 John Wiley & Sons, Ltd.

Separation of collagen-bound and porous bone-water longitudinal relaxation in mice using a segmented inversion recovery zero-echo-time sequence

PURPOSE

Cortical bone mechanical properties are related to the collagen-bound water (CBW) and pore water (PW) components of cortical bone. The study evaluates the feasibility of zero-echo-time imaging in mice in vivo for longitudinal relaxation time (T1) measurements in cortical bone and separation of CBW and PW components.

METHODS

Zero-echo-time data were acquired at 4.7 Tesla in six mice with 14 different inversion times (0-2,600 ms). Region-of-interest analysis was performed at level of femur diaphysis. The T1 of cortical bone and of CBW (T1cbw) and PW (T1pw) as well as the CBW fraction (cbwf) was computed using a mono-exponential and a bi-exponential fitting approach, respectively. The sum of the squared residuals (Res) to the fit was provided for both approaches.

RESULTS

For the mono-exponential model, mean T1 ± standard deviation (SD) was 1,057 ± 160 ms. The bi-exponential approach provided a reliable separation of two different bone-water components, with a mean T1cbw of 213 ± 95 ms, T1pw of 2,152 ± 894 ms, and cbwf of 7.4 ± 2.7 %. Lower Res was obtained with bi-exponential approach (P < 0.001), and Res mean values ± SD were 0.016 ± 0.007 (bi-exponential) and 0.033 ± 0.016 (mono-exponential).

CONCLUSION

Zero-echo-time imaging allows for longitudinal relaxation measurements of cortical bone in vivo in mice models, with a reliable separation of PW and CBW components using a bi-exponential curve fitting approach. Magn Reson Med 77:1909-1915, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Magnetization Transfer MR Imaging to Monitor Muscle Tissue Formation during Myogenic in Vivo Differentiation of Muscle Precursor Cells

Purpose To determine whether magnetization transfer (MT) magnetic resonance (MR) imaging may serve as a quantitative measure of the degree of fiber formation during differentiation of muscle precursor cells into engineered muscle tissue as a potential noninvasive monitoring tool in mice. Materials and Methods The study was approved by the local ethics committee (no. StV 01/2008) and the local Veterinary Office (license no. 99/2013). Human muscle progenitor cells (hMPCs) derived from rectus abdominis muscles were subcutaneously injected into CD-1 nude mice (CD-1 nude mice, Crl:CD1-Foxn1^nu; Charles River Laboratories, Wilmington, Mass) for development of muscle tissue. The mice underwent MR imaging examinations at 4.7 T at days 1, 3, 7, 14, 21, and 28 after cell transplantation by using a gradient-echo sequence with an MT prepulse and systematic variation of the off-resonance frequency (50-37 500 Hz) at an amplitude of 800°. Direct saturation was estimated from a Bloch equation simulation. The MT ratio (MTR) was correlated to immunohistochemistry findings, Western blot results, and results of myography. Data were analyzed by using one-way or two-way analysis of variance with the Sidak or Tukey multiple comparisons test. Results In the reference skeletal muscle, highest MT was found for 2500 Hz off-resonance frequency with an MTR ± standard deviation of 57.5% ± 3.5. The developing muscle tissue exhibited increasing MT values during the 28 days of myogenic in vivo differentiation and did not reach the values of native skeletal muscle. Mean values of MTR (2500 Hz) for hMPCs were 27.6% ± 6.3 (day 1), 24.7% ± 8.7 (day 3), 28.2% ± 5.7 (day 7), 35.9% ± 5.0 (day 14), 37.0% ± 7.9 (day 21), and 39.9% ± 8.1 (day 28). The results from MT MR imaging correlated qualitatively well with muscle tissue expression of specific skeletal markers, as well as muscle contractility. Conclusion MT MR imaging may be used to noninvasively monitor the process of myogenic in vivo differentiation of hMPCs as a biomarker of the quantity and quality of muscle fiber formation. ^© RSNA, 2016 Online supplemental material is available for this article.

Whole-Body Diffusion Imaging Applying Simultaneous Multi-Slice Excitation

PURPOSE

The purpose of this study was to examine the feasibility of a fast protocol for whole-body diffusion-weighted imaging (WB-DWI) using a slice-accelerated echo-planar sequence, which, when using comparable image acquisition parameters, noticeably reduces measurement time compared to a conventional WB-DWI protocol.

MATERIALS AND METHODS

A single-shot echo-planar imaging sequence capable of simultaneous slice excitation and acquisition was optimized for WB-DWI on a 3 T MR scanner, with a comparable conventional WB-DWI protocol serving as the reference standard. Eight healthy individuals and one oncologic patient underwent WB-DWI. Quantitative analysis was carried out by measuring the apparent diffusion coefficient (ADC) and its coefficient of variation (CV) in different organs. Image quality was assessed qualitatively by two independent radiologists using a 4-point Likert scale.

RESULTS

Using our proposed protocol, the scan time of the WB-DWI measurement was reduced by up to 25.9 %. Both protocols, the slice-accelerated protocol and the conventional protocol, showed comparable image quality without statistically significant differences in the reader scores. Similarly, no significant differences of the ADC values of parenchymal organs were found, whereas ADC values of brain tissue were slightly higher in the slice-accelerated protocol.

CONCLUSION

It was demonstrated that slice-accelerated DWI can be applied to WB-DWI protocols with the potential to greatly reduce the required measurement time, thereby substantially increasing clinical applicability.

KEY POINTS

•Whole-body diffusion-weighted imaging (WB-DWI) using simultaneous multi-slice and blipped-CAIPIRINHA reduces the measurement time strongly without having a significant impact on image quality. •The reduction in measurement time might strongly contribute to the clinical applicability of WB-DWI. •However, further refinement of the slice-accelerated EPI sequence, and the WB-DWI protocol applying this sequence type seems necessary; and the value of such WB-DWI protocols for assessment of systemic oncological diseases needs to be investigated in further clinical studies.

Dynamic intravoxel incoherent motion imaging of skeletal muscle at rest and after exercise

The purpose of this work was to demonstrate the feasibility of intravoxel incoherent motion imaging (IVIM) for non-invasive quantification of perfusion and diffusion effects in skeletal muscle at rest and following exercise. After IRB approval, eight healthy volunteers underwent diffusion-weighted MRI of the forearm at 3 T and eight different b values between 0 and 500 s/mm(2) with a temporal resolution of 57 s per dataset. Dynamic images were acquired before and after a standardized handgrip exercise. Diffusion (D) and pseudodiffusion (D*) coefficients as well as the perfusion fraction (FP ) were measured in regions of interest in the flexor digitorum superficialis and profundus (FDS/FDP), brachioradialis, and extensor carpi radialis longus and brevis muscles by using a multi-step bi-exponential analysis in MATLAB. Parametrical maps were calculated voxel-wise. Differences in D, D*, and FP between muscle groups and between time points were calculated using a repeated measures analysis of variance with post hoc Bonferroni tests. Mean values and standard deviations at rest were the following: D*, 28.5 ± 11.4 × 10(-3) mm(2) /s; FP , 0.03 ± 0.01; D, 1.45 ± 0.09 × 10(-3) mm(2) /s. Changes of IVIM parameters were clearly visible on the parametrical maps. In the FDS/FDP, D* increased by 289 ± 236% (p < 0.029), FP by 138 ± 58% (p < 0.01), and D by 17 ± 9% (p < 0.01). A significant increase of IVIM parameters could also be detected in the brachioradialis muscle, which however was significantly lower than in the FDS/FDP. After 20 min, all parameters were still significantly elevated in the FDS/FDP but not in the brachioradialis muscle compared with the resting state. The IVIM approach allows simultaneous quantification of muscle perfusion and diffusion effects at rest and following exercise. It may thus provide a useful alternative to other non-invasive methods such as arterial spin labeling. Possible fields of interest for this technique include perfusion-related muscle diseases, such as peripheral arterial occlusive disease.

ZTE imaging with long-T2 suppression

Three-dimensional radial zero echo time (ZTE) imaging enables efficient direct MRI of tissues with rapid transverse relaxation. Yet, the feature of capturing signals with a wide range of T2 and T2 * values is accompanied by a lack of contrast between the corresponding tissues. In particular, the targeted short-T2 tissues may not be easily identified, and various approaches have been proposed to generate T2 contrast by reducing the long-T2 signal of water and/or fat. The aim of this work was to provide efficient long-T2 suppression for selective direct MRI of short-T2 tissues using the ZTE technique. For magnetization preparation, suppression pulses for water and fat were designed to provide both good T2 selectivity and off-resonance performance. To obtain high efficiency at short TRs, the pulses were applied in a segmented sequence scheme with minimized timing overhead, thus leading to a quasi-steady state of magnetization. The sequence timing was adjusted for optimal tissue contrast in musculoskeletal applications by means of simulations and experiments, incorporating both T2 and T1 of the involved tissues. The developed technique was employed for imaging of a lamb joint sample at 4.7 T. ZTE images were obtained with effective suppression of signals from tissues with long-T2 water, such as muscle or articular spaces, and fat. Hence, primarily short-T2 tissues were visible, such as bone and tendon. The MR image intensity of bone showed strong similarity with bone density imaged with micro-computed tomography.

Quantitative in vivo analysis of small bowel motility using MRI examinations in mice--proof of concept study

Small bowel motility analyses using magnetic resonance imaging (MRI) could reduce current invasive techniques in animal studies and comply with the 'three Rs' rule for human animal experimentation. Thus we investigated the feasibility of in vivo small bowel motility analyses in mice using dynamic MRI acquisitions. All experimental procedures were approved by the institutional animal care committee. Six C57BL/6 mice underwent MRI without additional preparation after isoflurane anaesthetization in the prone position on a 4.7 T small animal imager equipped with a linear polarized hydrogen birdcage whole-body mouse coil. Motility was assessed using a true fast imaging in a steady precession sequence in the coronal orientation (acquisition time per slice 512 ms, in-plane resolution 234 × 234 µm, matrix size 128 × 128, slice thickness 1 mm) over 30 s corresponding to 60 acquisitions. Motility was manually assessed measuring the small bowel diameter change over time. The resulting motility curves were analysed for the following parameters: contraction frequency per minute (cpm), maximal contraction amplitude (maximum to minimum [mm]), luminal diameter (mm) and luminal occlusion rate. Small bowel motility quantification was found to be possible in all animals with a mean small bowel contraction frequency of 10.67 cpm (SD ± 3.84), a mean amplitude of the contractions of 1.33 mm (SD ± 0.43) and a mean luminal diameter of 1.37 mm (SD ± 0.42). The mean luminal occlusion rate was 1.044 (SD ± 0.45%/100). The mean duration needed for a single motility assessment was 185 s (SD ± 54.02). Thus our study demonstrated the feasibility of an easy and time-sparing functional assessment for in vivo small bowel motility analyses in mice. This could improve the development of small animal models of intestinal diseases and provide a method similar to clinical MR examinations that is in concordance with the 'three Rs' for humane animal experimentation.

Hybrid PET/MR imaging: an algorithm to reduce metal artifacts from dental implants in Dixon-based attenuation map generation using a multiacquisition variable-resonance image combination sequence

It was the aim of this study to implement an algorithm modifying Dixon-based MR imaging datasets for attenuation correction in hybrid PET/MR imaging with a multiacquisition variable resonance image combination (MAVRIC) sequence to reduce metal artifacts.

METHODS

After ethics approval, in 8 oncologic patients with dental implants data were acquired in a trimodality setup with PET/CT and MR imaging. The protocol included a whole-body 3-dimensional dual gradient-echo sequence (Dixon) used for MR imaging-based PET attenuation correction and a high-resolution MAVRIC sequence, applied in the oral area compromised by dental implants. An algorithm was implemented correcting the Dixon-based μ maps using the MAVRIC in areas of Dixon signal voids. The artifact size of the corrected μ maps was compared with the uncorrected MR imaging μ maps.

RESULTS

The algorithm was robust in all patients. There was a significant reduction in mean artifact size of 70.5% between uncorrected and corrected μ maps from 697 ± 589 mm(2) to 202 ± 119 mm(2) (P = 0.016).

CONCLUSION

The proposed algorithm could improve MR imaging-based attenuation correction in critical areas, when standard attenuation correction is hampered by metal artifacts, using a MAVRIC.

Characterization of trabecular bone density with ultra-short echo-time MRI at 1.5, 3.0 and 7.0 T--comparison with micro-computed tomography

The goal of this study was to test the potential of ultra-short echo-time (UTE) MRI at 1.5, 3.0 and 7.0 T for depiction of trabecular bone structure (of the wrist bones), to evaluate whether T2* relaxation times of bone water and parametric maps of T2* of trabecular bone could be obtained at all three field strengths, and to compare the T2* relaxation times with structural parameters obtained from micro-computed tomography (micro-CT) as a reference standard. Ex vivo carpal bones of six wrists were excised en bloc and underwent MRI at 1.5, 3.0 and 7.0 T in a whole-body MR imager using the head coil. A three-dimensional radial fat-suppressed UTE sequence was applied with subsequent acquisitions, with six different echo times TE of 150, 300, 600, 1200, 3500 and 7000 µs. The T2* relaxation time and pixel-wise computed T2* parametric maps were compared with a micro-computed-tomography reference standard providing trabecular bone structural parameters including porosity (defined as the bone-free fraction within a region of interest), trabecular thickness, trabecular separation, trabecular number and fractal dimension (Dk). T2* relaxation curves and parametric maps could be computed from datasets acquired at all field strengths. Mean T2* relaxation times of trabecular bone were 4580 ± 1040 µs at 1.5 T, 2420 ± 560 µs at 3.0 T and 1220 ± 300 µs at 7.0 T, when averaged over all carpal bones. A positive correlation of T2* with trabecular bone porosity and trabecular separation, and a negative correlation of T2* relaxation time with trabecular thickness, trabecular number and fractal dimension, was detected (p < 0.01 for all field strengths and micro-CT parameters). We conclude that UTE MRI may be useful to characterize the structure of trabecular bone, comparable to micro-CT.

Rapid and robust pulmonary proton ZTE imaging in the mouse

Pulmonary MRI is challenging because of the low proton density and rapid transverse relaxation in the lung associated with microscopic magnetic field inhomogeneities caused by tissue-air interfaces. Therefore, low signal is obtained in gradient and spin echo proton images. Alternatively, non-proton MRI using hyperpolarized gases or radial techniques with ultrashort or zero TE have been proposed to image the lung. Also with the latter approach, the general challenge remains to provide full coverage of the lung at sufficient spatial resolution, signal-to-noise ratio (SNR) and image quality within a reasonable scan time. This task is further aggravated by physiological motion and is particularly demanding in small animals, such as mice. In this work, three-dimensional (3D) zero echo time (ZTE) imaging is employed for efficient pulmonary MRI. Four protocols with different averaging and respiratory triggering schemes are developed and compared with respect to image quality and SNR. To address the critical issue of background signal in ZTE images, a subtraction approach is proposed, providing images virtually free of disturbing signal from nearby hardware parts. The protocols are tested for pulmonary MRI in six mice at 4.7 T, consistently providing images of high quality with a 3D isotropic resolution of 313 µm and SNR values in the lung between 8.0 and 18.5 within scan times between 1 min 21 s and 4 min 44 s. A generally high robustness of the ZTE approach against motion is observed, whilst respiratory triggering further improves the SNR and visibility of image details. The developed techniques are expected to enable efficient preclinical animal studies in the lung and will also be of importance for human applications. Further improvements are expected from radiofrequency (RF) coils with increased SNR and reduced background signal.

The benefits of skull stripping in the normalization of clinical fMRI data

Establishing a reliable correspondence between lesioned brains and a template is challenging using current normalization techniques. The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed. Here we provide a first investigation into whether clinical fMRI benefits from skull stripping, based on data from a presurgical language localization task. Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches. Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space — particularly when used in combination with the New Segment normalization technique.

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First investigation of the possible effects of skull-stripping with clinical fMRI data.

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Comparison of standard and most recent normalization approaches.

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Skull stripping improves language localization in MNI space.

Mastering mouse lung transplantation from scratch--a track record

BACKGROUND

Mouse lung transplantation has evolved into an established scientific model that is currently used by an increasing number of research groups. Acquiring this technique without previous microsurgical knowledge is considered very difficult. Disclosing all the intraoperative failures and mistakes during the model's evolution will encourage all researchers who lack microsurgical skills that overcoming and eventually succeeding in this model is possible.

METHODS

Inbred (C57BL/6, BALB/c, SVG129) and CD1-outbred mice served as the transplant donors and recipients. The training procedure was performed by a surgeon not experienced in microsurgery, and arranged as follows: donor preparation until proof of functionality, graft implantation into deceased recipients, and graft implantation into surviving recipients until stable performance was achieved. The transplant's viability was controlled using micro-computed tomography imaging.

RESULTS

Donor preparation complications decreased from 43% after 1 month to 0% after 2 mo. The first functional donor was implanted at day 28, and the first successful implantation into a surviving recipient was performed at day 60 after six training recipients. Micro-computed tomography confirmed a ventilated and perfused graft. Intraoperative complications, mainly due to anastomosis failure, decreased from 58% after the first month to 15% at the latest assessment. The most recent implantation time was 75 ± 4.8 min, and the transplantation success rate was 82% ± 2.8%. A modified forceps considerably improved completion of the venous anastomosis.

CONCLUSIONS

Consistent success in the mouse lung transplantation model can be achieved even without pre-existing microsurgical skills. The surgery can be mastered within a reasonable period using a limited number of training animals. Procedure-related complications can be restricted to a minimum by applying key corrective steps at critical phases. This should encourage investigators without pre-expert knowledge in microsurgery to start to learn this research model.

Variability of clinical functional MR imaging results: a multicenter study

PURPOSE

To investigate intersite variability of clinical functional magnetic resonance (MR) imaging, including influence of task standardization on variability and use of various parameters to inform the clinician whether the reliability of a given functional localization is high or low.

MATERIALS AND METHODS

Local ethics committees approved the study; all participants gave written informed consent. Eight women and seven men (mean age, 40 years) were prospectively investigated at three experienced functional MR sites with 1.5- (two sites) or 3-T (one site) MR. Nonstandardized motor and highly standardized somatosensory versions of a frequently requested clinical task (localization of the primary sensorimotor cortex) were used. Perirolandic functional MR variability was assessed (peak activation variability, center of mass [COM] variability, intraclass correlation values, overlap ratio [OR], activation size ratio). Data quality measures for functional MR images included percentage signal change (PSC), contrast-to-noise ratio (CNR), and head motion parameters. Data were analyzed with analysis of variance and a correlation analysis.

RESULTS

Localization of perirolandic functional MR activity differed by 8 mm (peak activity) and 6 mm (COM activity) among sites. Peak activation varied up to 16.5 mm (COM range, 0.4-16.5 mm) and 45.5 mm (peak activity range, 1.8-45.5 mm). Signal strength (PSC, CNR) was significantly lower for the somatosensory task (mean PSC, 1.0% ± 0.5 [standard deviation]; mean CNR, 1.2 ± 0.4) than for the motor task (mean PSC, 2.4% ± 0.8; mean CNR, 2.9 ± 0.9) (P < .001, both). Intersite variability was larger with low signal strength (negative correlations between signal strength and peak activation variability) even if the task was highly standardized (mean OR, 22.0% ± 18.9 [somatosensory task] and 50.1% ± 18.8 [motor task]).

CONCLUSION

Clinical practice and clinical functional MR biomarker studies should consider that the center of task-specific brain activation may vary up to 16.5 mm, with the investigating site, and should maximize functional MR signal strength and evaluate reliability of local results with PSC and CNR.