Visceral fat mass dynamics in a 2-year randomized STrength versus ENdurance training trial in people with obesity.

AIM: To compare the effectiveness of strength versus endurance training on reducing visceral fat in individuals with obesity. MATERIALS AND METHODS: For the STrength versus ENdurance (STEN) 24-month randomized clinical trial, we assigned 239 participants with abdominal obesity to either strength or endurance training (two to three times a week, 60 min/training session) in addition to standard nutritional counselling to promote a healthy diet. Changes in abdominal visceral adipose tissue (VAT) area quantified by magnetic resonance imaging after 12 months were defined as a primary endpoint. RESULTS: Participants (aged 44 years, 74% women, body mass index: 37 kg/m2, mean VAT volume: 4050 cm3) had an approximately 50% retention rate and a 30% good training programme adherence at 12 months. There was no difference between strength and endurance training in VAT volume dynamics after 12 and 24 months (p = .13). Only in the good adherence group did we find a trend for reduced VAT volume in both training regimens. Independently of the exercise programme, there was a continuous trend for moderate loss of abdominal subcutaneous AT volume, body fat mass, body mass index and improved parameters of insulin sensitivity. Although parameters of physical fitness improved upon both exercise interventions, the dynamics of resting energy expenditure, glucose and lipid metabolism parameters were not different between the intervention groups and did not significantly improve during the 2-year trial (p > .05). CONCLUSIONS: Despite heterogeneous individual training responses, strength and endurance training neither affected VAT volume nor key secondary endpoints differently.

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer.

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm². Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. CONCLUSIONS: histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.

Navigated MRI-guided liver biopsies in a closed-bore scanner: experience in 52 patients.

OBJECTIVES: To evaluate clinical effectiveness and diagnostic efficiency of a navigation device for MR-guided biopsies of focal liver lesions in a closed-bore scanner. METHODS: In 52 patients, 55 biopsies were performed. An add-on MR navigation system with optical instrument tracking was used for image guidance and biopsy device insertion outside the bore. Fast control imaging allowed visualization of the true needle position at any time. The biopsy workflow and procedure duration were recorded. Histological analysis and clinical course/outcome were used to calculate sensitivity, specificity and diagnostic accuracy. RESULTS: Fifty-four of 55 liver biopsies were performed successfully with the system. No major and four minor complications occurred. Mean tumour size was 23 ± 14 mm and the skin-to-target length ranged from 22 to 177 mm. In 39 cases, access path was double oblique. Sensitivity, specificity and diagnostic accuracy were 88 %, 100 % and 92 %, respectively. The mean procedure time was 51 ± 12 min, whereas the puncture itself lasted 16 ± 6 min. On average, four control scans were taken. CONCLUSIONS: Using this navigation device, biopsies of poorly visible and difficult accessible liver lesions could be performed safely and reliably in a closed-bore MRI scanner. The system can be easily implemented in clinical routine workflow. KEY POINTS: • Targeted liver biopsies could be reliably performed in a closed-bore MRI. • The navigation system allows for image guidance outside of the scanner bore. • Assisted MRI-guided biopsies are helpful for focal lesions with a difficult access. • Successful integration of the method in clinical workflow was shown. • Subsequent system installation in an existing MRI environment is feasible.

Predictive accuracy of single- and multi-slice MRI for the estimation of total visceral adipose tissue in overweight to severely obese patients.

The quantification of visceral adipose tissue (VAT) is increasingly being considered for risk assessment and treatment monitoring in obese patients, but is generally time-consuming. The goals of this work were to semi-automatically segment and quantify VAT areas of MRI slices at previously proposed anatomical landmarks and to evaluate their predictive power for whole-abdominal VAT volumes on a relatively large number of patients. One-hundred and ninety-seven overweight to severely obese patients (65 males; body mass index, 33.3 ± 3.5 kg/m(2); 132 females; body mass index, 34.3 ± 3.2 kg/m(2)) underwent MRI examination. Total VAT volumes (VVAT-T ) of the abdominopelvic cavity were quantified by retrospective analysis of two-point Dixon MRI data (active-contour segmentation, visual correction and histogram analysis). VVAT-T was then compared with VAT areas determined on one or five slices defined at seven anatomical landmarks (lumbar intervertebral spaces, umbilicus and femoral heads) and corresponding conversion factors were determined. Statistical measures were the coefficients of variation and standard deviations σ1 and σ5 of the difference between predicted and measured VAT volumes (Bland-Altman analysis). VVAT-T was 6.0 ± 2.0 L (2.5-11.2 L) for males and 3.2 ± 1.4 L (0.9-7.7 L) for females. The analysis of five slices yielded a better agreement than the analysis of single slices, required only a little extra time (4 min versus 2 min) and was substantially faster than whole-abdominal assessment (24 min). Best agreements were found at intervertebral spaces L3-L4 for females (σ5/1 = 523/608 mL) and L2-L3 for males (σ5/1 = 613/706 mL). Five-slice VAT volume estimates at the level of lumbar disc L3-L4 for females and L2-L3 for males can be obtained within 4 min and were a reliable predictor for abdominopelvic VAT volume in overweight to severely adipose patients. One-slice estimates took only 2 min and were slightly less accurate. These findings may contribute to the implementation of analytical methods for fast and reliable (routine) estimation of VAT volumes in obese patients.

Non-invasive estimation of prostate cancer aggressiveness using diffusion-weighted MRI and 3D proton MR spectroscopy at 3.0 T.

BACKGROUND: Clinical management of prostate cancer increasingly aims to distinguish aggressive types that require immediate and radical treatment from indolent tumors that are candidates for watchful waiting. This requires reliable and reproducible parameters to effectively control potential cancer progression. Magnetic resonance imaging (MRI) may provide a non-invasive means for this purpose. PURPOSE: To assess the value of diffusion-weighted imaging and proton MR spectroscopy for the prediction of prostate cancer (PCa) aggressiveness. MATERIAL AND METHODS: In 39 of 64 consecutive patients who underwent endorectal 3-T MRI prior to radical prostatectomy, prostate specimens were analyzed as whole-mount step sections. Apparent diffusion coefficient (ADC), normalized ADC (nADC: tumor/healthy tissue), choline/citrate (CC), and (choline + creatine)/citrate (CCC) ratios were correlated with Gleason scores (GS) from histopathological results. The power to discriminate low (GS ≤ 6) from higher-risk (GS ≥ 7) tumors was assessed with receiver operating characteristics (area under the curve [AUC]). Resulting threshold values were used by a blinded reader to distinguish between aggressive and indolent tumors. RESULTS: Ninety lesions (1 × GS = 5, 41 × GS = 6, 36 × GS = 7, 12 × GS = 8) were considered. nADC (AUC = 0.90) showed a higher discriminatory power than ADC (AUC = 0.79). AUC for CC and CCC were 0.73 and 0.82, respectively. Using either nADC < 0.46 or CCC > 1.3, as well as both criteria for aggressive PCa, the reader correctly identified aggressive and indolent tumors in 31 (79%), 28 (72%), and 33 of 39 patients (85%), respectively. Predictions of tumor aggressiveness from TRUS-guided biopsies were correct in 27 of 36 patients (75%). CONCLUSION: The combination of a highly sensitive normalized ADC with a highly specific CCC was found to be well suited to prospectively estimate PCa aggressiveness with a similar diagnostic accuracy as biopsy results.

Comparison of T1 relaxation times in adipose tissue of severely obese patients and healthy lean subjects measured by 1.5 T MRI.

Subcutaneous (SAT) and visceral adipose tissue (VAT) differ in composition, endocrine function and localization in the body. VAT is considered to play a role in the pathogenesis of insulin resistance, type 2 diabetes, fatty liver disease, and other obesity-related disorders. It has been shown that the amount, distribution, and (cellular) composition of adipose tissue (AT) correlate well with metabolic conditions. In this study, T1 relaxation times of AT were measured in severely obese subjects and compared with those of healthy lean controls. Here, we tested the hypothesis that T1 relaxation times of AT differ between lean and obese individuals, but also between VAT and SAT as well as superficial (sSAT) and deep SAT (dSAT) in the same individual. Twenty severely obese subjects (BMI 41.4 ± 4.8 kg/m(2) ) and ten healthy lean controls matched for age (BMI 21.5 ± 1.9 kg/m(2) ) underwent MRI at 1.5 T using a single-shot fast spin-echo sequence (short-tau inversion recovery) at six different inversion times (TI range 100-1000 ms). T1 relaxation times were computed for all subjects by fitting the TI -dependent MR signal intensities of user-defined regions of interest in both SAT and VAT to a model function. T1 times in sSAT and dSAT were only measured in obese patients. For both obese patients and controls, the T1 times of SAT (275 ± 14 and 301 ± 12 ms) were significantly (p < 0.01) shorter than the respective values in VAT (294 ± 20 and 360 ± 35 ms). Obese subjects also showed significant (p < 0.01) T1 differences between sSAT (268 ± 11 ms) and dSAT (281 ± 19 ms). More important, T1 differences in both SAT and VAT were highly significant (p < 0.001) between obese patients and healthy subjects. The results of our pilot study suggest that T1 relaxation times differ between severely obese patients and lean controls, and may potentially provide an additional means for the non-invasive assessment of AT conditions and dysfunction.

Angle-sensitive MRI for quantitative analysis of fiber-network deformations in compressed cartilage.

PURPOSE: To demonstrate the feasibility of a novel experimental method to quantitatively analyze fiber-network deformation in compressed cartilage by angle-sensitive magnetic resonance imaging (MRI) of cartilage. METHODS: Three knee cartilage samples of an adult sheep were imaged in a high-resolution MRI scanner at 7 T. Main fiber orientation and its "offset" from the direction perpendicular to the bone-cartilage boundary were derived from MR images taken at different orientations with respect to B0. Bending of the collagen fibers was determined from weight-bearing MRI with the load (up to 1.0 MPa) applied over the whole sample surface. A "fascicle" model of the cartilage ultrastructure was assumed to analyze characteristic intensity variations in T2-weighted images under load. RESULTS: T2-weighted MR images showed a strong variation of the signal intensities with sample orientation. In the T2-weighted weight-bearing series, regions of high signal intensity underwent shifts from the lateral to the central parts in all three cartilage samples. The bending of the collagen fibers was determined to be 27.2°, 35.4°, and 40.0° per MPa, respectively. CONCLUSION: Assuming a "fascicle" model, the presented MRI method provides quantitative measures of structural adjustments in compressed cartilage. Our preliminary analysis suggests that cartilage fiber deformation includes both bending and crimping.

An algorithm for the calculation of three-dimensional collagen fiber orientation in ligaments using angle-sensitive MRI.

A method based on angle-sensitive magnetic resonance imaging for determining unknown orientations of collagen fibers in ligaments is presented. Collagen fibers were stepwise rotated around two independent axes within a 3T magnetic resonance tomograph (from 0° to 180°, step size=10°). Analyzing the magnetic resonance signal intensity of each voxel as a function of the rotation angle, directions were calculated by means of a computational algorithm. The accuracy of the algorithm was validated using 1000 random test directions, revealing an average deviation of 4.4° (median±standard deviation: 2.7°±9°). Subsequently, the presented method was applied to three specimens of the human iliotibial tract mounted in different directions in a rotatable plastic box. Polarized light microscopy was used to verify parallel alignment of the collagen fibers in the three specimens. The calculated directions were compared with the directions of the specimens. Analyzing each voxel separately, average deviations (median±standard deviation) in the three specimens were: 11.2° (3.6°±20.4°), 12° (5°±24.1°), and 20.4° (8.7°±27°). If the magnetic resonance signal intensity of each voxel was averaged with the intensity of immediately neighboring voxels, average deviations (median±standard deviation) were 8.5° (3.6°±17.4°), 6.2° (0°±18°), and 9.2° (5°±19.2°). The presented method has the potential to be applied in situ to anatomical structures like cartilage, ligaments, tendons and fascia.

In vivo MRI analysis of depth-dependent ultrastructure in human knee cartilage at 7 T.

Signal intensities of T2-weighted magnetic resonance images depend on the local fiber arrangement in hyaline cartilage. The aims of this study were to determine whether angle-sensitive MRI at 7 T can be used to quantify the cartilage ultrastructure of the knee in vivo and to assess potential differences with age. Ten younger (21-30) and ten older (55-76 years old) healthy volunteers were imaged with a T2-weighted spin-echo sequence in a 7 T whole-body MRI. A "fascicle" model was assumed to describe the depth-dependent fiber arrangement of cartilage. The R/T boundary positions between radial and transitional zones were assessed from intensity profiles in small regions of interest in the femur and tibia, and normalized to cartilage thickness using logistic curve fits. The quality of our highly resolved (0.3 × 0.3 × 1.0 mm(3)) MR cartilage images were high enough for quantitative analysis (goodness of fit R(2) = 0.91 ± 0.09). Between younger and older subjects, normalized positions of the R/T boundary, with value 0 at the bone-cartilage interface and 1 at the cartilage surface, were significantly (p < 0.05) different in femoral (0.51 ± 0.12 versus 0.41 ± 0.10), but not in tibial cartilage (0.65 ± 0.11 versus 0.57 ± 0.09, p = 0.119). Within both age groups, differences between femoral and tibial R/T boundaries were significant. Using a fascicle model and angle-sensitive MRI, the depth-dependent anisotropic fiber arrangement of knee cartilage could be assessed in vivo from a single 7 T MR image. The derived quantitative parameter, thickness of the radial zone, may serve as an indicator of the structural integrity of cartilage. This method may potentially be suitable to detect and monitor early osteoarthritis because the progressive disintegration of the anisotropic network is also indicative of arthritic changes in cartilage.

Novel technique for MR elastography of the prostate using a modified standard endorectal coil as actuator.

PURPOSE: To present a novel method for MR elastography (MRE) of the prostate at 3 Tesla using a modified endorectal imaging coil. MATERIALS AND METHODS: A commercial endorectal coil was modified to dynamically generate mechanical stress (contraction and dilation) in a prostate phantom with embedded phantom "lesions" (6 mm diameter) and in a porcine model. Resulting tissue displacements were measured with a motion-sensitive EPI sequence at actuation frequencies of 50-200 Hz. Maps of shear modulus G were calculated from the measured phase-difference shear-wave patterns. RESULTS: In the G maps of the phantom, "lesions" were easily discernible against the background. The average G values of regions of interest placed in the "lesion" (8.2 ± 1.9 kPa) were much higher than those in the background (3.6 ± 1.4 kPa) but systematically lower than values reported by the vendor (13.0 ± 1.0 and 6.7 ± 0.7 kPa, respectively). In the porcine model, shear waves could be generated and measured shear moduli were substantially different for muscle (7.1 ± 2.0 kPa), prostate (3.0 ± 1.4 kPa), and bulbourethral gland (5.6 ± 1.9 kPa). CONCLUSION: An endorectal MRE concept is technically feasible. The presented technique will allow for simultaneous MRE and MRI acquisitions using a commercial base device with minor, MR-conditional modifications. The diagnostic value needs to be determined in further trials.

Software for automated MRI-based quantification of abdominal fat and preliminary evaluation in morbidly obese patients.

PURPOSE: To present software for supervised automatic quantification of visceral and subcutaneous adipose tissue (VAT, SAT) and evaluates its performance in terms of reliability, interobserver variation, and processing time, since fully automatic segmentation of fat-fraction magnetic resonance imaging (MRI) is fast but susceptible to anatomical variations and artifacts, particularly for advanced stages of obesity. MATERIALS AND METHODS: Twenty morbidly obese patients (average BMI 44 kg/m(2) ) underwent 1.5-T MRI using a double-echo gradient-echo sequence. Fully automatic analysis (FAA) required no user interaction, while supervised automatic analysis (SAA) involved review and manual correction of the FAA results by two observers. Standard of reference was provided by manual segmentation analysis (MSA). RESULTS: Average processing times per patient were 6, 6+4, and 21 minutes for FAA, SAA, and MSA (P < 0.001), respectively. For VAT/SAT assessment, Pearson correlation coefficients, mean (bias), and standard deviations of the differences were R = 0.950, +0.003, and 0.043 between FAA and MSA and R = 0.981, +0.009, and 0.027 between SAA and MSA. Interobserver variation and intraclass correlation were 3.1% and 0.996 for SAA, and 6.6% and 0.986 for MSA, respectively. CONCLUSION: The presented supervised automatic approach provides a reliable option for MRI-based fat quantification in morbidly obese patients and was much faster than manual analysis.

Diagnostic value of ADC in patients with prostate cancer: influence of the choice of b values.

OBJECTIVES: To evaluate the influence of the choice of b values on the diagnostic value of the apparent diffusion coefficient (ADC) for detection and grading of prostate cancer (PCa). METHODS: Forty-one patients with biopsy-proven PCa underwent endorectal 3-T MRI before prostatectomy. Different combinations of b values (0-800 s/mm(2)) were used to calculate four representative ADC maps. Mean ADCs of tumours and non-malignant tissue were determined. Tumour appearance on different ADC maps was rated by three radiologists as good, fair or poor by assigning a visual score (VS) of 2, 1 or 0, respectively. Differences in the ADC values with the choice of b values were analysed using one-way ANOVA. RESULTS: Choice of b values had a highly (P < 0.001) significant influence on the absolute ADC in each tissue. Maps using b = [50, 800] and [0, 800] were rated best (VS= 1.6 ± 0.3) and second best (1.1 ± 0.3, P < 0.001), respectively. For low-grade carcinomas (Gleason score ≤ 6, 13/41 patients), only the former choice received scores better than fair (VS = 1.4 ± 0.3). Mean tumour ADCs showed significant negative correlation (Spearman's ρ -0.38 to -0.46, P < 0.05) with Gleason score. CONCLUSIONS: Absolute ADC values strongly depend on the choice of b values and therefore should be used with caution for diagnostic purposes. A minimum b value greater than zero is recommended for ADC calculation to improve the visual assessment of PCa in ADC maps. KEY POINTS: • Absolute ADC values are highly dependent on the choice of b values. • Absolute ADC thresholds should be used carefully to predict tumour aggressiveness. • Subjective ratings of ADC maps involving b = 0 s/mm ( 2 ) are poor to fair. • Minimum b value greater than 0 s/mm ( 2 ) is recommended for ADC calculation.

Suitability of miniature inductively coupled RF coils as MR-visible markers for clinical purposes.

PURPOSE: MR-visible markers have already been used for various purposes such as image registration, motion detection, and device tracking. Inductively coupled RF (ICRF) coils, in particular, provide a high contrast and do not require connecting wires to the scanner, which makes their application highly flexible and safe. This work aims to thoroughly characterize the MR signals of such ICRF markers under various conditions with a special emphasis on fully automatic detection. METHODS: The small markers consisted of a solenoid coil that was wound around a glass tube containing the MR signal source and tuned to the resonance frequency of a 1.5 T MRI. Marker imaging was performed with a spoiled gradient echo sequence (FLASH) and a balanced steady-state free precession (SSFP) sequence (TrueFISP) in three standard projections. The signal intensities of the markers were recorded for both pulse sequences, three source materials (tap water, distilled water, and contrast agent solution), different flip angles and coil alignments with respect to the B(0) direction as well as for different marker positions in the entire imaging volume (field of view, FOV). Heating of the ICRF coils was measured during 10-min RF expositions to three conventional pulse sequences. Clinical utility of the markers was assessed from their performance in computer-aided detection and in defining double oblique scan planes. RESULTS: For almost the entire FOV (±215 mm) and an estimated 82% of all possible RF coil alignments with respect to B(0), the ICRF markers generated clearly visible MR signals and could be reliably localized over a large range of flip angles, in particular with the TrueFISP sequence (0.3°-4.0°). Generally, TrueFISP provided a higher marker contrast than FLASH. RF exposition caused a moderate heating (≤5 °C) of the ICRF coils only. CONCLUSIONS: Small ICRF coils, imaged at low flip angles with a balanced SSFP sequence showed an excellent performance under a variety of experimental conditions and therefore make for a reliable, compact, flexible, and relatively safe marker for clinical use.

Flexible add-on solution for MR image-guided interventions in a closed-bore scanner environment.

MRI is of great clinical utility for the guidance of various diagnostic and therapeutic procedures. In a standard closed-bore scanner, the simplest approach is to manipulate the instrument outside the bore and move the patient into the bore for reference and control imaging only. Without navigational assistance, however, such an approach can be difficult, inaccurate, and time consuming. Therefore, an add-on navigation solution is described that addresses these limitations. Patient registration is established by an automatic, robust, and fast (<30 sec) localization of table-mounted MR reference markers and the instrument is tracked optically. Good hand-eye coordination is provided by following the virtual instrument on MR images that are reconstructed in real time from the reference data. Needle displacements of 2.2 +/- 0.6 mm and 3.9 +/- 2.4 mm were determined in a phantom (P < 0.05), depending on whether the reference markers were placed at smaller (98-139 mm) or larger (147-188 mm) distances from the isocenter. Clinical functionality of the navigation concept is demonstrated by a double oblique, subscapular hook-wire insertion in a patient with a body mass index of 30.1 kg/m(2). Ease of use, compactness, and flexibility of this technique suggest that it can be used for many other procedures in different body regions. More patient cases are needed to evaluate clinical performance and workflow.

Comparison of Two Mathematical Models of Cellularity Calculation.

OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a logistic tumor growth model were proposed to predict tumor cellularity with DWI and DCE. The purpose of this study was to proof these formulas. METHODS: 16 patients with head and neck squamous cell carcinomas were included into the study. There were 2 women and 14 men with a mean age of 57.0 ± 7.5 years. In every case, tumor cellularity was calculated using the proposed formulas by Atuegwu et al. In every case, also tumor cell count was estimated on histopathological specimens as an average cell count per 2 to 5 high-power fields. RESULTS: There was no significant correlation between the calculated cellularity and histopathologically estimated cell count by using the formula based on apparent diffusion coefficient (ADC) values. A moderate positive correlation (r=0.515, P=.041) could be identified by using the formula including ADC and Ve values. CONCLUSIONS: The formula including ADC and Ve values is more sensitive to predict tumor cellularity than the formula including ADC values only.

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

OBJECTIVE: Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. MATERIALS AND METHODS: Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm2. Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (Ktrans), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. RESULTS: Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, Ktrans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and Ktrans min (p=0.58, P=0.0007), and ADC P75 and Ktrans P10 (p=0.56, P=0.001). Only four Kep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between Kep max and ADC mode (p=-0.47, P=0.008). CONCLUSION: Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC.

Histogram Analysis of T1-Weighted, T2-Weighted, and Postcontrast T1-Weighted Images in Primary CNS Lymphoma: Correlations with Histopathological Findings-a Preliminary Study.

PURPOSE: Previously, some reports mentioned that magnetic resonance imaging (MRI) can predict histopathological features in primary CNS lymphoma (PCNSL). The reported data analyzed diffusion-weighted imaging findings. The aim of this study was to investigate possible associations between histopathological findings, such as tumor cellularity, nucleic areas and proliferation index Ki-67, and signal intensity on T1-weighted and T2-weighted images in PCNSL. PROCEDURES: For this study, 18 patients with PCNSL were retrospectively investigated by histogram analysis on precontrast and postcontrast T1-weighted and fluid-attenuated inversion recovery (FLAIR) images. For every patient, histopathology parameters, nucleic count, total nucleic area, and average nucleic area, as well as Ki-67 index, were estimated. RESULTS: Correlation analysis identified several statistically significant associations. Skewness derived from precontrast T1-weighted images correlated with Ki-67 index (p = - 0.55, P = 0.028). Furthermore, entropy derived from precontrast T1-weighted images correlated with average nucleic area (p = 0.53, P = 0.04). Several parameters from postcontrast T1-weighted images correlated with nucleic count: maximum signal intensity (p = 0.59, P = 0.017), P75 (p = 0.56, P = 0.02), and P90 (p = 0.52, P = 0.04) as well as SD (p = 0.58, P = 0.02). Maximum signal intensity derived from FLAIR sequence correlated with nucleic count (p = 0.50, P = 0.03). CONCLUSION: Histogram-derived parameters of conventional MRI sequences can reflect different histopathological features in PSNCL.

Whole Tumor Histogram-profiling of Diffusion-Weighted Magnetic Resonance Images Reflects Tumorbiological Features of Primary Central Nervous System Lymphoma.

PURPOSE: Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. PROCEDURES: Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. RESULTS: The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. CONCLUSIONS: Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis.

Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

PURPOSE: Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status. PROCEDURES: Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed. RESULTS: The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas. CONCLUSIONS: ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC values vary between MRI scanners of different vendors and field strengths, their use is more limited in the presurgical setting.