The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

A proof-of-concept pipeline to guide evaluation of tumor tissue perfusion by dynamic contrast-agent imaging: Direct simulation and inverse tracer-kinetic procedures.

Dynamic contrast-enhanced (DCE) perfusion imaging has shown great potential to non-invasively assess cancer development and its treatment by their characteristic tissue signatures. Different tracer kinetics models are being applied to estimate tissue and tumor perfusion parameters from DCE perfusion imaging. The goal of this work is to provide an in silico model-based pipeline to evaluate how these DCE imaging parameters may relate to the true tissue parameters. As histology data provides detailed microstructural but not functional parameters, this work can also help to better interpret such data. To this aim in silico vasculatures are constructed and the spread of contrast agent in the tissue is simulated. As a proof of principle we show the evaluation procedure of two tracer kinetic models from in silico contrast-agent perfusion data after a bolus injection. Representative microvascular arterial and venous trees are constructed in silico. Blood flow is computed in the different vessels. Contrast-agent input in the feeding artery, intra-vascular transport, intra-extravascular exchange and diffusion within the interstitial space are modeled. From this spatiotemporal model, intensity maps are computed leading to in silico dynamic perfusion images. Various tumor vascularizations (architecture and function) are studied and show spatiotemporal contrast imaging dynamics characteristic of in vivo tumor morphotypes. The Brix II also called 2CXM, and extended Tofts tracer-kinetics models common in DCE imaging are then applied to recover perfusion parameters that are compared with the ground truth parameters of the in silico spatiotemporal models. The results show that tumor features can be well identified for a certain permeability range. The simulation results in this work indicate that taking into account space explicitly to estimate perfusion parameters may lead to significant improvements in the perfusion interpretation of the current tracer-kinetics models.

Periportal steatosis in mice affects distinct parameters of pericentral drug metabolism.

Little is known about the impact of morphological disorders in distinct zones on metabolic zonation. It was described recently that periportal fibrosis did affect the expression of CYP proteins, a set of pericentrally located drug-metabolizing enzymes. Here, we investigated whether periportal steatosis might have a similar effect. Periportal steatosis was induced in C57BL6/J mice by feeding a high-fat diet with low methionine/choline content for either two or four weeks. Steatosis severity was quantified using image analysis. Triglycerides and CYP activity were quantified in photometric or fluorometric assay. The distribution of CYP3A4, CYP1A2, CYP2D6, and CYP2E1 was visualized by immunohistochemistry. Pharmacokinetic parameters of test drugs were determined after injecting a drug cocktail (caffeine, codeine, and midazolam). The dietary model resulted in moderate to severe mixed steatosis confined to periportal and midzonal areas. Periportal steatosis did not affect the zonal distribution of CYP expression but the activity of selected CYPs was associated with steatosis severity. Caffeine elimination was accelerated by microvesicular steatosis, whereas midazolam elimination was delayed in macrovesicular steatosis. In summary, periportal steatosis affected parameters of pericentrally located drug metabolism. This observation calls for further investigations of the highly complex interrelationship between steatosis and drug metabolism and underlying signaling mechanisms.

Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue.

Many physiological processes and pathological phenomena in the liver tissue are spatially heterogeneous. At a local scale, biomarkers can be quantified along the axis of the blood flow, from portal fields (PFs) to central veins (CVs), i.e., in zonated form. This requires detecting PFs and CVs. However, manually annotating these structures in multiple whole-slide images is a tedious task. We describe and evaluate a fully automated method, based on a convolutional neural network, for simultaneously detecting PFs and CVs in a single stained section. Trained on scans of hematoxylin and eosin-stained liver tissue, the detector performed well with an F1 score of 0.81 compared to annotation by a human expert. It does, however, not generalize well to previously unseen scans of steatotic liver tissue with an F1 score of 0.59. Automated PF and CV detection eliminates the bottleneck of manual annotation for subsequent automated analyses, as illustrated by two proof-of-concept applications: We computed lobulus sizes based on the detected PF and CV positions, where results agreed with published lobulus sizes. Moreover, we demonstrate the feasibility of zonated quantification of biomarkers detected in different stainings based on lobuli and zones obtained from the detected PF and CV positions. A negative control (hematoxylin and eosin) showed the expected homogeneity, a positive control (glutamine synthetase) was quantified to be strictly pericentral, and a plausible zonation for a heterogeneous F4/80 staining was obtained. Automated detection of PFs and CVs is one building block for automatically quantifying physiologically relevant heterogeneity of liver tissue biomarkers. Perspectively, a more robust and automated assessment of zonation from whole-slide images will be valuable for parameterizing spatially resolved models of liver metabolism and to provide diagnostic information.

Reproducibility of dynamic contrast enhanced MRI derived transfer coefficient Ktrans in lung cancer.

Dynamic contrast enhanced MRI (DCE-MRI) is a useful method to monitor therapy assessment in malignancies but must be reliable and comparable for successful clinical use. The aim of this study was to evaluate the inter- and intrarater reproducibility of DCE-MRI in lung cancer. At this IRB approved single centre study 40 patients with lung cancer underwent up to 5 sequential DCE-MRI examinations. DCE-MRI were performed using a 3.0T system. The volume transfer constant Ktrans was assessed by three readers using the two-compartment Tofts model. Inter- and intrarater reliability and agreement was calculated by wCV, ICC and their 95% confident intervals. DCE-MRI allowed a quantitative measurement of Ktrans in 107 tumors where 91 were primary carcinomas or intrapulmonary metastases and 16 were extrapulmonary metastases. Ktrans showed moderate to good interrater reliability in overall measurements (ICC 0.716-0.841; wCV 30.3-38.4%). Ktrans in pulmonary lesions ≥ 3 cm showed a good to excellent reliability (ICC 0.773-0.907; wCV 23.0-29.4%) compared to pulmonary lesions < 3 cm showing a moderate to good reliability (ICC 0.710-0.889; wCV 31.6-48.7%). Ktrans in intrapulmonary lesions showed a good reliability (ICC 0.761-0.873; wCV 28.9-37.5%) compared to extrapulmonary lesions with a poor to moderate reliability (ICC 0.018-0.680; wCV 28.1-51.8%). The overall intrarater agreement was moderate to good (ICC 0.607-0.795; wCV 24.6-30.4%). With Ktrans, DCE MRI offers a reliable quantitative biomarker for early non-invasive therapy assessment in lung cancer patients, but with a coefficient of variation of up to 48.7% in smaller lung lesions.

Radiofrequency transmit calibration: A multi-center evaluation of vendor-provided radiofrequency transmit mapping methods.

PURPOSE: To determine the accuracy and test-retest repeatability of fast radiofrequency (RF) transmit measurement approaches used in Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI). Spatial variation in the transmitted RF field introduces bias and increased variance in quantitative DCE-MRI metrics including tracer kinetic parameter maps. If unaccounted for, these errors can dominate all other sources of bias and variance. The amount and pattern of variation depend on scanner-specific hardware and software. METHODS: Human tissue mimicking torso and brain phantoms were constructed. RF transmit maps were measured and compared across eight different commercial scanners, from three major vendors, and three clinical sites. Vendor-recommended rapid methods for RF mapping were compared to a slower reference method. Imaging was repeated at all sites after 2 months. Ranges and magnitude of RF inhomogeneity were compared scanner-wise at two time points. Limits of Agreement of vendor-recommended methods and double-angle reference method were assessed. RESULTS: At 3 T, B1 + inhomogeneity spans across 35% in the head and 120% in the torso. Fast vendor provided methods are within 30% agreement with the reference double angle method for both the head and the torso phantom. CONCLUSIONS: If unaccounted for, B1 + inhomogeneity can severely impact tracer-kinetic parameter estimation. Depending on the scanner, fast vendor provided B1 + mapping sequences allow unbiased and reproducible measurements of B1 + inhomogeneity to correct for this source of bias.

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials.

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.

Observer variability of reference tissue selection for relativecerebral blood volume measurements in glioma patients.

OBJECTIVES: To assess observer variability of different reference tissues used for relative CBV (rCBV) measurements in DSC-MRI of glioma patients. METHODS: In this retrospective study, three observers measured rCBV in DSC-MR images of 44 glioma patients on two occasions. rCBV is calculated by the CBV in the tumour hotspot/the CBV of a reference tissue at the contralateral side for normalization. One observer annotated the tumour hotspot that was kept constant for all measurements. All observers annotated eight reference tissues of normal white and grey matter. Observer variability was evaluated using the intraclass correlation coefficient (ICC), coefficient of variation (CV) and Bland-Altman analyses. RESULTS: For intra-observer, the ICC ranged from 0.50-0.97 (fair-excellent) for all reference tissues. The CV ranged from 5.1-22.1 % for all reference tissues and observers. For inter-observer, the ICC for all pairwise observer combinations ranged from 0.44-0.92 (poor-excellent). The CV ranged from 8.1-31.1 %. Centrum semiovale was the only reference tissue that showed excellent intra- and inter-observer agreement (ICC>0.85) and lowest CVs (<12.5 %). Bland-Altman analyses showed that mean differences for centrum semiovale were close to zero. CONCLUSION: Selecting contralateral centrum semiovale as reference tissue for rCBV provides the lowest observer variability. KEY POINTS: • Reference tissue selection for rCBV measurements adds variability to rCBV measurements. • rCBV measurements vary depending on the choice of reference tissue. • Observer variability of reference tissue selection varies between poor and excellent. • Centrum semiovale as reference tissue for rCBV provides the lowest observer variability.

Landmark-based evaluation of a deformable motion correction for DCE-MRI of the liver.

PURPOSE: Annotation of meaningful landmark ground truth on DCE-MRI is difficult and laborious. Motion correction methods applied to DCE-MRI of the liver are thus mostly evaluated using qualitative or indirect measures. We propose a novel landmark annotation scheme that facilitates the generation of landmark ground truth on larger clinical datasets. METHODS: In our annotation scheme, landmarks are equally distributed over all time points of all available dataset cases and annotated by multiple observers on a per-pair basis. The scheme is used to annotate 26 DCE-MRI of the liver. A subset of the ground truth is used to optimize parameters of a deformable motion correction. Several variants of the motion correction are evaluated on the remaining cases with respect to distances of corresponding landmarks after registration, deformation field properties, and qualitative measures. RESULTS: A landmark ground truth on 26 cases could be generated in under 12 h per observer with a mean inter-observer distance below the mean voxel diagonal. Furthermore, the landmarks are spatially well distributed within the liver. Parameter optimization significantly improves the performance of the motion correction, and landmark distance after registration is 2 mm. Qualitative evaluation of the motion correction reflects the quantitative results. CONCLUSIONS: The annotation scheme makes a landmark-based evaluation of motion corrections for hepatic DCE-MRI practically feasible for larger clinical datasets. The comparably large number of cases enables both optimization and evaluation of motion correction methods.

Pre-treatment estimation of future remnant liver function using gadoxetic acid MRI in patients with HCC.

BACKGROUND & AIMS: This study aimed to determine whether the predicted remnant liver function on dynamic hepatocyte-specific contrast media-enhanced magnetic resonance (DHCE-MR) imaging correlates with the results of the indocyanin green retention test (ICG R15) after hepatic resection or radiofrequency ablation (RFA). METHODS: This prospective multicenter study was approved by the Institutional Review Boards of each hospital. Informed consents were obtained from all. DHCE-MRI and ICG R15 were performed in 57 patients scheduled to undergo hepatectomy or RFA for hepatocellular carcinoma, once before treatment and repeated on post-treatment day 3. In nine donors and three recipients, DHCE-MRI and ICG R15 were performed only preoperatively. The predicted remnant liver function (HEFml) was estimated using the hepatic extraction fraction (HEF) multiplied by the remnant liver volume, and compared with post-treatment ICG R15. Intra-individual heterogeneity of HEF was assessed using pooled coefficients of variation (CV) among hepatic segments. Finally, development of post-treatment hepatic failure was assessed according to the 50-50 criteria on post-treatment day 5. RESULTS: Predicted remnant HEFml showed a negative correlation with post-treatment ICG R15 (r=-0.45, p=0.001), whereas liver volume did not (p>0.05). There were significant correlations between pre-treatment HEFml and pre-treatment ICG R15 (r=-0.33, p=0.006) and between post-treatment HEFml and post-treatment ICG R15 (r=-0.54, p<0.001). Pooled CV among segmental HEFs was 12.6%. No patients showed post-treatment liver failure on post-treatment day 5. CONCLUSIONS: DHCE-MRI using Gd-EOB-DTPA was able to provide both global and segmental liver function information, and post-treatment remnant liver function predicted on pre-treatment DHCE-MRI showed a significant negative correlation with post-treatment ICG R15. LAY SUMMARY: Post-treatment liver function could be predicted at pre-treatment DHCE-MRI. Liver function was heterogeneous among the liver segments. Liver anatomy, disease extent, and underlying liver function can be assessed in one DHCE-MRI examination. CLINICAL TRIAL NUMBER: ClinicalTrials.gov number, NCT01490203.

Increased microcirculation detected by dynamic contrast-enhanced magnetic resonance imaging is of prognostic significance in asymptomatic myeloma.

This prospective study aimed to investigate the prognostic significance of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) as a non-invasive imaging technique delivering the quantitative parameters amplitude A (reflecting blood volume) and exchange rate constant kep (reflecting vascular permeability) in patients with asymptomatic monoclonal plasma cell diseases. We analysed DCE-MRI parameters in 33 healthy controls and 148 patients with monoclonal gammopathy of undetermined significance (MGUS) or smouldering multiple myeloma (SMM) according to the 2003 IMWG guidelines. All individuals underwent standardized DCE-MRI of the lumbar spine. Regions of interest were drawn manually on T1-weighted images encompassing the bone marrow of each of the 5 lumbar vertebrae sparing the vertebral vessel. Prognostic significance for median of amplitude A (univariate: P < 0·001, hazard ratio (HR) 2·42, multivariate P = 0·02, HR 2·7) and exchange rate constant kep (univariate P = 0·03, HR 1·92, multivariate P = 0·46, HR 1·5) for time to progression of 79 patients with SMM was found. Patients with amplitude A above the optimal cut-off point of 0·89 arbitrary units had a 2-year progression rate into symptomatic disease of 80%. In conclusion, DCE-MRI parameters are of prognostic significance for time to progression in patients with SMM but not in individuals with MGUS.

Prognostic significance of increased bone marrow microcirculation in newly diagnosed multiple myeloma: results of a prospective DCE-MRI study.

OBJECTIVES: Aim of this prospective study was to investigate prognostic significance of increased bone marrow microcirculation as detected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for survival and local complications in patients with multiple myeloma (MM). METHODS: We performed DCE-MRI of the lumbar spine in 131 patients with newly diagnosed MM and analysed data according to the Brix model to acquire amplitude A and exchange rate constant kep. In 61 patients a second MRI performed after therapy was evaluated to assess changes in vertebral height and identify vertebral fractures. RESULTS: Correlation analysis revealed significant positive association between beta2-microglobulin as well as immunoparesis with DCE-MRI parameters A and kep. Additionally, A was negatively correlated with haemoglobin levels and kep was positively correlated with LDH levels. Higher baseline kep values were associated with decreased vertebral height in a second MRI (P = 0.007) and A values were associated with new vertebral fractures in the lower lumbar spine (P = 0.03 for L4). Pre-existing lytic bone lesions or remission after therapy had no impact on the occurrence of vertebral fractures. Multivariate analysis revealed that amplitude A is an independent adverse risk factor for overall survival. CONCLUSION: DCE-MRI is a non-invasive tool with significance for systemic prognosis and vertebral complications. KEY POINTS: • Qualitative parameters from DCE-MRI are correlated with established factors of disease activity • Increased marrow microcirculation might be a risk factor for loss of vertebral height and fractures • Amplitude A is an independent predictor for shortened overall survival.

A 4D digital phantom for patient-specific simulation of brain CT perfusion protocols.

PURPOSE: Optimizing CT brain perfusion protocols is a challenge because of the complex interaction between image acquisition, calculation of perfusion data, and patient hemodynamics. Several digital phantoms have been developed to avoid unnecessary patient exposure or suboptimum choice of parameters. The authors expand this idea by using realistic noise patterns and measured tissue attenuation curves representing patient-specific hemodynamics. The purpose of this work is to validate that this approach can realistically simulate mean perfusion values and noise on perfusion data for individual patients. METHODS: The proposed 4D digital phantom consists of three major components: (1) a definition of the spatial structure of various brain tissues within the phantom, (2) measured tissue attenuation curves, and (3) measured noise patterns. Tissue attenuation curves were measured in patient data using regions of interest in gray matter and white matter. By assigning the tissue attenuation curves to the corresponding tissue curves within the phantom, patient-specific CTP acquisitions were retrospectively simulated. Noise patterns were acquired by repeatedly scanning an anthropomorphic skull phantom at various exposure settings. The authors selected 20 consecutive patients that were scanned for suspected ischemic stroke and constructed patient-specific 4D digital phantoms using the individual patients' hemodynamics. The perfusion maps of the patient data were compared with the digital phantom data. Agreement between phantom- and patient-derived data was determined for mean perfusion values and for standard deviation in de perfusion data using intraclass correlation coefficients (ICCs) and a linear fit. RESULTS: ICCs ranged between 0.92 and 0.99 for mean perfusion values. ICCs for the standard deviation in perfusion maps were between 0.86 and 0.93. Linear fitting yielded slope values between 0.90 and 1.06. CONCLUSIONS: A patient-specific 4D digital phantom allows for realistic simulation of mean values and standard deviation in perfusion data and makes it possible to retrospectively study how the interaction of patient hemodynamics and scan parameters affects CT perfusion values.

Quantitative evaluation of MR perfusion imaging using blood pool contrast agent in subjects without pulmonary diseases and in patients with pulmonary embolism.

OBJECTIVE: To assess the feasibility of time-resolved parallel three-dimensional magnetic resonance imaging (MRI) for quantitative analysis of pulmonary perfusion using a blood pool contrast agent. METHODS: Quantitative perfusion analysis was performed using novel software to assess pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) in a quantitative manner. RESULTS: The evaluation of lung perfusion in the normal subjects showed an increase of PBF, PBV ventrally to dorsally (gravitational direction), and the highest values at the upper lobe, with a decrease to the middle and lower lobe (isogravitational direction). MTT showed no relevant changes in either the gravitational or isogravitational directions. In comparison with normally perfused lung areas (in diseased patients), the pulmonary embolism (PE) regions showed a significantly lower mean PBF (20 ± 0.6 ml/100 ml/min, normal region 94 ± 1 ml/100 ml/min; P < 0.001), mean PBV (2 ± 0.1 ml/100 ml, normal region 9.8 ± 0.1 ml/100 ml; P < 0.001) and mean MTT (3.8 ± 0.1 s; normal region 6.3 ± 0.1; P < 0.001). CONCLUSION: Our results demonstrate the feasibility of using time-resolved dynamic contrast-enhanced MRI to determine normal range and regional variation of pulmonary perfusion and perfusion deficits in patients with PE. KEY POINTS: • Recently introduced blood pool contrast agents improve MR evaluation of lung perfusion • Regional differences in lung perfusion indicating a gravitational and isogravitational dependency. • Focal areas of significantly decreased perfusion are detectable in pulmonary embolism.

Simulation-based comparison of two approaches frequently used for dynamic contrast-enhanced MRI.

PURPOSE: The purpose was to compare two approaches for the acquisition and analysis of dynamic-contrast-enhanced MRI data with respect to differences in the modelling of the arterial input-function (AIF), the dependency of the model parameters on physiological parameters and their numerical stability. Eight hundred tissue concentration curves were simulated for different combinations of perfusion, permeability, interstitial volume and plasma volume based on two measured AIFs and analysed according to the two commonly used approaches. The transfer constants (Approach 1) K (trans) and (Approach 2) k (ep) were correlated with all tissue parameters. K (trans) showed a stronger dependency on perfusion, and k (ep) on permeability. The volume parameters (Approach 1) v (e) and (Approach 2) A were mainly influenced by the interstitial and plasma volume. Both approaches allow only rough characterisation of tissue microcirculation and microvasculature. Approach 2 seems to be somewhat more robust than 1, mainly due to the different methods of CA administration.

Tumor perfusion assessed by dynamic contrast-enhanced MRI correlates to the grading of renal cell carcinoma: initial results.

In this study, we investigated whether assessment of the tumor perfusion by dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) enables to estimate the morphologic grading of renal cell carcinomas. A total of 21 patients with suspected renal cell cancer were examined using a Gadobutrol-enhanced, dynamic saturation-recovery, turbo-fast, low-angle shot sequence. Tumor perfusion and the tissue-blood ratio within the entire tumor and the most highly vascularized part of the tumor were calculated according to the model of Miles. Immediately after examination, patients underwent surgery, and the results from imaging were compared with the morphological analysis of the histologic grading. Fourteen patients had G2 tumors, and seven patients had G3 tumors. Significantly higher perfusion values (p<0.05) were obtained in G3 tumors than in G2 tumors when the entire tumor area was considered (1.59+/-0.44(ml/g/min) vs. 1.08+/-0.38(ml/g/min)) or its most highly vascularized part (2.14+/-0.89(ml/g/min) vs. 1.40+/-0.49(ml/g/min)). By contrast, the tissue-blood ratios did not differ significantly between the two groups. In conclusion, unlike tissue-blood ratio, surrogate parameters of the tumor perfusion determined by DCE MRI seem to allow an estimation of the grading of renal cell carcinoma. However, further studies with high case numbers and including patients with G1 tumors are required to evaluate the full potential and clinical impact.

Computer assistance for MR based diagnosis of breast cancer: present and future challenges.

MR based methods have gained an important role for the clinical detection and diagnosis of breast cancer. Dynamic contrast-enhanced MRI of the breast has become a robust and successful method, especially for diagnosis of high-risk cases due to its higher sensitivity compared to X-ray mammography. The application of MR based imaging methods depends on various automated image processing routines. The combination of techniques for preprocessing, quantification and visualization of datasets is necessary to achieve fast and solid assessment of valuable parameters for diagnosis. In this paper, different aspects such as registration methods for the reduction of motion artifacts, segmentation issues, as well as morphologic and dynamic lesion analysis will be reviewed with a focus on breast MRI, MR spectroscopy and MR guided biopsies of the breast, their implications and technical challenges from a computer assistance point of view.