Dynamic contrast-enhanced and diffusion-weighted MRI for early detection of tumoral changes in single-dose and fractionated radiotherapy: evaluation in a rat rhabdomyosarcoma model

We aimed to examine different intratumoral changes after single-dose and fractionated radiotherapy, using diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in a rat rhabdomyosarcoma model. Four WAG/Rij rats with rhabdomyosarcomas in the flanks received single-dose radiotherapy of 8 Gy, and four others underwent fractionated radiotherapy (five times 3 Gy). In rats receiving single-dose radiotherapy, a significant perfusion decrease was found in the first 2 days post-treatment, with slow recuperation afterwards. No substantial diffusion changes could be seen; tumor growth delay was 12 days. The rats undergoing fractionated radiotherapy showed a similar perfusion decrease early after the treatment. However, a very strong increase in apparent diffusion coefficient occurred in the first 10 days; growth delay was 18 days. DW-MRI and DCE-MRI can be used to show early tumoral changes induced by radiotherapy. Single-dose and fractionated radiotherapy induce an immediate perfusion effect, while the latter induces more intratumoral necrosis.

Does normalized signal intensity of cervical discs on T2 weighted MRI images change in whiplash patients?

PURPOSE We tested the hypothesis that whiplash trauma leads to changes of the signal intensity of cervical discs in T2-weighted images. METHODS AND MATERIALS 50 whiplash patients (18-65 years) were examined within 48h after motor vehicle accident, and again after 3 and 6 months and compared to 50 age- and sex-matched controls. Signal intensity in ROI's of the discs at the levels C2/3 to C7/T1 and the adjacent vertebral bodies were measured on sagittal T2 weighted MR images and normalized using the average of ROI's in fat tissue. The contrast between discs and both adjacent vertebrae was calculated and disc degeneration was graded by the Pfirrmann-grading system. RESULTS Whiplash trauma did not have a significant effect on the normalized signals from discs and vertebrae, on the contrast between discs and adjacent vertebrae, or on the Pfirrmann grading. However, the contrast between discs and adjacent vertebrae and the Pfirrmann grading showed a strong correlation. In healthy volunteers, the contrast between discs and adjacent vertebrae and Pfirrmann grading increased with age and was dependent on the disc level. CONCLUSION We could not find any trauma related changes of cervical disc signal intensities. Normalized signals of discs and Pfirrmann grading changed with age and varied between disc levels with the used MR sequence.

Atlas-free Brain Tissue Segmentation Using a Single T1-weighted MRI Acquisition

Many studies investigating the aging brain or disease-induced brain alterations rely on accurate and reproducible brain tissue segmentation. Being a preliminary processing step prior to the segmentation, reliableskull-stripping the removal ofnon-brain tissue is also crucial for all later image assessment. Typically, segmentation algorithms rely on an atlas i.e. pre-segmented template data. Brain morphology, however, differs considerably depending on age, sex and race. In addition, diseased brains may deviate significantly from the atlas information typically gained from healthy volunteers. The imposed prior atlas information can thus lead to degradation of segmentation results. The recently introduced MP2RAGE sequence provides a bias-free T1 contrast with heavily reduced T2*- and PD-weighting compared to the standard MP-RAGE [1]. To this end, it acquires two image volumes at different inversion times in one acquisition, combining them to a uniform, i.e. homogenous image. In this work, we exploit the advantageous contrast properties of the MP2RAGE and combine it with a Dixon (i.e. fat-water separation) approach. The information gained by the additional fat image of the head considerably improves the skull-stripping outcome [2]. In conjunction with the pure T1 contrast of the MP2RAGE uniform image, we achieve robust skull-stripping and brain tissue segmentation without the use of an atlas

Radiotherapy Assessment Using Diffusion Weighted MRI

Purpose: There are two goals of this study. The first goal of this study is to investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment among a unique cohort of early stage breast cancer patients who received the single-dose preoperative radiotherapy. The second goal of this study is to investigate the clinical feasibility of using classic texture features as potential biomarkers which are supplementary to regional apparent diffusion coefficient in gynecological cancer radiotherapy response assessment.

Methods and Materials: For the breast cancer study, 15 patients with early stage breast cancer were enrolled in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE-MRI scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b = 500 mm2/s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T1-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (Ktrans) and kep were analyzed using the two-compartment Tofts pharmacokinetic model. For pharmacokinetic parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction.

For the gynecological cancer study, 12 female patients with gynecologic cancer treated with fractionated external beam radiotherapy (EBRT) combined with high dose rate (HDR) intracavitary brachytherapy were studied. Each patient first received EBRT treatment followed by five fractions of HDR treatment. Before EBRT and before each fraction of brachytherapy, Diffusion Weighted MRI (DWI-MRI) and CT scans were acquired. DWI scans were acquired in sagittal plane utilizing a spin-echo echo-planar imaging sequence with weighting factors of b = 500 s/mm2 and b = 1000 s/mm2, one set of images of b = 0 s/mm2 were also acquired. ADC maps were calculated using linear least-square fitting method. Distributed diffusion coefficient (DDC) maps and stretching parameter α were calculated. For ADC and DDC maps, 33 classic texture features were generated utilizing the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from high-risk clinical target volume (HR-CTV). Wilcoxon signed-rank statistics test was applied to determine the significance of each feature’s numerical value change after radiotherapy. Significance level was set to 0.05 with multi-comparison correction if applicable.

Results: For the breast cancer study, regarding ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of Ktrans and 33 features of kep changed significantly.

For the gynecological cancer study, regarding ADC maps, 28 out of 33 HR-CTV texture features showed significant changes after the EBRT treatment. 28 out of 33 HR-CTV texture features indicated significant changes after HDR treatments. The texture features that indicated significant changes after HDR treatments are the same as those after EBRT treatment. 28 out of 33 HR-CTV texture features showed significant changes after whole radiotherapy treatment process. The texture features that indicated significant changes for the whole treatment process are the same as those after HDR treatments.

Conclusion: Initial results indicate that certain classic texture features are sensitive to radiation-induced changes. Classic texture features with significant numerical changes can be used in monitoring radiotherapy effect. This might suggest that certain texture features might be used as biomarkers which are supplementary to ADC and DDC for assessment of radiotherapy response in breast cancer and gynecological cancer.

Diagnostic value of diffusion weighted MRI and ADC in differential diagnosis of cavernous hemangioma of the liver.

Aims: To investigate the use of diffusion weighted magnetic resonance imaging (DWI) and the apparent diffusion coefficient (ADC) values in the diagnosis of hemangioma. Materials and methods: The study population consisted of 72 patients with liver masses larger than 1 cm (72 focal lesions). DWI examination with a b value of 600 s/mm2 was carried out for all patients. After DWI examination, an ADC map was created and ADC values were measured for 72 liver masses and normal liver tissue (control group). The average ADC values of normal liver tissue and focal liver lesions, the “cut-off” ADC values, and the diagnostic sensitivity and specificity of the ADC map in diagnosing hemangioma, benign and malignant lesions were researched. Results: Of the 72 liver masses, 51 were benign and 21 were malignant. Benign lesions comprised 38 hemangiomas and 13 simple cysts. Malignant lesions comprised 9 hepatocellular carcinomas, and 12 metastases. The highest ADC values were measured for cysts (3.782±0.53×10-3 mm2/s) and hemangiomas (2.705±0.63×10-3 mm2/s). The average ADC value of hemangiomas was significantly higher than malignant lesions and the normal control group (p<0.001). The average ADC value of cysts were significantly higher when compared to hemangiomas and normal control group (p<0.001). To distinguish hemangiomas from malignant liver lesions, the “cut-off” ADC value of 1.800×10-3 mm2/s had a sensitivity of 97.4% and a specificity of 90.9%. To distinguish hemangioma from normal liver parenchyma the “cut-off” value of 1.858×10-3 mm2/s had a sensitivity of 97.4% and a specificity of 95.7%. To distinguish benign liver lesions from malignant liver lesions the “cut-off” value of 1.800×10-3 mm2/s had a sensitivity of 96.1% and a specificity of 90.0%. Conclusion: DWI and quantitative measurement of ADC values can be used in differential diagnosis of benign and malignant liver lesions and also in the diagnosis and differentiation of hemangiomas. When dynamic examination cannot distinguish cases with vascular metastasis and lesions from hemangioma, DWI and ADC values can be useful in the primary diagnosis and differential diagnosis. The technique does not require contrast material, so it can safely be used in patients with renal failure. Keywords:

Added value of diffusion-weighted MRI in detection of cervical cancer recurrence compared with morphologic and dynamic contrast-enhanced MRI sequences

PURPOSE We aimed to evaluate the added value of diffusion-weighted imaging (DWI) to standard magnetic resonance imaging (MRI) for detecting post-treatment cervical cancer recurrence. The detection accuracy of T2-weighted (T2W) images was compared with that of T2W MRI combined with either dynamic contrast-enhanced (DCE) MRI or DWI. METHODS Thirty-eight women with clinically suspected uterine cervical cancer recurrence more than six months after treatment completion were examined with 1.5 Tesla MRI including T2W, DCE, and DWI sequences. Disease was confirmed histologically and correlated with MRI findings. The diagnostic performance of T2W imaging and its combination with either DCE or DWI were analyzed. Sensitivity, positive predictive value, and accuracy were calculated. RESULTS Thirty-six women had histologically proven recurrence. The accuracy for recurrence detection was 80% with T2W/DCE MRI and 92.1% with T2W/DWI. The addition of DCE sequences did not significantly improve the diagnostic ability of T2W imaging, and this sequence combination misclassified two patients as falsely positive and seven as falsely negative. The T2W/DWI combination revealed a positive predictive value of 100% and only three false negatives. CONCLUSION The addition of DWI to T2W sequences considerably improved the diagnostic ability of MRI. Our results support the inclusion of DWI in the initial MRI protocol for the detection of cervical cancer recurrence, leaving DCE sequences as an option for uncertain cases.

Acute Toxic Leukoencephalopathy: Potential for Reversibility Clinically and on MRI With Diffusion-Weighted and FLAIR Imaging

OBJECTIVE. Toxic leukoencephalopathy may present acutely or subacutely with symmetrically reduced diffusion in the periventricular and supraventricular white matter, hereafter referred to as periventricular white matter. This entity may reverse both on imaging and clinically. However, a gathering together of the heterogeneous causes of this disorder as seen on MRI with diffusion-weighted imaging (DWI) and an analysis of their likelihood to reverse has not yet been performed. Our goals were to gather causes of acute or subacute toxic leukoencephalopathy that can present with reduced diffusion of periventricular white matter in order to promote recognition of this entity, to evaluate whether DWI with apparent diffusion coefficient (ADC) values can predict the extent of chronic FLAIR abnormality ( imaging reversibility), and to evaluate whether DWI can predict the clinical outcome ( clinical reversibility). MATERIALS AND METHODS. Two neuroradiologists retrospectively reviewed the MRI examinations of 39 patients with acute symptoms and reduced diffusion of periventricular white matter. The reviewers then scored the extent of abnormality on DWI and FLAIR. ADC ratios of affected white matter versus the unaffected periventricular white matter were obtained. Each patient`s clinical records were reviewed to determine the cause and clinical outcome. Histology findings were available in three patients. Correlations were calculated between the initial MRI markers and both the clinical course and the follow-up extent on FLAIR using Spearman`s correlation coefficient. RESULTS. Of the initial 39 patients, seven were excluded because of a nontoxic cause (hypoxic-ischemic encephalopathy [HIE] or congenital genetic disorders) or because of technical errors. In the remaining 32 patients, no correlation was noted between any of the initial MRI markers (percentage of ADC reduction, DWI extent, or FLAIR extent) with the clinical outcome. Three patients had histologic correlation. However, moderate correlation was seen between the extent of abnormality on initial FLAIR and the extent on follow-up FLAIR (r = 0.441, p = 0.047). Of the 13 patients who underwent repeat MRI at 21 days or longer, the reduced diffusion resolved in all but one. Significant differences were noted between ADC values in affected white matter versus unaffected periventricular white matter on initial (p < 0.0001) but not on follow-up MRI (p = 0.13), and in affected white matter on initial versus follow-up (p = 0.0014) in those individuals who underwent repeat imaging on the same magnet (n = 9), confirming resolution of the DWI abnormalities. CONCLUSION. Acute toxic leukoencephalopathy with reduced diffusion may be clinically reversible and radiologically reversible on DWI, and may also be reversible, but to a lesser degree, on FLAIR MRI. None of the imaging markers measured in this study appears to correlate with clinical outcome, which underscores the necessity for prompt recognition of this entity. Alerting the clinician to this potentially reversible syndrome can facilitate treatment and removal of the offending agent in the early stages.

Changes in Perfusion-Weighted Magnetic Resonance Imaging after Carotid Angioplasty with Stent

Carotid artery stenosis due to arteriosclerosis increases the risk of cerebral ischemia via embolic phenomena or reduced blood flow. The changes in cerebral perfusion that may occur after treatment are not clearly understood. This study evaluated the changes in cerebral microcirculation following carotid angioplasty with stenting (CAS) under cerebral protection with filters using ultrafast gradient echo (GRE) perfusion weighted imaging (PWI) with magnetic resonance imaging (MRI). Prospectively, 21 cervical carotid stenosis patients, mean age 69.95 years, underwent MRI 12 h before and 72 h after CAS. PWI parameters were collected for statistical analysis: cerebral blood volume (CB V), mean transit time (MTT) and time to peak (TTP). Statistical analysis was applied to absolute parameters and to values normalized against those from the contralateral parenchyma. The main finding of this study was improved hemodynamics for the normalized data after CAS, shown by reduced MTT (p<0.001) and TTP (p=0.019) in the territory fed by the middle cerebral artery ipsilateral to the CAS. Absolute data showed increased blood volume in the cerebral hemispheres after CAS, which was more accentuated on the stent side (p=0.016) than the contralateral side (p=0.029). Early improvements in cerebral perfusion, mainly seen in the normalized data, were clearly demonstrated in the timing parameters - TTP & MTT - after CAS.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P

Diffusion-weighted magnetic resonance imaging in metastatic gastrointestinal stromal tumor (GIST): a pilot study on the assessment of treatment response in comparison with 18F-FDG PET/CT.

BACKGROUND: Diffusion-weighted magnetic resonance imaging (MRI) is increasingly being used for assessing the treatment succes in oncology, but the real clinical value needs to evaluated by comparison with other, already established, metabolic imaging techniques. PURPOSE: To prospectively evaluate the clinical potential of diffusion-weighted MRI with apparent diffusion coefficient (ADC) mapping for gastrointestinal stromal tumor (GIST) response to targeted therapy compared with 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). MATERIAL AND METHODS: Eight patients (mean age, 56 ± 11 years) known to have metastatic GIST underwent 18F-FDG PET/CT and MRI (T1Gd, DWI [b = 50,300,600], ADC mapping) simultaneously, before and after change in targeted therapy. MR and PET/CT examinations were first analyzed blindly. Second, PET/CT images were co-registered with T1Gd-MR images for lesion detection. Only 18F-FDG avid lesions were considered. Maximum standardized uptake value (SUVmax) and the corresponding minimum ADCmin were measured for the six largest lesions per patient, if any, on baseline and follow-up examinations. The relationship between changes in SUVmax and ADCmin was analyzed (Spearman's correlation). RESULTS: Twenty-four metastases (12 hepatic, 12 extra-hepatic) were compared on PET/CT and MR images. SUVmax decreased from 7.7 ± 8.1 g/mL to 5.5 ± 5.4 g/mL (P = 0.20), while ADCmin increased from 1.2 ± 0.3 × 10(-3)mm(2)/s to 1.5 ± 0.3 × 10(-3)mm(2)/s (P = 0.0002). There was a significant association between changes in SUVmax and ADCmin (rho = - 0.62, P = 0.0014), but not between changes in lesions size (P = 0.40). CONCLUSION: Changes in ADCmin correlated with the response of 18F-FDG avid GIST to targeted therapy. Thus, diffusion-weighted MRI may represent a radiation-free alternative for follow-up treatment for metastatic GIST patients.

Assessment of liver tumor response by high-field (3T) MRI after radiofrequency ablation: Short- and mid-term evolution of diffusion parameters within the ablation zone.

PURPOSE: To compare the apparent diffusion coefficient (ADC) values of malignant liver lesions on diffusion-weighted MRI (DWI) before and after successful radiofrequency ablation (RF ablation). MATERIALS AND METHODS: Thirty-two patients with 43 malignant liver lesions (23/20: metastases/hepatocellular carcinomas (HCC)) underwent liver MRI (3.0T) before (<1month) and after RF ablation (at 1, 3 and 6months) using T2-, gadolinium-enhanced T1- and DWI-weighted MR sequences. Jointly, two radiologists prospectively measured ADCs for each lesion by means of two different regions of interest (ROIs), first including the whole lesion and secondly the area with the visibly most restricted diffusion (MRDA) on ADC map. Changes of ADCs were evaluated with ANOVA and Dunnett tests. RESULTS: Thirty-one patients were successfully treated, while one patient was excluded due to focal recurrence. In metastases (n=22), the ADC in the whole lesion and in MRDA showed an up-and-down evolution. In HCC (n=20), the evolution of ADC was more complex, but with significantly higher values (p=0.013) at 1 and 6months after RF ablation. CONCLUSION: The ADC values of malignant liver lesions successfully treated by RF ablation show a predictable evolution and may help radiologists to monitor tumor response after treatment.

MRI monitoring of focal cerebral ischemia in peroxisome proliferator-activated receptor (PPAR)-deficient mice.

Peroxisome proliferator-activated receptors (PPARs) are a potential target for neuroprotection in focal ischemic stroke. These nuclear receptors have major effects in lipid metabolism, but they are also involved in inflammatory processes. Three PPAR isotypes have been identified: alpha, beta (or delta) and gamma. The development of PPAR transgenic mice offers a promising tool for prospective therapeutic studies. This study used MRI to assess the role of PPARalpha and PPARbeta in the development of stroke. Permanent middle cerebral artery occlusion induced focal ischemia in wild-type, PPARalpha-null mice and PPARbeta-null mice. T(2)-weighted MRI was performed with a 7 T MRI scan on day 0, 1, 3, 7 and 14 to monitor lesion growth in the various genotypes. General Linear Model statistical analysis found a significant difference in lesion volume between wild-type and PPAR-null mice for both alpha and beta isotypes. These data validate high-resolution MRI for monitoring cerebral ischemic lesions, and confirm the neuroprotective role of PPARalpha and PPARbeta in the brain.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Therapy response with diffusion MRI: an update

The efficiency of an oncological treatment regimen is often assessed by morphological criteria such as tumour size evaluated by cross-sectional imaging, or by laboratory measurements of plasma biomarkers. Because these types of measures typically allow for assessment of treatment response several weeks or even months after the start of therapy, earlier response assessment that provides insight into tumour function is needed. This is particularly urgent for the evaluation of newer targeted therapies and for fractionated therapies that are delivered over a period of weeks to allow for a change of treatment in non-responding patients. Diffusion-weighted MRI (DW-MRI) is a non-invasive imaging tool that does not involve radiation or contrast media, and is sensitive to tissue microstructure and function on a cellular level. DW-MRI parameters have shown sensitivity to treatment response in a growing number of tumour types and organ sites, with additional potential as predictive parameters for treatment outcome. A brief overview of DW-MRI principles is provided here, followed by a review of recent literature in which DW-MRI has been used to monitor and predict tumour response to various therapeutic regimens.