A novel MRI-compatible brain ventricle phantom for validation of segmentation and volumetry methods

Anthropomorphic brain phantoms for use in MRI systems: a systematic review

OBJECTIVE

To provide a systematic review of available brain MRI phantoms for comparison of structural and functional characteristics.

MATERIALS AND METHODS

Phantoms were identified from a literature search using two databases including Google Scholar and PubMed. Narrow inclusion criteria were followed for identification of only tissue-mimicking MRI phantoms excluding digital, computational, or numerical phantoms. Assessment criteria for the identified phantoms was based on three categories being anatomical accuracy, tissue-mimicking materials, and exhibiting relaxation times approximating in-vivo tissues. The available features and uses of each phantom were reported and discussed using the assessment criteria.

RESULTS

Ten phantoms were identified after screening; each proposed phantom was then summarized in a table (Table 2). Significant features and characteristics were shown in the comparisons of phantom type in each category, being anthropomorphic vs. traditional phantoms. Anthropomorphic phantoms had more anatomically accurate features than traditional phantoms. On the other hand, traditional phantoms commonly used effective tissue-mimicking materials and accurate electromagnetic properties.

DISCUSSION

The findings provide an overview of the different proposed tissue-mimicking MRI brain phantoms available. Various uses and features are highlighted by comparing criteria such as anatomical accuracy, tissue-mimicking material, and electromagnetic properties. Tissue-mimicking MRI phantoms are an extremely useful tool for researchers and clinicians. Future applications include personalized phantom technology and validation of MR imaging and segmentation methods.

Systematic and Comprehensive Automated Ventricle Segmentation on Ventricle Images of the Elderly Patients: A Retrospective Study

Background and Objective: Ventricle volume is closely related to hydrocephalus, brain atrophy, Alzheimer's, Parkinson's syndrome, and other diseases. To accurately measure the volume of the ventricles for elderly patients, we use deep learning to establish a systematic and comprehensive automated ventricle segmentation framework.

Methods: The study participation included 20 normal elderly people, 20 patients with cerebral atrophy, 64 patients with normal pressure hydrocephalus, and 51 patients with acquired hydrocephalus. Second, get their imaging data through the picture archiving and communication systems (PACS) system. Then use ITK software to manually label participants' ventricular structures. Finally, extract imaging features through machine learning.

Results: This automated ventricle segmentation method can be applied not only to CT and MRI images but also to images with different scan slice thicknesses. More importantly, it produces excellent segmentation results (Dice > 0.9).

Conclusion: This automated ventricle segmentation method has wide applicability and clinical practicability. It can help clinicians find early disease, diagnose disease, understand the patient's disease progression, and evaluate the patient's treatment effect.

How to design and construct a 3D-printed human head phantom

In this paper, we will provide a methodology for head phantom development based on in vivo imaging data attained utilizing MRI. The anthropomorphic phantom can be designed to mimic human anatomy.

Design and construction of an innovative brain phantom prototype for MRI

PURPOSE

The purpose of this project was to construct a physical brain phantom for MRI, mimicking structure and T₁ relaxation properties of white matter (WM) and gray matter (GM).

METHODS

The phantom design comprised 2 compartments, 1 resembling the WM and 1 resembling the GM. Their T₁ relaxation times, as assessed using an inversion recovery turbo spin echo sequence, were reproduced using an agar gel doped with contrast agent (CA) and their folding patterns were simulated through a molding-casting procedure using 3D-printed casts and flexible silicone molds. Three versions of the assembling procedure were adopted to build: Phantom1 without any separation; Phantom2 with a varnish layer; and Phantom3 with a thin wax layer between the compartments.

RESULTS

Phantom1 was characterized by an immediate diffusion of CA between the 2 compartments. Phantom2 and Phantom3, instead, showed relaxation times and shape comparable with the target ones identified in a healthy control subject (WM: 754 ± 40 ms; GM: 1277 ± 96 ms). Moreover, both compartments revealed intact gyri and sulci. However, the diffusion of CA made Phantom2 stable only for a short period of time. Phantom3 showed stability within a time window of several days but the wax layer between the WM and GM was visible in the MRI.

CONCLUSION

Structural and intensity properties of the constructed phantoms are useful in evaluating and validating steps from image acquisition to image processing. Moreover, the described constructing procedure and its modular design make it adjustable to a variety of applications.

An open source, 3D printed preclinical MRI phantom for repeated measures of contrast agents and reference standards

In medical imaging, clinicians, researchers and technicians have begun to use 3D printing to create specialized phantoms to replace commercial ones due to their customizable and iterative nature. Presented here is the design of a 3D printed open source, reusable magnetic resonance imaging (MRI) phantom, capable of flood-filling, with removable samples for measurements of contrast agent solutions and reference standards, and for use in evaluating acquisition techniques and image reconstruction performance. The phantom was designed using SolidWorks, a computer-aided design software package. The phantom consists of custom and off-the-shelf parts and incorporates an air hole and Luer Lock system to aid in flood filling, a marker for orientation of samples in the filled mode and bolt and tube holes for assembly. The cost of construction for all materials is under $90. All design files are open-source and available for download. To demonstrate utility, B₀ field mapping was performed using a series of gadolinium concentrations in both the unfilled and flood-filled mode. An excellent linear agreement (R²>0.998) was observed between measured relaxation rates (R₁/R₂) and gadolinium concentration. The phantom provides a reliable setup to test data acquisition and reconstruction methods and verify physical alignment in alternative nuclei MRI techniques (e.g. carbon-13 and fluorine-19 MRI). A cost-effective, open-source MRI phantom design for repeated quantitative measurement of contrast agents and reference standards in preclinical research is presented. Specifically, the work is an example of how the emerging technology of 3D printing improves flexibility and access for custom phantom design.

Multicenter Evaluation of Geometric Accuracy of MRI Protocols Used in Experimental Stroke

It has recently been suggested that multicenter preclinical stroke studies should be carried out to improve translation from bench to bedside, but the accuracy of magnetic resonance imaging (MRI) scanners routinely used in experimental stroke has not yet been evaluated. We aimed to assess and compare geometric accuracy of preclinical scanners and examine the longitudinal stability of one scanner using a simple quality assurance (QA) protocol. Six 7 Tesla animal scanners across six different preclinical imaging centers throughout Europe were used to scan a small structural phantom and estimate linear scaling errors in all orthogonal directions and volumetric errors. Between-scanner imaging consisted of a standard sequence and each center's preferred sequence for the assessment of infarct size in rat models of stroke. The standard sequence was also used to evaluate the drift in accuracy of the worst performing scanner over a period of six months following basic gradient calibration. Scaling and volumetric errors using the standard sequence were less variable than corresponding errors using different stroke sequences. The errors for one scanner, estimated using the standard sequence, were very high (above 4% scaling errors for each orthogonal direction, 18.73% volumetric error). Calibration of the gradient coils in this system reduced scaling errors to within ±1.0%; these remained stable during the subsequent 6-month assessment. In conclusion, despite decades of use in experimental studies, preclinical MRI still suffers from poor and variable geometric accuracy, influenced by the use of miscalibrated systems and various types of sequences for the same purpose. For effective pooling of data in multicenter studies, centers should adopt standardized procedures for system QA and in vivo imaging.

On replacing the manual measurement of ACR phantom images performed by MRI technologists with an automated measurement approach

PURPOSE

To assess whether measurements on American College of Radiology (ACR) phantom images performed by magnetic resonance imaging (MRI) technologists as part of a weekly quality control (QC) program could be performed exclusively using an automated system without compromising the integrity of the QC program.

MATERIALS AND METHODS

ACR phantom images are acquired on 15 MRI scanners at a number of ACR-accredited sites to fulfill requirements of a weekly QC program. MRI technologists routinely perform several measurements on these images. Software routines are also used to perform the measurements. A set of geometry measurements made by technologists over a five week period and those made using software routines were compared to reference-standard measurements made by two MRI physicists.

RESULTS

The geometry measurements performed by software routines had a very high positive correlation (0.92) with the reference-standard measurements. Technologist measurements also had a high positive correlation (0.63), although the correlation was less than for the automated measurements. Bland-Altman analysis revealed overall good agreement between the automated and reference-standard measurements, with the 95% limits of agreement being within ±0.62 mm. Agreement between the technologist and the reference-standard measurements was demonstratively poorer, with 95% limits of agreement being ±1.46 mm. Some of the technologist measurements differed from the reference standard by as much as 2 mm.

CONCLUSION

The technologists' geometry measurements may be able to be replaced by automated measurement without compromising the weekly QC program required by the ACR.

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

An anatomically realistic temperature phantom for radiofrequency heating measurements

PURPOSE

An anthropomorphic phantom with realistic electrical properties allows for a more accurate reproduction of tissue current patterns during excitation. A temperature map can then probe the worst-case heating expected in the unperfused case. We describe an anatomically realistic human head phantom that allows rapid three-dimensional (3D) temperature mapping at 7T.

METHODS

The phantom was based on hand-labeled anatomical imaging data and consists of four compartments matching the corresponding human tissues in geometry and electrical properties. The increases in temperature resulting from radiofrequency excitation were measured with MR thermometry using a temperature-sensitive contrast agent (TmDOTMA(-)) validated by direct fiber optic temperature measurements.

RESULTS

Acquisition of 3D temperature maps of the full phantom with a temperature accuracy better than 0.1°C was achieved with an isotropic resolution of 5 mm and acquisition times of 2-4 minutes.

CONCLUSION

Our results demonstrate the feasibility of constructing anatomically realistic phantoms with complex geometries incorporating the ability to measure accurate temperature maps in the phantom. The anthropomorphic temperature phantom is expected to provide a useful tool for the evaluation of the heating effects of both conventional and parallel transmit pulses and help validate electromagnetic and temperature simulations.