Mineralization of the deep gray matter with age: a retrospective review with susceptibility-weighted MR imaging

BACKGROUND AND PURPOSE: Susceptibility-weighted imaging (SWI) is an advanced MR imaging sequence that can be implemented at high resolution. This sequence can be performed on conventional MR imaging scanners and is very sensitive to mineralization. The purpose of this study was to establish the course of mineralization in the deep gray matter with age by using SWI.Materials and METHODS: We retrospectively reviewed susceptibility-weighted images of 134 patients (age range, 1 to 88 years). Inclusion criteria comprised a normal conventional MR imaging (T1, T2, and fluid-attenuated inversion recovery sequences). We statistically analyzed the relative signal intensities of the globus pallidus, putamen, substantia nigra, caudate nucleus, red nucleus, and thalamus for correlation with age. The putamen was graded according to a modified scale, based on previous work that described a systematic pattern of mineralization with age. Bands of hypointensity in the globus pallidus, dubbed “waves,” were also evaluated.RESULTS: We documented decreasing intensity (ie, increasing mineralization) with age in all deep gray matter areas analyzed. We confirmed the age-related posterolateral to anteromedial progression of mineralization in the putamen. Characteristic medial and lateral bands of mineralization were exhibited in the globus pallidus in all children and young adults older than 3 years. Finally, an increase in the number of “waves” present in the globus pallidus was associated with increased age by category.CONCLUSION: This study documents the course and pattern of mineralization in the deep gray matter with age, as determined by SWI. These findings may play a role in evaluating diseased brains in the future.

In 1958, Hallgren and Sourander¹ performed some of the earliest work on characterizing brain iron. They studied iron distribution in various tissues, including the deep gray matter, during an autopsy of brains from 98 subjects, excluding those with cerebrovascular or neuropsychiatric disorders. Iron was found to increase with age in most brain tissues. In the globus pallidus, red nucleus, substantia nigra, and dentate nucleus, iron increases rapidly from birth until the end of the second decade, plateaus for several years, and then shows another milder increase after age 60. Iron increases more slowly in the putamen and caudate, levelling off in the fifth or sixth decade. Subsequent iron-staining studies have largely supported the work of Hallgren and Sourander.¹Most brain iron, other than that found in hemoglobin, is protein-bound, nonheme iron. Approximately one third of nonheme iron is postulated to be in the form of ferritin, though this fraction may be higher in certain deep gray matter structures. Other forms include transferrin, lactoferrin, hemosiderin (thought to be degenerated ferritin), ionic iron, and possibly biogenic magnetite.^2,3 The 2 most important compounds in brain-iron regulation are transferrin, which is used in iron transport, and ferritin, which is used in iron storage. Transferrin and ferritin are also thought to be the only forms of nonheme iron that have a high enough concentration in the brain to be detected currently by MR.³ The mechanisms by which iron and other minerals are deposited in the brain are not well understood. Although the bulk of iron required for the metabolic activity of the adult brain is taken up during the neonatal period, experiments with radioactively labeled iron indicate that small amounts continue to be transported into the adult brain.⁴ In particular, the basal ganglia may exhibit increased susceptibility to mineralization because of their high metabolic rate, and the pattern of mineralization may, in part, relate to the functional vascular components of the striatum.^5,6 Mineral deposits may, in turn, restrict blood flow and cause neural tissue injury that leads to further mineralization.It is believed that the destruction of gray matter causes the release of iron, which is then taken up by activated microglia. Studies have linked increased brain mineralization with several diseases (eg, Parkinson, Alzheimer, Huntington, dementia with Lewy bodies, multiple sclerosis, hemochromatosis, Hallervorden-Spatz, Down syndrome, and AIDS). Histochemical analysis of mineralization of the basal ganglia has shown that many other minerals may be present in addition to iron (eg, calcium, manganese, zinc, copper, magnesium, aluminum, potassium, phosphorus).^5,7 It has been found that the accumulation of iron tends to precede the deposition of calcium and other minerals. These discoveries have underlined the need to develop in vivo imaging techniques sensitive to mineralization, particularly iron.Early attempts at developing such techniques have involved CT imaging.^8,9 More recently, with MR imaging, T2 shortening in the gray matter nuclei with age has been well documented.^10–14 A reduction in T2 is thought to be predominantly related to iron deposition, particularly ferritin,^2,11,15 though 1 team¹⁶ reports contrary findings. The drawback of simply using T2 shortening as a measure of mineralization is that it is also affected by factors such as myelin loss and changes in water concentration, which vary with tissue type, presence of disease, and age.^3,11,13,17 Some researchers have worked on minimizing this effect. Bartzokis et al¹¹ used an imaging process called field-dependent relaxation rate increase (FDRI) to extract that portion of T2 shortening that is the result of mineralization. However, this method is logistically difficult because it requires access to 2 MR machines of different magnetic field strengths as well as careful positioning of the patient in order to extract similar sections from high- and low-field sequences for comparison. Gelman et al¹³ also tried to measure susceptibility using gradient-echo sampling of free induction decay and echo (GESFIDE) MR imaging¹⁸ to measure R2′, ie, that part of the transverse relaxation rate resulting from magnetic field inhomogeneities (R2` = R2* − R2, where R2* refers to the actual observed relaxation rate, and R2 refers to the relaxation rate intrinsic to the tissue). They found a correlation between R2` and iron concentration in the brain. However, they experienced problems with significant magnetic field distortions in the region of the sphenoid sinus and nasal cavity.