Magnetic resonance imaging: effects of magnetic field strength.

Crooks, L E; Arakawa, M; Hoenninger, J; McCarten, B; Watts, J C; Kaufman, L

doi:10.1148/radiology.151.1.6701302

Cited by 68 publications

(22 citation statements)

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“…Measurements of diffusion anisotropy are known to be highly noise dependent, especially in areas of low anisotropy where the ratio between the magnitude of the principal eigenvectors of the diffusion tensor and the background tissue noise is less favorable [7,19,34,44]. Higher field strengths typically boost the SNR [44]. The field-strength-related SNR gain we observed was in the range of 20% comparing 1.5 with 3.0 Tesla.…”

Section: Discussionmentioning

confidence: 75%

“…Theoretically, low FA values are expected for brain areas that have a predominant cellular architecture (central gray matter); high FA-values are expected for brain areas with tightly packed fiber tracts (central white matter). Measurements of diffusion anisotropy are known to be highly noise dependent, especially in areas of low anisotropy where the ratio between the magnitude of the principal eigenvectors of the diffusion tensor and the background tissue noise is less favorable [7,19,34,44]. Higher field strengths typically boost the SNR [44].…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies showed that the T2 relaxation time of gray and white matter decreases with the magnetic field strength [44]. To evaluate the impact of these differences in T2-relaxation times, we compared identical DTI sequences at different echo times for both field strengths.…”

Section: Discussionmentioning

confidence: 99%

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Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars

et al. 2006

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Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars Abstract The objectives were to study the "impact" of the magnetic field strength on diffusion tensor imaging (DTI) metrics and also to determine whether magnetic-field-related differences in T2-relaxation times of brain tissue influence DTI measurements. DTI was performed on 12 healthy volunteers at 1.5 and 3.0 Tesla (within 2 h) using identical DTI scan parameters. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured at multiple gray and white matter locations. ADC and FA values were compared and analyzed for statistically significant differences. In addition, DTI measurements were performed at different echo times (TE) for both field strengths. ADC values for gray and white matter were statistically significantly lower at 3.0 Tesla compared with 1.5 Tesla (% change between −1.94% and −9.79%). FA values were statistically significantly higher at 3.0 Tesla compared with 1.

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Section: Discussionmentioning

confidence: 75%

Section: Discussionmentioning

confidence: 99%

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Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars

et al. 2006

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“…Chen et al ratio gain at 3.0 T ( 28,29 ). In the present study, we used the same contrast medium (gadodiamide) with the same standard clinical dose and the same injection method compared with the previous 1.5 T studies ( 13,14 ), so the results could be directly compared.…”

Section: Breast Imaging: Assessing Breast Cancer Response To Neoadjuvmentioning

confidence: 96%

Breast Cancer: Evaluation of Response to Neoadjuvant Chemotherapy with 3.0-T MR Imaging

Chen

Bahri²,

Mehta³

et al. 2011

Radiology

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Purpose:To assess how the molecular biomarker status of a breast cancer, including human epidermal growth factor receptor 2 (HER2), hormone receptors, and the proliferation marker Ki-67 status, affects the diagnosis at 3.0-T magnetic resonance (MR) imaging. Materials and Methods:This study was approved by the institutional review board and was HIPAA compliant. Fifty patients (age range, 28-82 years; mean age, 49 years) receiving neoadjuvant chemotherapy were monitored with 3.0-T MR imaging. The longest dimension of the residual cancer was measured at MR imaging and correlated with pathologic fi ndings.Patients were further divided into subgroups on the basis of HER2, hormone receptor, and Ki-67 status. Pathologic complete response (pCR) was defi ned as when there were no residual invasive cancer cells. The Pearson correlation was used to correlate MR imaging-determined and pathologic tumor size, and the unpaired t test was used to compare MR imaging-pathologic size discrepancies. Results:Of the 50 women, 14 achieved pCR. There were seven false-negative diagnoses at MR imaging. The overall sensitivity, specifi city, and accuracy for diagnosing invasive residual disease at MR imaging were 81%, 93%, and 84%, respectively. The mean MR imaging-pathologic size discrepancy was 0.5 cm 6 0.9 (standard deviation) for HER2-positive cancer and 2.3 cm 6 3 .5 for HER2-negative cancer ( P = .009). In the HER2-negative group, the size discrepancy was smaller for hormone receptor-negative than for hormone receptor-positive cancers (1.0 cm 6 1.1 vs 3.0 cm 6 4.0, P = .04). The size discrepancy was smaller in patients with 40% or greater Ki-67 expression (0.8 cm 6 1.1) than in patients with 10% or less Ki-67 expression (3.9 cm 6 5.1, P = .06). Conclusion:The diagnostic accuracy of breast MR imaging is better in more aggressive than in less aggressive cancers. When MR imaging is used for surgical planning, caution should be taken with HER2-negative hormone receptor-positive cancers.q RSNA, 2011Supplemental material : http://radiology.rsna.org/lookup /suppl

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“…Animal MR imaging is also usually performed at higher field, in which the changes in T 1 associated with focal ischemia are greater than at low field (e.g. 4.7 or 9.4 T versus 1.5 T, respectively) (25,27). As high-field clinical magnets and faster T 1 acquisition sequences become more widely available, quantitative T 1 imaging could prove beneficial for diagnosing the acute edema associated with HI or stroke clinically (28).…”

Section: Discussionmentioning

confidence: 99%

Development of Acute Edema Following Cerebral Hypoxia-Ischemia in Neonatal Compared with Juvenile Rats Using Magnetic Resonance Imaging

et al. 2004

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We hypothesized that the evolution of cerebral edema accompanying cerebral hypoxia-ischemia is dependent on age and that such differences would be detectable using magnetic resonance imaging methods. Thus we examined in immature and juvenile rats the relationship between hypoxic-ischemic changes in T 1 and T 2 and the alterations in brain water content, as assessed by differences in tissue wet-dry weights. One-and 4-wk-old rats were anesthetized and subjected to unilateral carotid artery occlusion and subsequent exposure to hypoxia (8% oxygen). T 1 and T 2 maps were acquired at 9.4 T, and then brain water content was measured in sham controls or in hypoxic-ischemic animals before, during, and 1 or 24 h after hypoxia-ischemia. In sham controls, T 1 , T 2 , and proton density decreased with increasing age, corresponding to an ontogenic decrease in water content. In 1-wk-old rats, increases in T 1 and T 2 were observed during and at 1 and 24 h after hypoxia-ischemia, corresponding to elevations in water content. In 4-wk-old rats, T 1 and water content increased during and at 1 and 24 h after hypoxia-ischemia whereas T 2 was not increased until 24 h after hypoxia-ischemia. Regression analysis showed that T 1 correlated better with total water content than T 2 . In both immature and older brain, an increase in total brain water develops acutely and persists after an episode of cerebral hypoxia-ischemia, and T 1 imaging detects this change better than T 2 . Hypoxic-ischemic changes in T 2 are age dependent, reflecting other physicochemical changes of water in the tissue than water content alone. Cerebral ischemia produces a tissue edema consisting of a combination of intracellular and extracellular water accumulation within the tissue. The edema associated with ischemia has been assessed frequently using one or more noninvasive MR imaging techniques (1) in which the contrast has been based primarily on regional differences in proton density, spin-lattice (T 1 ), or spin-spin (T 2 ) proton relaxation times. Considering the fact that the majority of protons within the brain are found in water molecules, changes in intensity in T 1 -and T 2 -weighted images have often been interpreted to represent edema and have been used to monitor its progression under various pathologic states including cerebral ischemia and brain trauma (2). However, the actual changes in water content or the biophysical properties of the tissue that underlie many of the MR imaging changes remain poorly understood. Indeed, those studies measuring ontogenic or pathologic changes in tissue water content have reported a range of poor, mild, and good correlations between water content and MR variables such as T 2 and T 1 (3-12). The majority of such studies have not examined the correlation of the changes in MR relaxation variables with the evolution of the pathologic edema as a function of time, and even fewer have investigated directly the relationship between changes in MR variables and the edema resulting from a cerebral HI insult. Recently, we repor...

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Magnetic resonance imaging: effects of magnetic field strength.

Cited by 68 publications

References 0 publications

Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars

Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars

Breast Cancer: Evaluation of Response to Neoadjuvant Chemotherapy with 3.0-T MR Imaging

Development of Acute Edema Following Cerebral Hypoxia-Ischemia in Neonatal Compared with Juvenile Rats Using Magnetic Resonance Imaging

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