RATIONALE AND OBJECTIVES: Early detection of breast lesions using mammography has resulted in lower mortality rates. However, some breast lesions are mammography occult, and magnetic resonance imaging (MRI) is recommended, but it has lower specificity. It is possible to achieve higher specificity by using strain-encoded (SENC) MRI and/or magnetic resonance elastography. SENC breast MRI can measure the strain properties of breast tissue. Similarly, magnetic resonance elastography is used to measure the elasticity (ie, shear stiffness) of different tissue compositions interrogating the tissue mechanical properties. Reports have shown that malignant tumors are three to 13 times stiffer than normal tissue and benign tumors. MATERIALS AND METHODS: The investigators have developed a SENC breast hardware device capable of periodically compressing the breast, thus allowing for longer scanning time and measuring the strain characteristics of breast tissue. This hardware enables the use of SENC MRI with high spatial resolution (1 × 1 × 5 mm(3)) instead of fast SENC imaging. Simple controls and multiple safety measures were added to ensure accurate, repeatable, and safe in vivo experiments. RESULTS: Phantom experiments showed that SENC breast MRI has higher signal-to-noise ratio and contrast-to-noise ratio than fast SENC imaging under different scanning resolutions. Finally, the SENC breast device reproducibility measurements resulted in a difference of <1 mm with a 1% strain difference. CONCLUSIONS: SENC breast magnetic resonance images have higher signal-to-noise ratio and contrast-to-noise ratios than fast SENC images. Thus, combining SENC breast strain measurements with diagnostic breast MRI to differentiate benign from malignant lesions could potentially increase the specificity of diagnosis in the clinical setting.
RATIONALE AND OBJECTIVES: Early detection of breast lesions using mammography has resulted in lower mortality rates. However, some breast lesions are mammography occult, and magnetic resonance imaging (MRI) is recommended, but it has lower specificity. It is possible to achieve higher specificity by using strain-encoded (SENC) MRI and/or magnetic resonance elastography. SENC breast MRI can measure the strain properties of breast tissue. Similarly, magnetic resonance elastography is used to measure the elasticity (ie, shear stiffness) of different tissue compositions interrogating the tissue mechanical properties. Reports have shown that malignant tumors are three to 13 times stiffer than normal tissue and benign tumors. MATERIALS AND METHODS: The investigators have developed a SENC breast hardware device capable of periodically compressing the breast, thus allowing for longer scanning time and measuring the strain characteristics of breast tissue. This hardware enables the use of SENC MRI with high spatial resolution (1 × 1 × 5 mm(3)) instead of fast SENC imaging. Simple controls and multiple safety measures were added to ensure accurate, repeatable, and safe in vivo experiments. RESULTS: Phantom experiments showed that SENC breast MRI has higher signal-to-noise ratio and contrast-to-noise ratio than fast SENC imaging under different scanning resolutions. Finally, the SENC breast device reproducibility measurements resulted in a difference of <1 mm with a 1% strain difference. CONCLUSIONS: SENC breast magnetic resonance images have higher signal-to-noise ratio and contrast-to-noise ratios than fast SENC images. Thus, combining SENC breast strain measurements with diagnostic breast MRI to differentiate benign from malignant lesions could potentially increase the specificity of diagnosis in the clinical setting.
Authors: Laurent Huwart; Christine Sempoux; Eric Vicaut; Najat Salameh; Laurence Annet; Etienne Danse; Frank Peeters; Leon C ter Beek; Jacques Rahier; Ralph Sinkus; Yves Horsmans; Bernard E Van Beers Journal: Gastroenterology Date: 2008-04-04 Impact factor: 22.682
Authors: K A Kvistad; I J Bakken; I S Gribbestad; B Ehrnholm; S Lundgren; H E Fjøsne; O Haraldseth Journal: J Magn Reson Imaging Date: 1999-08 Impact factor: 4.813
Authors: Constance D Lehman; Constantine Gatsonis; Christiane K Kuhl; R Edward Hendrick; Etta D Pisano; Lucy Hanna; Sue Peacock; Stanley F Smazal; Daniel D Maki; Thomas B Julian; Elizabeth R DePeri; David A Bluemke; Mitchell D Schnall Journal: N Engl J Med Date: 2007-03-28 Impact factor: 91.245
Authors: Ahmed A Haruoni; Jakir Hossain; Riham El Khouli; Kant M Matsuda; David A Bluemke; Nael F Osman; Michael A Jacobs Journal: Med Phys Date: 2012-12 Impact factor: 4.071
Authors: Ahmed A Harouni; Ahmed M Gharib; Nael F Osman; Caryn Morse; Theo Heller; Khaled Z Abd-Elmoniem Journal: Magn Reson Med Date: 2014-07-31 Impact factor: 4.668
Authors: Grigorios Korosoglou; Sorin Giusca; Nina P Hofmann; Amit R Patel; Tomas Lapinskas; Burkert Pieske; Henning Steen; Hugo A Katus; Sebastian Kelle Journal: ESC Heart Fail Date: 2019-04-25