OBJECTIVE: To investigate the repeatability of the quantitative magnetic resonance imaging (MRI) metric (apparent diffusion coefficient [ADC]) derived from reduced field-of-view diffusion-weighted (rFOV DWI) on thyroid glands in a clinical setting. MATERIALS AND METHODS: Ten healthy human volunteers were enrolled in MRI studies performed on a 3-T MRI scanner. Each volunteer was designed to undergo 3 longitudinal examinations (2 weeks apart) with 2 repetitive sessions within each examination, which included rFOV and conventional full field-of-view (fFOV) DWI scans. Diffusion-weighted images were assessed and scored based on image characteristics. Apparent diffusion coefficient values of thyroid glands from all participants were calculated based on regions of interest. Repeatability analysis was performed based on the framework proposed by the Quantitative Imaging Biomarker Alliance, generating 4 repeatability metrics: within-participant variance ((Equation is included in full-text article.)), repeatability coefficients, intraclass correlation coefficient, and within-participant coefficient of variation. Student t test was used to compare the performance difference between rFOV and fFOV DWI. RESULTS: The overall image quality from rFOV DWI was significantly higher than that from fFOV DWI (P = 0.04). The ADC values calculated from rFOV DWI were significantly lower than corresponding values from fFOV DWI (P < 0.001). There was no significant difference in ADC values across sessions and examinations in either rFOV or fFOV DWI (P > 0.05). Reduced field-of-view DWI had lower values of (Equation is included in full-text article.), repeatability coefficient, and within-participant coefficient of variation and had a higher value of intraclass correlation coefficient compared with fFOV DWI across either sessions or examinations. CONCLUSIONS: This study demonstrated that rFOV DWI produced more superior-quality DWI images and more repeatable ADC measurements compared with fFOV DWI, thus providing a feasible quantitative imaging tool for investigating thyroid glands in clinical settings.
OBJECTIVE: To investigate the repeatability of the quantitative magnetic resonance imaging (MRI) metric (apparent diffusion coefficient [ADC]) derived from reduced field-of-view diffusion-weighted (rFOV DWI) on thyroid glands in a clinical setting. MATERIALS AND METHODS: Ten healthy human volunteers were enrolled in MRI studies performed on a 3-T MRI scanner. Each volunteer was designed to undergo 3 longitudinal examinations (2 weeks apart) with 2 repetitive sessions within each examination, which included rFOV and conventional full field-of-view (fFOV) DWI scans. Diffusion-weighted images were assessed and scored based on image characteristics. Apparent diffusion coefficient values of thyroid glands from all participants were calculated based on regions of interest. Repeatability analysis was performed based on the framework proposed by the Quantitative Imaging Biomarker Alliance, generating 4 repeatability metrics: within-participant variance ((Equation is included in full-text article.)), repeatability coefficients, intraclass correlation coefficient, and within-participant coefficient of variation. Student t test was used to compare the performance difference between rFOV and fFOV DWI. RESULTS: The overall image quality from rFOV DWI was significantly higher than that from fFOV DWI (P = 0.04). The ADC values calculated from rFOV DWI were significantly lower than corresponding values from fFOV DWI (P < 0.001). There was no significant difference in ADC values across sessions and examinations in either rFOV or fFOV DWI (P > 0.05). Reduced field-of-view DWI had lower values of (Equation is included in full-text article.), repeatability coefficient, and within-participant coefficient of variation and had a higher value of intraclass correlation coefficient compared with fFOV DWI across either sessions or examinations. CONCLUSIONS: This study demonstrated that rFOV DWI produced more superior-quality DWI images and more repeatable ADC measurements compared with fFOV DWI, thus providing a feasible quantitative imaging tool for investigating thyroid glands in clinical settings.
Authors: Dariya Malyarenko; Craig J Galbán; Frank J Londy; Charles R Meyer; Timothy D Johnson; Alnawaz Rehemtulla; Brian D Ross; Thomas L Chenevert Journal: J Magn Reson Imaging Date: 2012-09-28 Impact factor: 4.813
Authors: Thomas L Chenevert; Craig J Galbán; Marko K Ivancevic; Susan E Rohrer; Frank J Londy; Thomas C Kwee; Charles R Meyer; Timothy D Johnson; Alnawaz Rehemtulla; Brian D Ross Journal: J Magn Reson Imaging Date: 2011-10 Impact factor: 4.813
Authors: Lisa Singer; Lisa J Wilmes; Emine U Saritas; Ajit Shankaranarayanan; Evelyn Proctor; Dorota J Wisner; Belinda Chang; Bonnie N Joe; Dwight G Nishimura; Nola M Hylton Journal: Acad Radiol Date: 2011-12-22 Impact factor: 3.173
Authors: J B Andre; G Zaharchuk; E Saritas; S Komakula; A Shankaranarayan; S Banerjee; J Rosenberg; D G Nishimura; N J Fischbein Journal: AJNR Am J Neuroradiol Date: 2012-05-03 Impact factor: 3.825
Authors: Lisa J Wilmes; Rebekah L McLaughlin; David C Newitt; Lisa Singer; Sumedha P Sinha; Evelyn Proctor; Dorota J Wisner; Emine U Saritas; John Kornak; Ajit Shankaranarayanan; Suchandrima Banerjee; Ella F Jones; Bonnie N Joe; Nola M Hylton Journal: Acad Radiol Date: 2013-05 Impact factor: 3.173
Authors: Jessica M Winfield; Nina Tunariu; Mihaela Rata; Keiko Miyazaki; Neil P Jerome; Michael Germuska; Matthew D Blackledge; David J Collins; Johann S de Bono; Timothy A Yap; Nandita M deSouza; Simon J Doran; Dow-Mu Koh; Martin O Leach; Christina Messiou; Matthew R Orton Journal: Radiology Date: 2017-03-16 Impact factor: 11.105
Authors: David Aramburu Núñez; Yonggang Lu; Ramesh Paudyal; Vaios Hatzoglou; Andre L Moreira; Jung Hun Oh; Hilda E Stambuk; Yousef Mazaheri; Mithat Gonen; Ronald A Ghossein; Ashok R Shaha; R Michael Tuttle; Amita Shukla-Dave Journal: Tomography Date: 2019-03