The Experts below are selected from a list of 858897 Experts worldwide ranked by ideXlab platform

Mark A Griswold - One of the best experts on this subject based on the ideXlab platform.

  • Magnetic Resonance fingerprinting
    Nature, 2013
    Co-Authors: Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L Sunshine, Jeffrey L Duerk, Mark A Griswold
    Abstract:

    Magnetic Resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a Magnetic Resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization—which we term ‘Magnetic Resonance fingerprinting’ (MRF)—that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a Magnetic Resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy. A new approach to Magnetic Resonance, ‘Magnetic Resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data. Although nuclear Magnetic Resonance is a powerful analytical tool for many scientific and medical disciplines, usually only a fraction of its potential power is harnessed. Most implementations are qualitative, and restricted in the range of properties that are probed. Dan Ma and colleagues introduce a new approach — termed Magnetic Resonance fingerprinting — aimed at greatly enhancing the amount of quantitative information that can be obtained in one measurement. Their approach combines a data-acquisition scheme that is indiscriminate in the material properties that it probes with pattern-recognition algorithms that look for the 'fingerprints' of interest within the data. Magnetic Resonance fingerprinting has the potential to detect and analyse early indicators of disease or complex changes in materials, as well as increasing the sensitivity, specificity and speed of Magnetic Resonance studies.

  • Magnetic Resonance fingerprinting
    Nature, 2013
    Co-Authors: Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L Sunshine, Jeffrey L Duerk, Mark A Griswold
    Abstract:

    A new approach to Magnetic Resonance, ‘Magnetic Resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data.

Vikas Gulani - One of the best experts on this subject based on the ideXlab platform.

  • Magnetic Resonance fingerprinting
    Nature, 2013
    Co-Authors: Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L Sunshine, Jeffrey L Duerk, Mark A Griswold
    Abstract:

    Magnetic Resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a Magnetic Resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization—which we term ‘Magnetic Resonance fingerprinting’ (MRF)—that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a Magnetic Resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy. A new approach to Magnetic Resonance, ‘Magnetic Resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data. Although nuclear Magnetic Resonance is a powerful analytical tool for many scientific and medical disciplines, usually only a fraction of its potential power is harnessed. Most implementations are qualitative, and restricted in the range of properties that are probed. Dan Ma and colleagues introduce a new approach — termed Magnetic Resonance fingerprinting — aimed at greatly enhancing the amount of quantitative information that can be obtained in one measurement. Their approach combines a data-acquisition scheme that is indiscriminate in the material properties that it probes with pattern-recognition algorithms that look for the 'fingerprints' of interest within the data. Magnetic Resonance fingerprinting has the potential to detect and analyse early indicators of disease or complex changes in materials, as well as increasing the sensitivity, specificity and speed of Magnetic Resonance studies.

  • Magnetic Resonance fingerprinting
    Nature, 2013
    Co-Authors: Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L Sunshine, Jeffrey L Duerk, Mark A Griswold
    Abstract:

    A new approach to Magnetic Resonance, ‘Magnetic Resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data.

Takeshi Maruo - One of the best experts on this subject based on the ideXlab platform.

  • Magnetic Resonance guided focused ultrasound surgery for uterine fibroids relationship between the therapeutic effects and signal intensity of preexisting t2 weighted Magnetic Resonance images
    American Journal of Obstetrics and Gynecology, 2007
    Co-Authors: Kaoru Funaki, Hidenobu Fukunishi, Tsuyoshi Funaki, Katsuhiro Sawada, Yasushi Kaji, Takeshi Maruo
    Abstract:

    Objective This study was undertaken to clarify the relationship between the signal intensity of T2-weighted Magnetic Resonance images and the therapeutic effect of Magnetic Resonance-guided focused ultrasound surgery (MRgFUS) on uterine fibroids. Study design Ninety-five fibroids in 63 patients were classified into 3 types based on the signal intensity of T2-weighted Magnetic Resonance images as follows: type 1, low intensity; type 2, intermediate intensity; type 3, high intensity. The treated area ratio of MRgFUS and the volume reduction ratio 6 months after treatment were used as the indices of therapeutic effect. Results The treated area ratio of type 3 fibroids was the lowest among the 3 types ( P r = 0.64; P Conclusion The efficacy of MRgFUS correlates with the signal intensity of T2-weighted Magnetic Resonance images. Type 1 and type 2 fibroids are suitable candidates for MRgFUS, whereas type 3 fibroids are not.

  • Magnetic Resonance guided focused ultrasound surgery for uterine fibroids relationship between the therapeutic effects and signal intensity of preexisting t2 weighted Magnetic Resonance images
    American Journal of Obstetrics and Gynecology, 2007
    Co-Authors: Kaoru Funaki, Hidenobu Fukunishi, Tsuyoshi Funaki, Katsuhiro Sawada, Yasushi Kaji, Takeshi Maruo
    Abstract:

    OBJECTIVE: This study was undertaken to clarify the relationship between the signal intensity of T2-weighted Magnetic Resonance images and the therapeutic effect of Magnetic Resonance-guided focused ultrasound surgery (MRgFUS) on uterine fibroids. STUDY DESIGN: Ninety-five fibroids in 63 patients were classified into 3 types based on the signal intensity of T2-weighted Magnetic Resonance images as follows: type 1, low intensity; type 2, intermediate intensity; type 3, high intensity. The treated area ratio of MRgFUS and the volume reduction ratio 6 months after treatment were used as the indices of therapeutic effect. RESULTS: The treated area ratio of type 3 fibroids was the lowest among the 3 types (P < .01). The volume reduction ratio correlated with the treated area ratio (r = 0.64; P < .01). CONCLUSION: The efficacy of MRgFUS correlates with the signal intensity of T2-weighted Magnetic Resonance images. Type 1 and type 2 fibroids are suitable candidates for MRgFUS, whereas type 3 fibroids are not.

Peter A. Pinto - One of the best experts on this subject based on the ideXlab platform.

  • prostate Magnetic Resonance imaging and Magnetic Resonance imaging targeted biopsy in patients with a prior negative biopsy a consensus statement by aua and sar
    The Journal of Urology, 2016
    Co-Authors: Andrew B Rosenkrantz, Sadhna Verma, Peter L Choyke, Steven C Eberhardt, Scott E Eggener, Krishnanath Gaitonde, Masoom A Haider, Daniel Margolis, Leonard S Marks, Peter A. Pinto
    Abstract:

    Purpose: After an initial negative biopsy there is an ongoing need for strategies to improve patient selection for repeat biopsy as well as the diagnostic yield from repeat biopsies.Materials and Methods: As a collaborative initiative of the AUA (American Urological Association) and SAR (Society of Abdominal Radiology) Prostate Cancer Disease Focused Panel, an expert panel of urologists and radiologists conducted a literature review and formed consensus statements regarding the role of prostate Magnetic Resonance imaging and Magnetic Resonance imaging targeted biopsy in patients with a negative biopsy, which are summarized in this review.Results: The panel recognizes that many options exist for men with a previously negative biopsy. If a biopsy is recommended, prostate Magnetic Resonance imaging and subsequent Magnetic Resonance imaging targeted cores appear to facilitate the detection of clinically significant disease over standardized repeat biopsy. Thus, when high quality prostate Magnetic Resonance im...

  • Magnetic Resonance imaging ultrasound fusion guided prostate biopsy improves cancer detection following transrectal ultrasound biopsy and correlates with multiparametric Magnetic Resonance imaging
    The Journal of Urology, 2011
    Co-Authors: Peter A. Pinto, Angelo A Baccala, Compton Benjamin, Jochen Kruecker, Samuel Kadoury, Ardeshir R Rastinehad, Paul H Chung, Sheng Xu, Celene Chua
    Abstract:

    Purpose: A novel platform was developed that fuses pre-biopsy Magnetic Resonance imaging with real-time transrectal ultrasound imaging to identify and biopsy lesions suspicious for prostate cancer. The cancer detection rates for the first 101 patients are reported.Materials and Methods: This prospective, single institution study was approved by the institutional review board. Patients underwent 3.0 T multiparametric Magnetic Resonance imaging with endorectal coil, which included T2-weighted, spectroscopic, dynamic contrast enhanced and diffusion weighted Magnetic Resonance imaging sequences. Lesions suspicious for cancer were graded according to the number of sequences suspicious for cancer as low (2 or less), moderate (3) and high (4) suspicion. Patients underwent standard 12-core transrectal ultrasound biopsy and Magnetic Resonance imaging/ultrasound fusion guided biopsy with electroMagnetic tracking of Magnetic Resonance imaging lesions. Chi-square and within cluster resampling analyses were used to co...

Jeffrey L Duerk - One of the best experts on this subject based on the ideXlab platform.

  • Magnetic Resonance fingerprinting
    Nature, 2013
    Co-Authors: Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L Sunshine, Jeffrey L Duerk, Mark A Griswold
    Abstract:

    Magnetic Resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a Magnetic Resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization—which we term ‘Magnetic Resonance fingerprinting’ (MRF)—that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a Magnetic Resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy. A new approach to Magnetic Resonance, ‘Magnetic Resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data. Although nuclear Magnetic Resonance is a powerful analytical tool for many scientific and medical disciplines, usually only a fraction of its potential power is harnessed. Most implementations are qualitative, and restricted in the range of properties that are probed. Dan Ma and colleagues introduce a new approach — termed Magnetic Resonance fingerprinting — aimed at greatly enhancing the amount of quantitative information that can be obtained in one measurement. Their approach combines a data-acquisition scheme that is indiscriminate in the material properties that it probes with pattern-recognition algorithms that look for the 'fingerprints' of interest within the data. Magnetic Resonance fingerprinting has the potential to detect and analyse early indicators of disease or complex changes in materials, as well as increasing the sensitivity, specificity and speed of Magnetic Resonance studies.

  • Magnetic Resonance fingerprinting
    Nature, 2013
    Co-Authors: Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L Sunshine, Jeffrey L Duerk, Mark A Griswold
    Abstract:

    A new approach to Magnetic Resonance, ‘Magnetic Resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data.