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"Conformance of a 3T radiotherapy MRI scanner to the QIBA Diffusion Pro" by Madeline E. Carr, Kathryn E. Keenan et al.

Purpose: To assess the technical performance of the apparent diffusion coefficient (ADC) on a dedicated 3T radiotherapy scanner, using a standardized phantom and sequences. Investigations into factors that could impact the technical performance of ADC in the clinic were also completed, including changing the slice-encoded imaging direction and the reference sample ADC value. Methods: ADC acquisitions were performed monthly on an isotropic diffusion phantom over 1 year. Measurements of ADC %bias, coefficients of variation for short-/long-term repeatability and precision (CVST/CVLT and CVP), and b-value dependency (Depb) were calculated. The measurements were then assessed according to the Quantitative Imaging Biomarker Alliance (QIBA) Diffusion Profile specifications. Results: The average of all measurements over the year was within Profile recommended ranges. This included when testing was performed in different imaging directions, and on samples that had different ADC reference values ....

Quantitative Imaging Biomarker Alliance , Diffusion Profile , Apparent Diffusion Coefficient , Diffusion Weighted Imaging , Quantitative Imaging Biomarker Alliance , Quantitative Magnetic Resonance Imaging ,

TULSA-PRO® Was Front and Center at AUA2022

TULSA-PRO® Was Front and Center at AUA2022
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United States , Stephen Kilmer , Kennetha Goldberg , Arun Menawat , Surgery Therapy New Technology , Drug Administration , American Urological Association , Turku University Hospital , Turku University Hospital Mikael Anttinen , Ut Southwestern Medical Center , China National Medical Products Administration , University Of Chicago Scott Eggener , Department Of Urology , Health Canada , New Orleans , Assistant Professor , Medical Center , Plenary Session , Scott Eggener , Prostate Cancer , Mikael Anttinen , Prostatic Hyperplasia , Surgery Therapy , New Technology , Profound Medical , Weighted Imaging ,

TULSA-PRO® Was Front and Center at AUA2022

TULSA-PRO® Was Front and Center at AUA2022
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United States , Kennetha Goldberg , Arun Menawat , Surgery Therapy New Technology , Drug Administration , American Urological Association , Turku University Hospital , Turku University Hospital Mikael Anttinen , Ut Southwestern Medical Center , China National Medical Products Administration , University Of Chicago Scott Eggener , Department Of Urology , Health Canada , Wall Street , New Orleans , Assistant Professor , Medical Center , Plenary Session , Scott Eggener , Prostate Cancer , Mikael Anttinen , Prostatic Hyperplasia , Surgery Therapy , New Technology , Profound Medical , Weighted Imaging ,

Study of the Diffusion Tensor Imaging for Preclinical Tensor

Study of the Diffusion Tensor Imaging for Preclinical Therapeutic Efficacy of Umbilical Cord Mesenchymal Stem Cell Transplantation in the Treatment of SCI ....

Eteläuomen Läi , International Classification Of Diseases , Experimental Group Of Patients , Ethics Committee , Shenzhen Beike Stem Cell Biotechnology Co Ltd , Lexperimental Group , International Classification , Ninth Revision , Medical Ethics Committee , Kunming Medical University , Revaluation Method , Diffusion Tensor , Siemens Sonata , Stem Cell , Safety Indices , Control Groups Before , Patients Before , After Treatment , Apparent Diffusion Coefficient , Diffusion Coefficient , Fractional Anisotropy , Lesion Levels , Control Patients Before , After Transplantation , Lesion Site , Normal Site Before ,

Child Brain Tumors can be Classified by Advanced Imaging and AI

Child Brain Tumors can be Classified by Advanced Imaging and AI
Being able to classify a brain tumor s type, without the use of biopsy, is hard to do; however diffusion weighted imaging, an advanced imaging technique, when combined with machine learning, can help, a study has found
Example MR images from paediatric brain tumour patients. This first column shows T1-weighted images following the injection of gadolinium contrast agent. The second column shows T2-weighted images and the final column shows apparent diffusion coefficient maps calculated from diffusion-weighted images. (
a–
d–
g–
i) were acquired from a patient with a Medulloblastoma. Image courtesy of Nature Research Journal ....

United Kingdom , Theo Arvanitis , Andrew Peet , University Of Warwick , University Of Birmingham , Institute Of Digital Health , United Kingdom Based , Scientific Reports , Apparent Diffusion Coefficient , Apparent Diffusion Coeffcient , Digital Health , Magnetic Resonance , Clinical Paediatric Oncology , Birmingham Children , ஒன்றுபட்டது கிஂக்டம் , தியோ அர்வானிடிஸ் , ஆண்ட்ரூ பீட் , பல்கலைக்கழகம் ஆஃப் வார்விக் , பல்கலைக்கழகம் ஆஃப் பர்மிங்காம் , நிறுவனம் ஆஃப் டிஜிட்டல் ஆரோக்கியம் , ஒன்றுபட்டது கிஂக்டம் அடிப்படையிலானது , அறிவியல் அறிக்கைகள் , டிஜிட்டல் ஆரோக்கியம் , காந்த அதிர்வு , மருத்துவ குழந்தை புற்றுநோயியல் , பர்மிங்காம் குழந்தைகள் ,