scholarly journals MR imaging of the fetal brain at 1.5T and 3.0T field strengths: comparing specific absorption rate (SAR) and image quality

2015 ◽  
Vol 43 (2) ◽  
Author(s):  
Uday Krishnamurthy ◽  
Jaladhar Neelavalli ◽  
Swati Mody ◽  
Lami Yeo ◽  
Pavan K. Jella ◽  
...  

Abstract: Our two objectives were to evaluate the feasibility of fetal brain magnetic resonance imaging (MRI) using a fast spin echo sequence at 3.0T field strength with low radio frequency (: T2 weighted images of the fetal brain at 1.5T were compared to similar data obtained in the same fetus using a modified sequence at 3.0T. Quantitative whole-body SAR and normalized image signal to noise ratio (SNR), a nominal scoring scheme based evaluation of diagnostic image quality, and tissue contrast and conspicuity for specific anatomical structures in the brain were compared between 1.5T and 3.0T.: Twelve pregnant women underwent both 1.5T and 3.0T MRI examinations. The image SNR was significantly higher (P=0.03) and whole-body SAR was significantly lower (P<0.0001) for images obtained at 3.0T compared to 1.5T. All cases at both field strengths were scored as having diagnostic image quality. Images from 3.0T MRI (compared to 1.5T) were equal (57%; 21/37) or superior (35%; 13/37) for tissue contrast and equal (61%; 20/33) or superior (33%, 11/33) for conspicuity.It is possible to obtain fetal brain images with higher resolution and better SNR at 3.0T with simultaneous reduction in SAR compared to 1.5T. Images of the fetal brain obtained at 3.0T demonstrated superior tissue contrast and conspicuity compared to 1.5T.

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Akshay S. Chaudhari ◽  
Erik Mittra ◽  
Guido A. Davidzon ◽  
Praveen Gulaka ◽  
Harsh Gandhi ◽  
...  

AbstractMore widespread use of positron emission tomography (PET) imaging is limited by its high cost and radiation dose. Reductions in PET scan time or radiotracer dosage typically degrade diagnostic image quality (DIQ). Deep-learning-based reconstruction may improve DIQ, but such methods have not been clinically evaluated in a realistic multicenter, multivendor environment. In this study, we evaluated the performance and generalizability of a deep-learning-based image-quality enhancement algorithm applied to fourfold reduced-count whole-body PET in a realistic clinical oncologic imaging environment with multiple blinded readers, institutions, and scanner types. We demonstrate that the low-count-enhanced scans were noninferior to the standard scans in DIQ (p < 0.05) and overall diagnostic confidence (p < 0.001) independent of the underlying PET scanner used. Lesion detection for the low-count-enhanced scans had a high patient-level sensitivity of 0.94 (0.83–0.99) and specificity of 0.98 (0.95–0.99). Interscan kappa agreement of 0.85 was comparable to intrareader (0.88) and pairwise inter-reader agreements (maximum of 0.72). SUV quantification was comparable in the reference regions and lesions (lowest p-value=0.59) and had high correlation (lowest CCC = 0.94). Thus, we demonstrated that deep learning can be used to restore diagnostic image quality and maintain SUV accuracy for fourfold reduced-count PET scans, with interscan variations in lesion depiction, lower than intra- and interreader variations. This method generalized to an external validation set of clinical patients from multiple institutions and scanner types. Overall, this method may enable either dose or exam-duration reduction, increasing safety and lowering the cost of PET imaging.


2018 ◽  
Author(s):  
Melanie U Knopp ◽  
Katherine Binzel ◽  
Chadwick L Wright ◽  
Jun Zhang ◽  
Michael V Knopp

BACKGROUND Conventional approaches to improve the quality of clinical patient imaging studies focus predominantly on updating or replacing imaging equipment; however, it is often not considered that patients can also highly influence the diagnostic quality of clinical imaging studies. Patient-specific artifacts can limit the diagnostic image quality, especially when patients are uncomfortable, anxious, or agitated. Imaging facility or environmental conditions can also influence the patient’s comfort and willingness to participate in diagnostic imaging studies, especially when performed in visually unesthetic, anxiety-inducing, and technology-intensive imaging centers. When given the opportunity to change a single aspect of the environmental or imaging facility experience, patients feel much more in control of the otherwise unfamiliar and uncomfortable setting. Incorporating commercial, easily adaptable, ambient lighting products within clinical imaging environments allows patients to individually customize their environment for a more personalized and comfortable experience. OBJECTIVE The aim of this pilot study was to use a customizable colored light-emitting diode (LED) lighting system within a clinical imaging environment and demonstrate the feasibility and initial findings of enabling healthy subjects to customize the ambient lighting and color. Improving the patient experience within clinical imaging environments with patient-preferred ambient lighting and color may improve overall patient comfort, compliance, and participation in the imaging study and indirectly contribute to improving diagnostic image quality. METHODS We installed consumer-based internet protocol addressable LED lights using the ZigBee standard in different PET/CT scan rooms within a clinical imaging environment. We recruited healthy volunteers (n=35) to generate pilot data in order to develop a subsequent clinical trial. The visual perception assessment procedure utilized questionnaires with preprogrammed light/color settings and further assessed how subjects preferred ambient light and color within a clinical imaging setting. RESULTS Technical implementation using programmable LED lights was performed without any hardware or electrical modifications to the existing clinical imaging environment. Subject testing revealed substantial variabilities in color perception; however, clear trends in subject color preference were noted. In terms of the color hue of the imaging environment, 43% (15/35) found blue and 31% (11/35) found yellow to be the most relaxing. Conversely, 69% (24/35) found red, 17% (6/35) found yellow, and 11% (4/35) found green to be the least relaxing. CONCLUSIONS With the majority of subjects indicating that colored lighting within a clinical imaging environment would contribute to an improved patient experience, we predict that enabling patients to customize environmental factors like lighting and color to individual preferences will improve patient comfort and patient satisfaction. Improved patient comfort in clinical imaging environments may also help to minimize patient-specific imaging artifacts that can otherwise limit diagnostic image quality. CLINICALTRIAL ClinicalTrials.gov NCT03456895; https://clinicaltrials.gov/ct2/show/NCT03456895


2018 ◽  
Vol 20 (2) ◽  
pp. 1202-1213 ◽  
Author(s):  
Tomas Budrys ◽  
Vincentas Veikutis ◽  
Saulius Lukosevicius ◽  
Rymante Gleizniene ◽  
Egle Monastyreckiene ◽  
...  

2017 ◽  
Vol 106 (7) ◽  
pp. 485-492 ◽  
Author(s):  
Marco M. Ochs ◽  
Fabian aus dem Siepen ◽  
Thomas Fritz ◽  
Florian Andre ◽  
Gitsios Gitsioudis ◽  
...  

2016 ◽  
Vol 25 (4) ◽  
pp. 230-234
Author(s):  
Wai-Yung Yu ◽  
Thye Sin Ho ◽  
Henry Ko ◽  
Wai-Yee Chan ◽  
Serene Ong ◽  
...  

Introduction: The use of computed tomography (CT) imaging as a diagnostic modality is increasing rapidly and CT is the dominant contributor to diagnostic medical radiation exposure. The aim of this project was to reduce the effective radiation dose to patients undergoing cranial CT examination, while maintaining diagnostic image quality. Methods: Data from a total of 1003, 132 and 27 patients were examined for three protocols: CT head, CT angiography (CTA), and CT perfusion (CTP), respectively. Following installation of adaptive iterative dose reduction (AIDR) 3D software, tube current was lowered in consecutive cycles, in a stepwise manner and effective radiation doses measured at each step. Results: Baseline effective radiation doses for CT head, CTA and CTP were 1.80, 3.60 and 3.96 mSv, at currents of 300, 280 and 130–150 mA, respectively. Using AIDR 3D and final reduced currents of 160, 190 and 70–100 mA for CT head, CTA and CTP gave effective doses of 1.29, 3.18 and 2.76 mSv, respectively. Conclusion: We demonstrated that satisfactory reductions in the effective radiation dose for CT head (28.3%), CTA (11.6%) and CTP (30.1%) can be achieved without sacrificing diagnostic image quality. We have also shown that iterative reconstruction techniques such as AIDR 3D can be effectively used to help reduce effective radiation dose. The dose reductions were performed within a short period and can be easily achievable, even in busy departments.


1999 ◽  
Vol 72 (853) ◽  
pp. 55-61 ◽  
Author(s):  
A Lowe ◽  
A Finch ◽  
D Boniface ◽  
R Chaudhuri ◽  
J Shekhdar

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