Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI). Materials and Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed. Results: Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001). Conclusion T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.

Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI). Materials and Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed. Results: Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001). Conclusion T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.

Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI). Materials and Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed. Results: Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001). Conclusion T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.

Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI). Materials and Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed. Results: Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001). Conclusion T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.

Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI). Materials and Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed. Results: Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001). Conclusion T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.

Methods: We assessed baseline neutral upright, standing flexion, seated lateral radiographs, and magnetic resonance imaging (MRI) for patients identified with spondylolisthesis from January 2021 to May 2022 by a single spine surgeon. DS was classified by Meyerding and Clinical and Radiographic Degenerative Spondylolisthesis classifications. A difference of >10° or >8% between views, respectively, was used to characterize angular and translational instability. Analysis of variance and paired chi-square tests were utilized to compare modalities. Results: A total of 136 patients were included. Seated lateral and standing flexion radiographs showed the greatest slip percentage (16.0% and 16.7%), while MRI revealed the lowest (12.2%, p <0.001). Standing flexion and lateral radiographs when seated produced more kyphosis (4.66° and 4.97°, respectively) than neutral upright and MRI (7.19° and 7.20°, p <0.001). Seated lateral performed similarly to standing flexion in detecting all measurement parameters and categorizing DS (all p >0.05). Translational instability was shown to be more prevalent when associated with seated lateral or standing flexion than when combined with neutral upright (31.5% vs. 20.2%, p =0.041; and 28.1% vs. 14.6%, p =0.014, respectively). There were no differences between seated lateral or standing flexion in the detection of instability (all p >0.20). Conclusions Seated lateral radiographs are appropriate alternatives for standing flexion radiographs. Films taken when standing up straight do not offer any more information for DS detection. Rather than standing flexion-extension radiographs, instability can be detected using an MRI, which is often performed preoperatively, paired with a single seated lateral radiograph.

Methods: Patients undergoing primary, elective 1–3 level ACDF for radiculopathy at a single academic center between 2015 and 2021 were identified retrospectively. Cervical FS was evaluated using axial T2-weighted MRI images via a validated grading scale. The maximum degree of stenosis was used for multilevel disease. Motor symptoms were classified using encounters at their final preoperative and first postoperative visits, with examinations ≤3/5 indicating weakness. PROMs were obtained preoperatively and at 1-year follow-up. Bivariate analysis was used to compare outcomes based on stenosis severity, followed by multivariable analysis. Results: This study included 354 patients, 157 with moderate stenosis and 197 with severe stenosis. Overall, 58 patients (16.4%) presented with upper extremity weakness ≤3/5. A similar number of patients in both groups presented with baseline motor weakness (13.5% vs. 16.55, p =0.431). Postoperatively, 97.1% and 87.0% of patients with severe and moderate FS, respectively, experienced full motor recovery (p =0.134). At 1-year, patients with severe neuroforaminal stenosis presented with significantly worse 12-item Short Form Survey Physical Component Score (PCS-12) (33.3 vs. 37.3, p =0.049) but demonstrated a greater magnitude of improvement (Δ PCS-12: 5.43 vs. 0.87, p =0.048). Worse stenosis was independently associated with greater ΔPCS-12 at 1-year (β =5.59, p =0.022). Conclusions Patients with severe FS presented with worse preoperative physical health. While ACDF improved outcomes and conferred similar motor recovery in all patients, those with severe FS reported much better improvement in physical function.

Whole body ultrasound can be used to improve the speed and accuracy of evaluation of an increasing number of organ systems in the critically ill. Cardiac and abdominal ultrasound can be used to identify the mechanisms and etiology of hemodynamic instability. In hypoxemia or hypercarbia, lung ultrasound can rapidly identify the etiology of the condition with an accuracy that is equivalent to that of computed tomography. For encephalopathy, ocular ultrasound and transcranial Doppler can identify elevated intracranial pressure and midline shift. Renal and bladder ultrasound can identify the mechanisms and etiology of renal failure. Ultrasound can also improve the accuracy and safety of percutaneous procedures and should be currently used routinely for central vein catheterization and percutaneous tracheostomy.

Whole body ultrasound can be used to improve the speed and accuracy of evaluation of an increasing number of organ systems in the critically ill. Cardiac and abdominal ultrasound can be used to identify the mechanisms and etiology of hemodynamic instability. In hypoxemia or hypercarbia, lung ultrasound can rapidly identify the etiology of the condition with an accuracy that is equivalent to that of computed tomography. For encephalopathy, ocular ultrasound and transcranial Doppler can identify elevated intracranial pressure and midline shift. Renal and bladder ultrasound can identify the mechanisms and etiology of renal failure. Ultrasound can also improve the accuracy and safety of percutaneous procedures and should be currently used routinely for central vein catheterization and percutaneous tracheostomy.
Anoxia ; Brain Diseases ; Catheterization ; Catheters ; Critical Care ; Critical Illness ; Hemodynamics ; Intensive Care Units ; Intracranial Hypertension ; Lung ; Operating Rooms ; Renal Insufficiency ; Tracheostomy ; Ultrasonography ; Urinary Bladder ; Veins

Acupuncture Therapy ; Humans ; Needles