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Three-dimensional ultrasound for assessing synovial blood flow with exercise in thumb osteoarthritis
Automatic deep learning-based segmentation of neonatal cerebral ventricles from 3D ultrasound images
Clinically, 2D ultrasound (US) through the fontanelles ('soft spots') of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up cerebrospinal fluid (CSF) ('ventricle tap', VT) might be indicated for a patient; however, quantitative measurements of the growth of the ventricles are often not performed. There is no consensus on when a neonate with PHVD should have an intervention and often interventions are performed after the potential for brain damage is quite high.
Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients.
We will describe the potential utility of quantitative 2D and 3D US to monitor and manage PHVD in neonates. Specifically, we will look to determine image-based measurement thresholds for patients who will require VT in comparison to patients with PHVD who resolve without intervention. Additionally, since many patients who have an initial VT will require subsequent interventions, we look at the potential for US to determine which PHVD patients will require additional VT after the initial one has been performed.
3D prostate MR-TRUS non-rigid registration using dual optimization with volume-preserving constraint
Purpose: To compare HDR-BT needle tip localization accuracy between 2D and 3D-TRUS.
Methods: 5 prostate cancer patients underwent conventional 2D TRUS guided HDR-BT, during which 3D images were also acquired for post-operative registration and segmentation. Needle end-length measurements were taken, providing a gold standard for insertion depths.
Results: 73 needles were analyzed from all 5 patients. Needle tip position differences between imaging techniques was found to be largest in the S/I direction with mean±SD of -2.5±4.0 mm. End-length measurements indicated that 3D TRUS provided statistically significantly lower mean±SD insertion depth error of -0.2±3.4 mm versus 2.3±3.7 mm with 2D guidance (p < .001).
Conclusions: 3D TRUS may provide more accurate HDR-BT needle localization than conventional 2D TRUS guidance for the majority of HDR-BT needles.
Methods: Anatomical 1H and functional 3He MRI were acquired in 5 healthy asymptomatic ex-smokers and 7 ex-smokers with chronic obstructive pulmonary disease (COPD) at inspiration breath-hold. Thoracic CT was performed within ten minutes of MRI using the same breath-hold volume. Landmark-based affine registration methods previously validated for imaging of COPD, was based on corresponding fiducial markers located in both CT and 1H MRI coronal slices and compared with shape-based CT-MRI non-rigid registration. Shape-based CT-MRI registration was developed by first identifying the shapes of the lung cavities manually, and then registering the two shapes using affine and thin-plate spline algorithms. We compared registration accuracy using the fiducial localization error (FLE) and target registration error (TRE).
Results: For landmark-based registration, the TRE was 8.4±5.3 mm for whole lung and 7.8±4.6 mm for the R and L lungs registered independently (p=0.4). For shape-based registration, the TRE was 8.0±4.6 mm for whole lung as compared to 6.9±4.4 mm for the R and L lung registered independently and this difference was significant (p=0.01). The difference for shape-based (6.9±4.4 mm) and landmark-based R and L lung registration (7.8±4.6 mm) was also significant (p=.04)
Conclusion: Shape-based registration TRE was significantly improved compared to landmark-based registration when considering L and R lungs independently.
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