Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.

PURPOSE: In MRI, motion artifacts can significantly degrade image quality. Motion artifact correction methods using deep neural networks usually required extensive training on large datasets, making them time-consuming and resource-intensive. In this paper, an unsupervised deep learning-based motion artifact correction method for turbo-spin echo MRI is proposed using the deep image prior framework. THEORY AND METHODS: The proposed approach takes advantage of the high impedance to motion artifacts offered by the neural network parameterization to remove motion artifacts in MR images. The framework consists of parameterization of MR image, automatic spatial transformation, and motion simulation model. The proposed method synthesizes motion-corrupted images from the motion-corrected images generated by the convolutional neural network, where an optimization process minimizes the objective function between the synthesized images and the acquired images. RESULTS: In the simulation study of 280 slices from 14 subjects, the proposed method showed a significant increase in the averaged structural similarity index measure by 0.2737 in individual coil images and by 0.4550 in the root-sum-of-square images. In addition, the ablation study demonstrated the effectiveness of each proposed component in correcting motion artifacts compared to the corrected images produced by the baseline method. The experiments on real motion dataset has shown its clinical potential. CONCLUSION: The proposed method exhibited significant quantitative and qualitative improvements in correcting rigid and in-plane motion artifacts in MR images acquired using turbo spin-echo sequence.

Registration and quantification network (RQnet) for IVIM-DKI analysis in MRI.

PURPOSE: A deep learning method is proposed for aligning diffusion weighted images (DWIs) and estimating intravoxel incoherent motion-diffusion kurtosis imaging parameters simultaneously. METHODS: We propose an unsupervised deep learning method that performs 2 tasks: registration and quantification for intravoxel incoherent motion-diffusion kurtosis imaging analysis. A common registration method in diffusion MRI is based on minimizing dissimilarity between various DWIs, which may result in registration errors due to different contrasts in different DWIs. We designed a novel unsupervised deep learning method for both accurate registration and quantification of various diffusion parameters. In order to generate motion-simulated training data and test data, 17 volunteers were scanned without moving their heads, and 4 volunteers moved their heads during the scan in a 3 Tesla MRI. In order to investigate the applicability of the proposed method to other organs, kidney images were also obtained. We compared the registration accuracy of the proposed method, statistical parametric mapping, and a deep learning method with a normalized cross-correlation loss. In the quantification part of the proposed method, a deep learning method that considered the diffusion gradient direction was used. RESULTS: Simulations and experimental results showed that the proposed method accurately performed registration and quantification for intravoxel incoherent motion-diffusion kurtosis imaging analysis. The registration accuracy of the proposed method was high for all b values. Furthermore, quantification performance was analyzed through simulations and in vivo experiments, where the proposed method showed the best performance among the compared methods. CONCLUSION: The proposed method aligns the DWIs and accurately quantifies the intravoxel incoherent motion-diffusion kurtosis imaging parameters.

MC2 -Net: motion correction network for multi-contrast brain MRI.

PURPOSE: A motion-correction network for multi-contrast brain MRI is proposed to correct in-plane rigid motion artifacts in brain MR images using deep learning. METHOD: The proposed method consists of 2 parts: image alignment and motion correction. Alignment of multi-contrast MR images is performed in an unsupervised manner by a CNN work, yielding transformation parameters to align input images in order to minimize the normalized cross-correlation loss among multi-contrast images. Then, fine-tuning for image alignment is performed by maximizing the normalized mutual information. The motion correction network corrects motion artifacts in the aligned multi-contrast images. The correction network is trained to minimize the structural similarity loss and the VGG loss in a supervised manner. All datasets of motion-corrupted images are generated using motion simulation based on MR physics. RESULTS: A motion-correction network for multi-contrast brain MRI successfully corrected artifacts of simulated motion for 4 test subjects, showing 0.96%, 7.63%, and 5.03% increases in the average structural simularity and 5.19%, 10.2%, and 7.48% increases in the average normalized mutual information for T1 -weighted, T2 -weighted, and T2 -weighted fluid-attenuated inversion recovery images, respectively. The experimental setting with image alignment and artifact-free input images for other contrasts shows better performances in correction of simulated motion artifacts. Furthermore, the proposed method quantitatively outperforms recent deep learning motion correction and synthesis methods. Real motion experiments from 5 healthy subjects demonstrate the potential of the proposed method for use in a clinical environment. CONCLUSION: A deep learning-based motion correction method for multi-contrast MRI was successfully developed, and experimental results demonstrate the validity of the proposed method.

The optimal effect-site concentration of remifentanil to attenuate the pain caused by propofol.

BACKGROUND: The injection pain of propofol is a frequent and well-known adverse effect. This study was designed to determine the optimal effect-site concentration of remifentanil for minimizing injection pain during induction with propofol. METHODS: A total intravenous anesthetic technique was used for patients undergoing general anesthesia and remifentanil was pretreated to reach a certain target concentration before propofol injection. Using Dixon's up-and-down method, the degree of pain described by the patient was used to adjust the target concentration of remifentanil for the next patient. Ten success-failure curves (crossovers) were sought to find the effect-site concentration (EC) of remifentanil for minimizing injection pain of propofol. RESULTS: The EC of remifentanil in 50% and 95% of adult female population (EC(50) and EC(95)) for minimizing injection pain of propofol were 3.09 ng/ml (95% confidence limits [CI] 2.92-3.30 ng/ml) and 3.78 ng/ml (95% CI 3.45-3.95 ng/ml), respectively. Clinically significant hemodynamic compromise or respiratory complications were not found during remifentanil infusion. CONCLUSIONS: Maintaining 3.78 ng/ml EC of remifentanil during induction with propofol attenuate propofol injection pain without serious adverse events in female patients undergoing general anesthesia and this method may provide the patient's comfort without preparing other drugs for pain relief.

Comparison of clinical effects according to the dosage of sufentanil added to 0.5% hyperbaric bupivacaine for spinal anesthesia in patients undergoing cesarean section.

BACKGROUND: Subarachnoid block is a widely used technique for cesarean section. To improve the quality of analgesia and prolong the duration of analgesia, addition of intrathecal opioids to local anesthetics has been encouraged. We compared the effects of sufentanil 2.5 µg and 5 µg, which were added to intrathecal hyperbaric bupivacaine. METHODS: We enrolled 105 full term parturients were randomly divided into 3 groups: Group 1 (control), Group 2 (sufentanil 2.5 µg), and Group 3 (sufentanil 5 µg). In every group, 0.5% heavy bupivacaine was added according to the adjusted dose regimen. We determined the maximum level of sensory block and motor block, the quality of intraoperative analgesia, the duration of effective analgesia and side effects. RESULTS: There were no significant differences among the 3 groups in the maximum level of the sensory block and motor block. Recovery rate of the sensory block, however, was significantly slower in Group 3 than Group 1. Quality of intraopertive analgesia, muscle relaxation, and duration of effective analgesia were enhanced by increasing the dosage of intrathecal sufentanil. Frequencies of hypotension, maximum sedation level, and pruritus were directly related to the dosage of intrathecal sufentanil, whereas nausea and vomiting occurred only in the groups using sufentanil. CONCLUSIONS: The addition of sufentanil 2.5 µg for spinal anesthesia provides adequate intraoperative analgesia and good postoperative analgesia with minimal adverse effects on the mother.

Unexpected difficulty in ventilating the lungs after tracheal intubation -A case report-.

We experienced difficulty in ventilating the lungs of a patient after tracheal intubation. After intubation, an insufficient amount of tidal volume (V(T)) was delivered to the patient and the fiberoptic bronchoscopic examination identified partial abutment of the endotracheal tube (ETT) orifice against the tracheal wall. After various attempts to correctly place the ETT, a double-lumen endotracheal tube was placed to achieve a sufficient V(T). It is important to notice that even an appropriately placed ETT may get obstructed due to the left sided bevel at its tip.

Fatal pulmonary embolism and coincidental cerebral infarction after spinal anesthesia -A case report-.

A pulmonary embolism and cerebral infarction are the second and third most common acute cardiovascular diseases after a myocardial infarction. Early diagnosis and appropriate management are important clinical challenges. In this case, a fatal pulmonary embolism and extensive cerebral infarction caused cardiac arrest during spinal anesthesia for total hip replacement surgery. Transesophageal echocardiography indicated a pulmonary embolism and brain CT showed large area of acute infarction at right middle cerebral artery territory. Pulmonary CT angiogram revealed massive pulmonary embolism findings. This paper reviews this case and suggests other preventive modalities.

The relationship between symphysis-fundal height and intravenous ephedrine dose in spinal anesthesia for elective cesarean section.

BACKGROUND: A decreased lumbosacral subarachnoidal space volume is a major factor in the cephalad intrathecal spread of local anesthetics in term parturients and their subarachnoidal space is decreased due to the compressive effect of huge uteri. Therefore, they show a higher level of sensory block and hypotensive episodes. The purpose of this study is to investigate whether the symphysis-fundal height (SFH) correlates with the highest sensory level and the amount of ephedrine administered under spinal anesthesia. METHODS: Fifty-two uncomplicated parturients who consented to spinal anesthesia for elective cesarean section were studied. The SFH of all parturients had been measured just before the spinal anesthesia administered by one person. Hyperbaric bupivacaine with fentanyl 20 µg, was administered for spinal anesthesia. The amount of 0.5% bupivacaine was adjusted according to the patient's height and weight. The level of sensory block and the amounts of ephedrine to treat hypotension, nausea and vomiting were assessed. Linear regression and correlation analysis were applied to analyze the data. RESULTS: According to the results of correlation analysis, there was no significant correlation between the level of sensory block and SFH. There were statistically significant positive correlations between the amount of ephedrine administered due to hypotension and SFH. CONCLUSIONS: In term parturients choosing elective cesarean section, the SFH is not correlated with the sensory level of spinal anesthesia, but is correlated with the amount of ephedrine administered during spinal anesthesia.

Pulmonary thromboembolism after tourniquet inflation under spinal anesthesia -A case report-.

Pulmonary thromboembolism is one of the most important causes of morbidity and mortality in patients undergoing lower extremity orthopedic surgery. Early diagnosis and appropriate management are important clinical challenges. In this case, massive pulmonary embolism causing sudden cardiac arrest was attributed to use of tourniquet inflation during lower extremity orthopedic surgery. Resuscitation procedures were initiated and transesophageal echocardiography revealed pulmonary thromboembolism. Patients with high suspicion for the presence of deep vein thrombus must be monitored thoroughly during limb exsanguinations.