Predicting the Prognosis of HIFU Ablation of Uterine Fibroids Using a Deep Learning-Based 3D Super-Resolution DWI Radiomics Model: A Multicenter Study.

RATIONALE AND OBJECTIVES: To assess the feasibility and efficacy of a deep learning-based three-dimensional (3D) super-resolution diffusion-weighted imaging (DWI) radiomics model in predicting the prognosis of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids. METHODS: This retrospective study included 360 patients with uterine fibroids who received HIFU treatment, including Center A (training set: N = 240; internal testing set: N = 60) and Center B (external testing set: N = 60) and were classified as having a favorable or unfavorable prognosis based on the postoperative non-perfusion volume ratio. A deep transfer learning approach was used to construct super-resolution DWI (SR-DWI) based on conventional high-resolution DWI (HR-DWI), and 1198 radiomics features were extracted from manually segmented regions of interest in both image types. Following data preprocessing and feature selection, radiomics models were constructed for HR-DWI and SR-DWI using Support Vector Machine (SVM), Random Forest (RF), and Light Gradient Boosting Machine (LightGBM) algorithms, with performance evaluated using area under the curve (AUC) and decision curves. RESULT: All DWI radiomics models demonstrated superior AUC in predicting HIFU ablated uterine fibroids prognosis compared to expert radiologists (AUC: 0.706, 95% CI: 0.647-0.748). When utilizing different machine learning algorithms, the HR-DWI model achieved AUC values of 0.805 (95% CI: 0.679-0.931) with SVM, 0.797 (95% CI: 0.672-0.921) with RF, and 0.770 (95% CI: 0.631-0.908) with LightGBM. Meanwhile, the SR-DWI model outperformed the HR-DWI model (P < 0.05) across all algorithms, with AUC values of 0.868 (95% CI: 0.775-0.960) with SVM, 0.824 (95% CI: 0.715-0.934) with RF, and 0.821 (95% CI: 0.709-0.933) with LightGBM. And decision curve analysis further confirmed the good clinical value of the models. CONCLUSION: Deep learning-based 3D SR-DWI radiomics model demonstrated favorable feasibility and effectiveness in predicting the prognosis of HIFU ablated uterine fibroids, which was superior to HR-DWI model and assessment by expert radiologists.

3D MR neurography with gadolinium contrast to improve the visualization of pelvic nerves and the branches.

Objective: To evaluate the effectiveness of 3D NerveVIEW sequence with gadolinium contrast on the visualization of pelvic nerves and their branches compared to that without contrast. Methods: Participants were scanned twice using 3D NerveVIEW sequence with and without gadolinium contrast to acquire pelvic nerve images. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and contrast ratio of the nerves were calculated and compared to determine the quality of images. To subjectively assess, using a 3-point scale, branch nerves critical to therapeutic decision-making, including the pelvic splanchnic nerve and pelvic plexus, the superior gluteal nerve, and the pudendal nerve. Results: In the 32 eligible participants after using contrast, the CNRs of the images of nerve-to-bone and nerve-to-vessel significantly increased (p < 0.05). The CR of the images with contrast of all nerve-to-surrounding tissues (i.e., bone, muscle, blood vessels, and fat) were also found significantly higher (p < 0.05). The assessment of observers also shows higher scores for images with contrast compared to images without contrast. Conclusion: The 3D NerveVIEW sequence combined with gadolinium contrast improved vascular suppression, increased the contrast between pelvic nerves and surrounding tissue, and enhanced the visualization of nerves and their branches. This study may be helpful for the technically challenging preoperative planning of pelvic diseases surgery.

Exosomes from adipose-derived stem cells activate sebocytes through the PI3K/AKT/SREBP-1 pathway to accelerate wound healing.

Sebocyte regeneration after injury is considered a key element of functional skin repair. Exosomes from adipose-derived stem cells (ADSCs-EXO) accelerate wound healing by promoting the proliferation of fibroblasts. However, the effects of ADSCs-EXO on sebocytes are largely unknown. In this study, the effects of ADSCs-EXO on sebocyte proliferation and migration were evaluated. The levels of phosphorylated AKT (p-AKT), AKT, sterol regulatory-element binding protein (SREBP), and perilipin-1 (PLIN-1) were detected with immunofluorescence, quantitative PCR, and western blot analysis. RNA-Seq was used to analyze the differential gene expression between the ADSCs-EXO group and the control group under anaerobic conditions. Lipogenesis was assessed with Nile red staining. In animal studies, full-thickness skin wounds in BALB/c mice were treated with gelatin methacrylate (GelMA) hydrogel-loaded sebocytes alone or in combination with ADSCs-EXO. Histopathological assessments of the wound tissues were performed Masson Trichrome staining, Immunohistochemical staining and so on. The phosphatidylinositol 3-kinase (PI3K)/AKT pathway blocker LY294002 inhibited the effects of ADSCs-EXO on p-AKT and sebocytes proliferation. ADSCs-EXO also regulated the expression of SREBP-1 and PLIN-1 through the PI3K/AKT pathway in an oxygen level-dependent manner. In BALB/c mice, ADSCs-EXO accelerated sebocyte-assisted wound healing and regeneration. These in vitro and in vivo results supported that ADSCs-EXO can promote the regeneration of fully functional skin after injury through the PI3K/AKT-dependent activation of sebocytes.

Factors influencing magnetic resonance imaging changes associated with pelvic bone injury after high-intensity focused ultrasound ablation of uterine fibroids: a retrospective case-control study.

Background: The application of high-intensity focused ultrasound (HIFU) in the treatment of uterine fibroids is becoming increasingly widespread, and postoperative collateral thermal damage to adjacent tissue has become a prominent subject of discussion. However, there is limited research related to bone injury. Therefore, the aim of this study was to investigate the potential factors influencing unintentional pelvic bone injury after HIFU ablation of uterine fibroids with magnetic resonance imaging (MRI). Methods: A total of 635 patients with fibroids treated with HIFU in the First Affiliated Hospital of Chongqing Medical University were enrolled. All patients underwent contrast-enhanced MRI (CE-MRI) pre- and post-HIFU. Based on the post-treatment MRI, the patients were divided into two groups: pelvic bone injury group and non-injury group, while the specific site of pelvic bone injury of each patient was recorded. The univariate and multivariate analyses were used to assess the correlations between the factors of fibroid features and treatment parameters and pelvic bone injury, and to further analyze the factors influencing the site of injury. Results: Signal changes in the pelvis were observed on CE-MRI in 51% (324/635) of patients after HIFU. Among them, 269 (42.4%) patients developed sacral injuries and 135 (21.3%) had pubic bone injuries. Multivariate analyses showed that patients with higher age [P=0.003; odds ratio (OR), 1.692; 95% confidence interval (CI): 1.191-2.404], large anterior side-to-skin distance of fibroid (P<0.001; OR, 2.297; 95% CI: 1.567-3.365), posterior wall fibroid (P=0.006; OR, 1.897; 95% CI: 1.204-2.989), hyperintensity on T2-weighted imaging (T2WI, P=0.003; OR, 2.125; 95% CI: 1.283-3.518), and large therapeutic dose (TD, P<0.001; OR, 3.007; 95% CI: 2.093-4.319) were at higher risk of postoperative pelvic bone injury. Further analysis of the factors influencing the site of the pelvic bone injury showed that some of the fibroid features and treatment parameters were associated with it. Moreover, some postoperative pain-related adverse events were associated with the pelvic bone injury. Conclusions: Post-HIFU treatment, patients may experience pelvic injuries to the sacrum, pubis, or a combination of both, and some of them experienced adverse events. Some fibroid features and treatment parameters are associated with the injury. Taking its influencing factors into full consideration preoperatively, slowing down treatment, and prolonging intraoperative cooling phase can help optimize treatment decisions for HIFU.

Prediction of recurrence risk factors in patients with early-stage cervical cancers by nomogram based on MRI handcrafted radiomics features and deep learning features: a dual-center study.

PURPOSE: To establish and validate a deep learning radiomics nomogram (DLRN) based on intratumoral and peritumoral regions of MR images and clinical characteristics to predict recurrence risk factors in early-stage cervical cancer and to clarify whether DLRN could be applied for risk stratification. METHODS: Two hundred and twenty five pathologically confirmed early-stage cervical cancers were enrolled and made up the training cohort and internal validation cohort, and 40 patients from another center were enrolled into the external validation cohort. On the basis of region of interest (ROI) of intratumoral and different peritumoral regions, two sets of features representing deep learning and handcrafted radiomics features were created using combined images of T2-weighted MRI (T2WI) and diffusion-weighted imaging (DWI). The signature subset with the best discriminant features was chosen, and deep learning and handcrafted signatures were created using logistic regression. Integrated with independent clinical factors, a DLRN was built. The discrimination and calibration of DLNR were applied to assess its therapeutic utility. RESULTS: The DLRN demonstrated satisfactory performance for predicting recurrence risk factors, with AUCs of 0.944 (95% confidence interval 0.896-0.992) and 0.885 (95% confidence interval 0.834-0.937) in the internal and external validation cohorts. Furthermore, decision curve analysis revealed that the DLRN outperformed the clinical model, deep learning signature, and radiomics signature in terms of net benefit. CONCLUSION: A DLRN based on intratumoral and peritumoral regions had the potential to predict and stratify recurrence risk factors for early-stage cervical cancers and enhance the value of individualized precision treatment.

Effect of body mass index (BMI) on image contrast in the hepatobiliary phase of Gd-EOB-DTPA-enhanced-MRI and the feasibility of the application of half-dose Gd-EOB-DTPA to hepatobiliary phase imaging in patients with a BMI less than 24: a comparative study.

Background: Gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) can detect more lesions through the image contrast of hepatobiliary phase. Body mass index (BMI) reflects the composition ratio of human tissue, which is an influencing factor of magnetic resonance image contrast. Meanwhile, Gd-EOB-DTPA is recommended to use the minimum dose when the diagnosis demands could be met. The aim of this paper was to investigate the effect of BMI on hepatobiliary phase image contrast and explore the feasibility of using low-dose Gd-EOB-DTPA to obtain good hepatobiliary phase image contrast in patients with normal and lean BMI. Methods: Eighty-two patients who had previously undergone Gd-EOB-DTPA-enhanced MRI (0.025 mmol/kg) were collected and divided into group A (BMI <24 kg/m2) and group B (BMI ≥24 kg/m2) according to Chinese BMI standards. Liver-to-portal vein contrast ratio (LPC20) and liver-to-spleen contrast ratio (LSC20) in hepatobiliary phase (20 min after injection) were calculated. Thirty patients with a BMI <24 kg/m2 who were about to receive Gd-EOB-DTPA-enhanced MRI were randomly divided into group C (0.0125 mmol/kg) and group D (0.025 mmol/kg). Image acquisition was performed at 10, 15, and 20 min after injection. LPC10, LPC15, LPC20 and LSC10, LSC15, LSC20 in corresponding phases were calculated. Results: In retrospective grouping study, compared with group B, group A's LPC20 was significantly higher [2.63 (2.42-3.00) vs. 2.22 (1.97-2.67); P<0.01]. In prospective grouping study, there were no differences in LPC15, LSC15, LPC20 and LSC20 between group C and group D. Intragroup comparison in each group showed that LPC15 (group C: 2.67±0.33; group D: 2.61±0.21) and LPC20 (group C: 2.74±0.37; group D: 2.72±0.27) were higher than LPC10 (group C: 2.19±0.18; group D: 1.94±0.17) (all P<0.01), while there were no changes between LPC15 and LPC20. Conclusions: Under conventional dose, hepatobiliary phase image contrast in patients with a BMI <24 was higher, which was mainly manifested in the high LPC. For patients with a BMI <24 kg/m2, using a half conventional dose (0.0125 mmol/kg), good hepatobiliary phase image contrast can still be obtained at 15-20 min after administration.

An interpretable MRI-based radiomics model predicting the prognosis of high-intensity focused ultrasound ablation of uterine fibroids.

BACKGROUND: Accurate preoperative assessment of the efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine fibroids is essential for good treatment results. The aim of this study was to develop robust radiomics models for predicting the prognosis of HIFU-treated uterine fibroids and to explain the internal predictive process of the model using Shapley additive explanations (SHAP). METHODS: This retrospective study included 300 patients with uterine fibroids who received HIFU and were classified as having a favorable or unfavorable prognosis based on the postoperative nonperfusion volume ratio. Patients were divided into a training set (N = 240) and a test set (N = 60). The 1295 radiomics features were extracted from T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) scans. After data preprocessing and feature filtering, radiomics models were constructed by extreme gradient boosting and light gradient boosting machine (LightGBM), and the optimal performance was obtained by Bayesian optimization. Finally, the SHAP approach was used to explain the internal prediction process. RESULTS: The models constructed using LightGBM had the best performance, and the AUCs of the T2WI and CE-T1WI models were 87.2 (95% CI = 87.1-87.5) and 84.8 (95% CI = 84.6-85.7), respectively. The use of SHAP technology can help physicians understand the impact of radiomic features on the predicted outcomes of the model from a global and individual perspective. CONCLUSION: Multiparametric radiomic models have shown their robustness in predicting HIFU prognosis. Radiomic features can be a potential source of biomarkers to support preoperative assessment of HIFU treatment and improve the understanding of uterine fibroid heterogeneity. CLINICAL RELEVANCE STATEMENT: An interpretable radiomics model can help clinicians to effectively predict the prognosis of HIFU treatment for uterine fibroids. The heterogeneity of fibroids can be characterized by various radiomics features and the application of SHAP can be used to visually explain the prediction process of radiomics models.

A portable Raspberry Pi-based spectrometer for on-site spectral testing.

We designed a portable Raspberry Pi-based spectrometer, which mainly consists of a white LED acting as the wide-spectrum source, a reflection grating for light dispersion, and a CMOS imaging chip aiming at spectral recording. All the optical elements and Raspberry Pi were integrated using 3-D printing structures with a size of 118 mm × 92 mm × 84 mm, and home-built software was also designed for spectral recording, calibration, analysis, and display implemented with a touch LCD. Additionally, the portable Raspberry Pi-based spectrometer was equipped with an internal battery, thus supporting on-site applications. Tested by a series of verifications and applications, the portable Raspberry Pi-based spectrometer could reach a spectral resolution of 0.065 nm per pixel within the visible band and provide spectral detection with high accuracy. Therefore, it can be used for on-site spectral testing in various fields.

Deep-Gamma: deep low-excitation fluorescence imaging global enhancement.

Lowering the excitation to reduce phototoxicity and photobleaching while numerically enhancing the fluorescence signal is a useful way to support long-term observation in fluorescence microscopy. However, invalid features, such as near-zero gradient dark backgrounds in fluorescence images, negatively affect the neural networks due to the network training locality. This problem makes it difficult for mature deep learning-based image enhancement methods to be directly extended to fluorescence imaging enhancement. To reduce the negative optimization effect, we previously designed Kindred-Nets in conjunction with a mixed fine-tuning scheme, but the mapping learned from the fine-tuning dataset may not fully apply to fluorescence images. In this work, we proposed a new, to the best of our knowledge, deep low-excitation fluorescence imaging global enhancement framework, named Deep-Gamma, that is completely different from our previously designed scheme. It contains GammaAtt, a self-attention module that calculates the attention weights from global features, thus avoiding negative optimization. Besides, in contrast to the classical self-attention module outputting multidimensional attention matrices, our proposed GammaAtt output, as multiple parameters, significantly reduces the optimization difficulty and thus supports easy convergence based on a small-scale fluorescence microscopy dataset. As proven by both simulations and experiments, Deep-Gamma can provide higher-quality fluorescence-enhanced images compared to other state-of-the-art methods. Deep-Gamma is envisioned as a future deep low-excitation fluorescence imaging enhancement modality with significant potential in medical imaging applications. This work is open source and available at https://github.com/ZhiboXiao/Deep-Gamma.

sPhaseStation: a whole slide quantitative phase imaging system based on dual-view transport of intensity phase microscopy.

Whole slide imaging scans a microscope slide into a high-resolution digital image, and it paves the way from pathology to digital diagnostics. However, most of them rely on bright-field and fluorescence imaging with sample labels. In this work, we designed sPhaseStation, which is a dual-view transport of intensity phase microscopy-based whole slide quantitative phase imaging system for label-free samples. sPhaseStation relies on a compact microscopic system with two imaging recorders that can capture both under and over-focus images. Combined with the field of view (FoV) scan, a series of these defocus images in different FoVs can be captured and stitched into two FoV-extended under and over-focus ones, which are used for phase retrieval via solving the transport of intensity equation. Using a 10× micro-objective, sPhaseStation reaches the spatial resolution of 2.19 µm and obtains the phase with high accuracy. Additionally, it acquires a whole slide image of a 3m m×3m m region in 2 min. The reported sPhaseStation could be a prototype of the whole slide quantitative phase imaging device, which may provide a new perspective for digital pathology.

Deep SBP+: breaking through the space-bandwidth product limit based on a physical-driven cycle constraint framework.

To obtain an image with both high spatial resolution and a large field of view (FoV), we designed a deep space-bandwidth product (SBP)-expanded framework (Deep SBP+). Combining a single-captured low-spatial-resolution image with a large FoV and a few captured high-spatial-resolution images in sub-FoVs, an image with both high spatial resolution and a large FoV can be reconstructed via Deep SBP+. The physical model-driven Deep SBP+ reconstructs the convolution kernel as well as up-samples the low-spatial resolution image in a large FoV without relying on any external datasets. Compared to conventional methods relying on spatial and spectral scanning with complicated operations and systems, the proposed Deep SBP+ can reconstruct high-spatial-resolution and large-FoV images with much simpler operations and systems as well as faster speed. Since the designed Deep SBP+ breaks through the trade-off of high spatial resolution and large FoV, it is a promising tool for photography and microscopy.

Comparison of ultrasound-based ADNEX model with magnetic resonance imaging for discriminating adnexal masses: a multi-center study.

Objectives: The ADNEX model offered a good diagnostic performance for discriminating adnexal tumors, but research comparing the abilities of the ADNEX model and MRI for characterizing adnexal tumors has not been reported to our knowledge. The aim of this study was to evaluate the diagnostic accuracy of the ultrasound-based ADNEX (Assessment of Different NEoplasias in the adneXa) model in comparison with that of magnetic resonance imaging (MRI) for differentiating benign, borderline and malignant adnexal masses. Methods: This prospective study included 529 women with adnexal masses who underwent assessment via the ADNEX model and subjective MRI analysis before surgical treatment between October 2019 and April 2022 at two hospitals. Postoperative histological diagnosis was considered the gold standard. Results: Among the 529 women, 92 (17.4%) masses were diagnosed histologically as malignant tumors, 67 (12.7%) as borderline tumors, and 370 (69.9%) as benign tumors. For the diagnosis of malignancy, including borderline tumors, overall agreement between the ADNEX model and MRI pre-operation was 84.9%. The sensitivity of the ADNEX model of 0.91 (95% confidence interval [CI]: 0.85-0.95) was similar to that of MRI (0.89, 95% CI: 0.84-0.94; P=0.717). However, the ADNEX model had a higher specificity (0.90, 95% CI: 0.87-0.93) than MRI (0.81, 95% CI: 0.77-0.85; P=0.001). The greatest sensitivity (0.96, 95% CI: 0.92-0.99) and specificity (0.94, 95% CI: 0.91-0.96) were achieved by combining the ADNEX model and subjective MRI assessment. While the total diagnostic accuracy did not differ significantly between the two methods (P=0.059), the ADNEX model showed greater diagnostic accuracy for borderline tumors (P<0.001). Conclusion: The ultrasound-based ADNEX model demonstrated excellent diagnostic performance for adnexal tumors, especially borderline tumors, compared with MRI. Accordingly, we recommend that the ADNEX model, alone or with subjective MRI assessment, should be used for pre-operative assessment of adnexal masses.

A Deep Learning Radiomics Nomogram to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Cervical Cancer: A Two-Center Study.

Purpose: This study aimed to establish a deep learning radiomics nomogram (DLRN) based on multiparametric MR images for predicting the response to neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC). Methods: Patients with LACC (FIGO stage IB-IIIB) who underwent preoperative NACT were enrolled from center 1 (220 cases) and center 2 (independent external validation dataset, 65 cases). Handcrafted and deep learning-based radiomics features were extracted from T2WI, DWI and contrast-enhanced (CE)-T1WI, and radiomics signatures were built based on the optimal features. Two types of radiomics signatures and clinical features were integrated into the DLRN for prediction. The AUC, calibration curve and decision curve analysis (DCA) were employed to illustrate the performance of these models and their clinical utility. In addition, disease-free survival (DFS) was assessed by Kaplan-Meier survival curves based on the DLRN. Results: The DLRN showed favorable predictive values in differentiating responders from nonresponders to NACT with AUCs of 0.963, 0.940 and 0.910 in the three datasets, with good calibration (all p > 0.05). Furthermore, the DLRN performed better than the clinical model and handcrafted radiomics signature in all datasets (all p < 0.05) and slightly higher than the DL-based radiomics signature in the internal validation dataset (p = 0.251). DCA indicated that the DLRN has potential in clinical applications. Furthermore, the DLRN was strongly correlated with the DFS of LACC patients (HR = 0.223; p = 0.004). Conclusion: The DLRN performed well in preoperatively predicting the therapeutic response in LACC and could provide valuable information for individualized treatment.

Sacral injury and influencing factors after ultrasonic ablation of uterine fibroids ≤30 mm from the sacrum

PURPOSE: To study sacral injuries and influencing factors after ultrasonic ablation of uterine fibroids no more than 30 mm from the sacrum. METHODS: A total of 406 patients with uterine fibroids who underwent percutaneous ultrasound ablation were analyzed retrospectively. All patients underwent contrast-enhanced magnetic resonance imaging (MRI) scans before and after high-intensity focused ultrasound. The abnormal signal intensity (low signal intensity on T1WI and high signal intensity on T2WI) on the postoperative MRIs was indicative of a sacral injury. The patients were divided into a sacrum injury group and a sacrum non-injury group. The relationship between fibroid characteristics, ultrasound ablation parameters, and injury was analyzed using univariate and multivariate analyses. RESULTS: There were 139 cases of sacral injury (34.24%). When the distance from the fibroid's dorsal side to the sacrum was 0-10 mm, the risk assessment showed that the danger of sacral injury increased by 1.85 times and 3.03 times compared with that at a distance of 11-20 or 21-30 mm. Furthermore, the risk of sacral injury increased by 1.89 times and 3.23 times when the therapeutic dose (TD) of a fibroid was >500 KJ compared with that of a fibroid with TD= 250-500 KJ and <250 KJ. CONCLUSION: A distance of 10 mm or less and a TD of >500 KJ were significantly correlated with sacral injury. The distance from the fibroid's dorsal side to the sacrum and the TD were the main causes of injury to the sacrum. A distance of 10 mm or less and a TD of >500 KJ carried higher injury risks, while a distance of 21-30 mm and a TD of <250 KJ were the most appropriate circumstances to reduce the risk of sacral injury.

DARU-Net: A dual attention residual U-Net for uterine fibroids segmentation on MRI.

PURPOSE: Uterine fibroid is the most common benign tumor in female reproductive organs. In order to guide the treatment, it is crucial to detect the location, shape, and size of the tumor. This study proposed a deep learning approach based on attention mechanisms to segment uterine fibroids automatically on preoperative Magnetic Resonance (MR) images. METHODS: The proposed method is based on U-Net architecture and integrates two attention mechanisms: channel attention of squeeze-and-excitation (SE) blocks with residual connections, spatial attention of pyramid pooling module (PPM). We did the ablation study to verify the performance of these two attention mechanisms module and compared DARU-Net with other deep learning methods. All experiments were performed on a clinical dataset consisting of 150 cases collected from our hospital. Among them, 120 cases were used as the training set, and 30 cases are used as the test set. After preprocessing and data augmentation, we trained the network and tested it on the test dataset. We evaluated segmentation performance through the Dice similarity coefficient (DSC), precision, recall, and Jaccard index (JI). RESULTS: The average DSC, precision, recall, and JI of DARU-Net reached 0.8066 ± 0.0956, 0.8233 ± 0.1255, 0.7913 ± 0.1304, and 0.6743 ± 0.1317. Compared with U-Net and other deep learning methods, DARU-Net was more accurate and stable. CONCLUSION: This work proposed an optimized U-Net with channel and spatial attention mechanisms to segment uterine fibroids on preoperative MR images. Results showed that DARU-Net was able to accurately segment uterine fibroids from MR images.

Ultrathin Supratrochlear Artery Cutaneous Branch Flaps for Large Defects Around Eyebrows.

BACKGROUND: The key point of repairing large defects around eyebrows is to keep the eyebrow undistorted. The limited skin elevates the application difficulty of conventional methods such as direct suture or local flap. Forehead pedicle flaps do well in tension control. However, most of them are too thick for defects because the frontalis muscle must be included. Recently, 1 stable supratrochlear artery cutaneous branch was found, which provides an opportunity to make an ultrathin forehead flap with a good blood supply. This study aims to investigate whether the supratrochlear artery cutaneous branch flap could perform good esthetic reconstruction for defects around the eyebrow. METHODS: The authors retrospectively included 15 patients whose defect around the eyebrows was repaired by the supratrochlear artery cutaneous branch flap from June 2017 to June 2020. The authors followed up about their flap color and texture, scar, abnormal sensation, any complication, recurrence, and patient satisfaction for at least 6 months online or face-to-face. RESULTS: All of the flaps survived, without distortion of the eyebrows or inner canthi. Similar flap color, texture, and thickness with the nearby skin were obtained, except 2 patients reported pigmentation. Donor and receptor scars were acceptable. There was no recurrence or other complications. All of the patients were satisfied with the surgery effect. CONCLUSIONS: The supratrochlear artery cutaneous branch flap is a valuable alternative method to repair large defects around the eyebrows. It can avoid facial distortion and achieve good esthetic outcomes in single-stage surgery.

Upper Eyelid Blepharoplasty Improved the Overall Periorbital Aesthetics Ratio by Enhancing Harmony Between the Eyes and Eyebrows.

Purpose: In upper eyelid blepharoplasty, most aesthetic surgeons and patients focus on improvements in the appearance of the upper eyelids, such as changing the vertical dimension of the palpebral fissure and the width of the pretarsal crease. Nevertheless, appropriately balanced periorbital aesthetics stemming from harmony between the eyelids and eyebrows is often ignored. The aim of this study was to explore the use of upper eyelid blepharoplasty to improve the overall periorbital aesthetics by enhancing the harmony between the eyes and eyebrows in young Asian women. Patients and Methods: From December 2019 to December 2020, 45 young Asian female patients underwent external incision upper eyelidplasty without ptosis repair or brow lift at The Second Affiliated Hospital of Harbin Medical University. The pre- and 6-month post-operative follow-up changes in the overall periorbital aesthetics were studied retrospectively. Results: The vertical position of the eyebrows in the upper face and shape of the brow apex were significantly improved after surgery. As a result, the height of the upper face was increased. Furthermore, the facial width proportion and midface ratio were closer to the ideal aesthetic golden ratio due to changes in the size of the periorbital area. All patients were satisfied with the result, and they achieved excellent surgical outcomes for not only the upper eyelids but also the overall periorbital region. Conclusion: This study revealed that upper eyelid blepharoplasty, which enhances the appearance of the upper eyelids while regulating the eyelid position and shape of the eyebrows by considering the eye to eyebrow ratio, optimizes the proportion of the periorbital area and improves the overall periorbital aesthetics.

Automatic whole blood cell analysis from blood smear using label-free multi-modal imaging with deep neural networks.

Whole blood cell analysis is widely used in medical applications since its results are indicators for diagnosing a series of diseases. In this work, we report automatic whole blood cell analysis from blood smear using label-free multi-modal imaging with deep neural networks. First, a commercial microscope equipped with our developed Phase Real-time Microscope Camera (PhaseRMiC) obtains both bright-field and quantitative phase images. Then, these images are automatically processed by our designed blood smear recognition networks (BSRNet) that recognize erythrocytes, leukocytes and platelets. Finally, blood cell parameters such as counts, shapes and volumes can be extracted according to both quantitative phase images and automatic recognition results. The proposed whole blood cell analysis technique provides high-quality blood cell images and supports accurate blood cell recognition and analysis. Moreover, this approach requires rather simple and cost-effective setups as well as easy and rapid sample preparations. Therefore, this proposed method has great potential application in blood testing aiming at disease diagnostics.

Progranulin Promotes the Formation and Development of Capsules Caused by Silicone in Sprague-Dawley Rats.

Background: Silicone implants are currently the most widely used artificial materials in plastic surgery. Capsule formation following implant application is unavoidable. When the capsule is excessively thick and strongly contracted, it can lead to obvious symptoms, clinically known as capsular contracture. Biological factors have always been the focus of research on the capsule formation. As a growth factor, progranulin (PGRN) plays an important regulatory role in wound healing, tissue fibrosis, tumor proliferation and invasion, and inflammation regulation. At present, the research on the capsule mainly involves the regulation of tissue healing and fibrosis under the influence of inflammation. Because PGRN has a regulatory role in these processes, we believe that the study of both can provide a new theoretical basis and intervention sites for monitoring and inhibiting the development of the capsule. Methods: In this experiment, the effects of different surgical operations on the content of PGRN in the surgical site and plasma of rats were detected. Sprague-Dawley (SD) rat dermal fibroblasts were co-cultured by recombinant PGRN. The effects of r-PGRN on fibroblasts were detected by 5-ethynyl-2'-deoxyuridine (EdU) assay, wound healing assay and Western blot assay. Finally, the effect of PGRN on capsule formation and contracture was studied by changing the content of PGRN in the prosthesis in rats after operation. Results: Surgical trauma and silicone implant increased plasma and local PGRN levels in SD rats. PGRN can activate the TGF-ß/SMAD signaling pathway in a dose-dependent manner, thereby promoting fibroblast proliferation, differentiation and migration and inhibiting apoptosis and enhancing cell function, thereby promoting capsule formation and contracture. Conclusion: PGRN promotes the formation and contracture of the silicone implant capsule in SD rats by activating the TGF-ß/SMAD signaling pathway. This discovery may provide new therapeutic targets and detection indicators.

Factors influencing magnetic resonance imaging finding of endopelvic fascial edema after ultrasound-guided high-intensity focused ultrasound ablation of uterine fibroids.

OBJECTIVE: Investigate the relationships between endopelvic fascial edema and its influencing factors after ultrasound-guided high-intensity focused ultrasound (USgHIFU) ablation of uterine fibroids. METHODS: This retrospective study included 688 women with uterine fibroids treated by USgHIFU; based on post-treatment MRI, the patients were divided into two groups: endopelvic fascial edema group and nonedema group. The specific location of fascial edema of each patient was also recorded. Fascial edema and fibroid features and treatment parameters were set as the dependent and independent variables, respectively, and the correlations were studied using univariate and multivariate analyses. The relationship between the pain-related adverse events and location of fascial edema was analyzed by χ2 and fisher's exact tests. RESULTS: Edema and nonedema groups had 556 and 112 patients, respectively. Among the edema patients, posterior fascial edema incidence was the highest. Multifactorial analysis showed that the energy efficiency factor (EEF), fibroid location, and enhancement type were positively associated with endopelvic fascial edema (p < 0.05), while the distance from dorsal surface of the fibroid to sacrum was negatively correlated (p < 0.001). Patients with anterior, posterior and perirectal, and right lateral fascial edemas were associated with lower abdominal pain, sacrococcygeal pain, and leg numbness/pain, respectively. CONCLUSION: Post-USgHIFU ablation, patients were prone to developing endopelvic fascial edema, and some of them experienced pain-related adverse events. The fibroid location, its types of contrast enhancement, the distance from the dorsal surface of the fibroid to the sacrum, and EEF were the influencing factors resulting in the endopelvic fascial edema after USgHIFU ablation.