Selection Of Treatment Plan Research Articles

Von Mises stress peak (VMSP) and laryngomalacia severity score (LSS) are extremely useful in the selection of treatment for laryngomalacia.

To analyze the judgment efficiency of a computer stress model and severity score in severity evaluation and treatment plan selection of laryngomalacia patients. Twenty-two children (12 cases in the operation group and 10 cases in the follow-up group) with moderate to severe laryngomalacia were assessed by laryngomalacia severity score (LSS) which included visual analogue scale (VAS) and clinical score. A computer stress model of the laryngeal cavity was constructed for all children, with the von Mises stress peak (VMSP) of the model used as another quantitative evaluation method. The ROC curves of two quantitative evaluation methods, the LSS and the VMSP, were analyzed respectively, according to the clinical guideline which is regarded as the gold standard for judging whether surgery is needed. The diagnostic efficiency indexes such as sensitivity, specificity, and accuracy were calculated. The area under ROC curves (AUC) of the two methods were compared by a DeLong model. Spearman correlation analysis and Kappa test were used to test the correlation and consistency of the two quantitative evaluation methods. The independent sample t test was used to compare the difference of LSS and VMSP between operation group and follow-up group. The sensitivity, specificity, and accuracy of LSS in judging whether laryngomalacia was operated or not were 83.33%, 80.00% and 81.82%, respectively, and the area under ROC curve (AUC) was 0.825 (p < 0.05). The sensitivity, specificity, and accuracy of the computer stress model for laryngomalacia were 58.33%, 90.00% and 72.73%, respectively, and the AUC was 0.796 (p < 0.05). The spearman correlation coefficient between LSS and VMSP was 0.833, p < 0.001, which is statistically significant. LSS (t = 3.251, p = 0.004) and VMSP (t = 2.435, p = 0.024) of the two groups were statistically different. VMSP and LSS have high diagnostic efficacy in the quantitative evaluation of the severity of laryngomalacia and the selection of treatment plan. The consistency of the two quantitative evaluation methods is good, which has practical value for the evaluation of the severity of laryngomalacia and has guiding significance for surgery.

Towards artificial intelligence-based automated treatment planning in clinical practice: A prospective study of the first clinical experiences in high-dose-rate prostate brachytherapy

This prospective study evaluates our first clinical experiences with the novel ``BRachytherapy via artificial Intelligent GOMEA-Heuristic based Treatment planning''(BRIGHT) applied to high-dose-rate prostate brachytherapy. Between March 2020 and October 2021, 14 prostate cancer patients were treated in our center with a 15Gy HDR-brachytherapy boost. BRIGHT was used for bi-objective treatment plan optimization and selection of the most desirable plans from a coverage-sparing trade-off curve. Selected BRIGHT plans were imported into the commercial treatment planning system Oncentra Brachy . In Oncentra Brachy a dose distribution comparison was performed for clinical plan choice, followed by manual fine-tuning of the preferred BRIGHT plan when deemed necessary. The reasons for plan selection, clinical plan choice, and fine-tuning, as well as process speed were monitored. For each patient, the dose-volume parameters of the (fine-tuned) clinical plan were evaluated. In all patients, BRIGHT provided solutions satisfying all protocol values for coverage and sparing. In four patients not all dose-volume criteria of the clinical plan were satisfied after manual fine-tuning. Detailed information on tumour coverage, dose-distribution, dwell time pattern, and insight provided by the patient-specific trade-off curve, were used for clinical plan choice. Median time spent on treatment planning was 42 min, consisting of 16 min plan optimization and selection, and 26 min undesirable process steps. BRIGHT is implemented in our clinic and provides automated prostate high-dose-rate brachytherapy planning with trade-off based plan selection. Based on our experience, additional optimization aims need to be implemented to further improve direct clinical applicability of treatment plans and process efficiency.

Application of Dynamic Enhanced Magnetic Resonance Imaging Texture Analysis Combined with ADCs in Predicting Pelvic Lymph Metastasis of Prostate Cancer.

The application value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) texture analysis combined with apparent diffusion coefficient (ADC) in predicting pelvic lymph node metastasis of prostate cancer was explored. The clinical and imaging data of 151 patients with prostate cancer admitted to The Affiliated Tumor Hospital of Guizhou Medical University from November 2019 to November 2021 were retrospectively analysed. According to the final pathological diagnosis results, they were divided into two groups: Metastasis group (n = 63, pelvic lymph node metastasis) and non-metastasis group (n = 88, no pelvic lymph node metastasis). The DCE-MRI texture parameters and ADCs of the two groups were compared using Omni-Kinetics software and MADC software packages. The receiver operating characteristic (ROC) curve was used in evaluating the predictive value of each method and their combination, and Spearman rank correlation analysis was used in evaluating their correlation. The volume transfer (Ktrans) and interstitium-to-plasmarate rate constant (Kep) in the metastatic group were significantly higher than those in the non-metastatic group (p < 0.001). However, no significant difference in extravascular extracellular space volume fraction (Ve) was found between the groups (p > 0.05). The ADC of the metastatic group was lower (p < 0.001). The Ktrans and Kep values were positively correlated with pelvic lymph node metastasis of prostate cancer (r = 0.580, 0.684; p < 0.001), and the ADC was negatively correlated with pelvic lymph node metastasis of prostate cancer (r = -0.478; p < 0.001). The ROC curve showed that the area under the curve (AUC) of DCE-MRI texture analysis parameters Ktrans and Kep combined with ADC was large, and the prediction efficiency increased. The AUC, sensitivity and specificity were 0.974, 95.20% and 93.20% (p < 0.001), respectively. DCE-MRI texture analysis combined with ADC value can accurately predict pelvic lymphatic metastasis of prostate cancer, which is helpful for the selection and formulation of clinical treatment plans and has certain guiding value for the implementation of pelvic lymph node clearing in patients.

Using an anomaly detection approach for the segmentation of colorectal cancer tumors in whole slide images

Colorectal cancer (CRC) is the second most commonly diagnosed cancer in the United States. Genetic testing is critical in assisting in the early detection of CRC and selection of individualized treatment plans, which have shown to improve the survival rate of CRC patients. The tissue slide review (TSR), a tumor tissue macro-dissection procedure, is a required pre-analytical step to perform genetic testing. Due to the subjective nature of the process, major discrepancies in CRC diagnostics by pathologists are reported, and metrics for quality are often only qualitative. Progressive context encoder anomaly detection (P-CEAD) is an anomaly detection approach to detect tumor tissue from whole slide images (WSIs), since tumor tissue is by its nature, an anomaly. P-CEAD-based CRC tumor segmentation achieves a 71% 26% sensitivity, 92% 7% specificity, and 63% 23% F1 score. The proposed approach provides an automated CRC tumor segmentation pipeline with a quantitatively reproducible quality compared with the conventional manual tumor segmentation procedure.

Epidemiological Investigation of Brucellosis Spondylitis and Optimal Selection of Clinical Drug Compatibility, Treatment Course and Treatment Plan

Background: Brucellosis is a zoonotic endemic disease, the main source of infection is infected cattle, sheep, pigs and their products. In recent years, the global incidence of brucellosis spondylitis has increased year by year, and it has spread from pastoral areas to semi-agricultural and semi-pastoral areas, agricultural areas and cities. It has changed from a mainly occupational disease to a mainly food-borne disease, and it is also a zoonotic specific spinal infectious disease that WHO and governments around the world pay great attention to. Due to the low cure rate and high recurrence rate of traditional drug therapy regimen. Therefore, to carry out epidemiological investigation and Related research on clinical drug therapy of brucellosis spondylitis has practical significance for improving diagnosis rate, cure rate and reducing recurrence rate. Objective: To analyze the epidemiological characteristics of Brucellosis spondylitis and explore the choice of drugs and the best drug treatment plan, so as to provide scientific basis for improving the prevention and control of the disease and treatment effect. Methods: Clinical epidemiodogical materials were collected from 113 patients with brucellar spondylitis. All these patients were divided into 5 different groups according to 5 kinds of drugs adopted respectively, and then the patients were given different course of treatment. Results: In the 113 patients, brucellar spondylitis morbility of female patients were higher than that of male ones, and the morbility of Bashang were higher than that of Baxia. These patients were infected mainly through browsing and breeding beasts. Lumbars were the major focus of infection. It was very comnlon that two adjacent lumbars were involved in concurrently. L4 was the most common infection location and its demolishment was most serious. The curative effect of group treated with doxycycline was better than that of group treated without doxycycline. If the course of treatment Was increased, the curative effect Was not increased obviously. Conclusions: There are characteristic features in clinical epidemiology of brucell spondylitis. Doxycycline + Rifampicin + Sulfamethoxazole was used as the preferred antibiotic. Using antibiotics adequately and jointly by two courses of treatment for a long time is the most reasonable way to treat the disease and prevent the disease from recurrence.

The value of contrast-enhanced ultrasonography in the diagnosis of primary testicular non-neoplastic and neoplastic lesions in adults

BackgroundDifferent pathological types of testicular tumors are treated differently. Malignant germ cell tumors require radical orchiectomy, while benign tumors may only need mass enucleation. Contrast-enhanced ultrasonography (CEUS) is more sensitive than conventional ultrasonography in displaying tumor microvessels, which helps distinguish between benign and malignant tumors.MethodsThis was a retrospective analysis of 35 patients with pathological-confirmed primary testicular non-neoplastic and neoplastic lesions in our hospital from February 2017 to February 2022. Conventional ultrasonography and CEUS imaging findings of included lesions were retrospectively analyzed and their diagnostic values were compared with the pathological results.ResultsThere were 13 cases of benign testicular lesions (including 1 case of spontaneous hematoma, 2 cases of segmental infarctions, 5 cases of epidermoid cysts, 2 cases of Sertoli cell tumors, and 3 cases of Leydig cell tumors) and 23 cases of malignant testicular lesions (including 10 cases of seminomas, 1 case of embryonal carcinoma, 2 cases of mixed germ cell tumors, 2 cases of spermatocytic tumors, and 8 cases of lymphomas). The sensitivity, specificity, positive predictive value, negative predictive value and accuracy rates of conventional ultrasound in diagnosing benign testicular tumors by "onion skin-like" echo (epidermoid cysts) and peripheral annular blood flow were 30.8%, 100.0%, 100.0%, 71.9% and 75.0%, respectively. All testicular non-neoplastic lesions and epidermoid cysts showed no enhancement by CEUS. All Sertoli-Leydig cell tumors (SLCTs)’ CEUS imaging showed uniform high enhancement (no necrosis area), fast forward, and slow backward. 80.0% (12/15) malignant germ cell tumors showed heterogeneous enhancement and fast forward and fast backward in CEUS. All lymphomas showed fast forward and fast backward, and 87.5% (7/8) of them showed uniform high levels of enhancement in CEUS. According to CEUS without enhancement (non-neoplastic lesions and epidermoid cysts) and uniform high enhancement with fast forward and slow backward (SLCT), the sensitivity, specificity, positive predictive value, negative predictive value and accuracy rates for diagnosing benign testicular tumors were all 100.0%. Compared with conventional ultrasound, the difference was statistically significant (p = 0.004).ConclusionsCEUS could accurately distinguish between benign and malignant testicular tumors, as well as differentiate specific pathological types (testicular focal infarction, epidermoid cysts, spermatocytic tumors, SLTC and lymphoma). Accurate preoperative diagnosis is critical for guiding the selection of appropriate treatment plans for different pathological types of testicular tumors.

Imaging of Cervical Lymph Nodes

The occurrence of cervical lymph node metastases is the single most important prognostic factor for head and neck malignancy. It directly influences the staging of tumors, selection of treatment plan, and patient prognosis. Various head and neck cancers have the propensity to spread to different nodal stations in the neck. CT/MRI is routinely used to evaluate the patient of head and neck malignancy. Knowledge of various cervical nodal levels, as well as the preferential drainage pattern of various sites of head and neck malignancies, can aid in accurate imaging interpretation.

The role of artificial intelligence in veterinary radiation oncology.

Veterinary radiation oncology regularly deploys sophisticated contouring, image registration, and treatment planning optimization software for patient care. Over the past decade, advances in computing power and the rapid development of neural networks, open-source software packages, and data science have been realized and resulted in new research and clinical applications of artificial intelligent (AI) systems in radiation oncology. These technologies differ from conventional software in their level of complexity and ability to learn from representative and local data. We provide clinical and research application examples of AI in human radiation oncology and their potential applications in veterinary medicine throughout the patient's care-path: from treatment simulation, deformable registration, auto-segmentation, automated treatment planning and plan selection, quality assurance, adaptive radiotherapy, and outcomes modeling. These technologies have the potential to offer significant time and cost savings in the veterinary setting; however, since the range of usefulness of these technologies have not been well studied nor understood, care must be taken if adopting AI technologies in clinical practice. Over the next several years, some practical and realizable applications of AI in veterinary radiation oncology include automated segmentation of normal tissues and tumor volumes, deformable registration, multi-criteria plan optimization, and adaptive radiotherapy. Keys in achieving success in adopting AI in veterinary radiation oncology include: establishing "truth-data"; data harmonization; multi-institutional data and collaborations; standardized dose reporting and taxonomy; adopting an open access philosophy, data collection and curation; open-source algorithm development; and transparent and platform-independent code development.

Recent Progress on the Applications of Nanomaterials and Nano-Characterization Techniques in Endodontics: A Review.

The impact of nano-based technologies in endodontics for the identification and treatment of various dental infections is showing fast progress. Studies show that nanoparticles could serve as useful agents with many beneficial results and continue to be promising in the field of endodontics. To ensure progress and improvements on novel nanomaterials in relation to their physicochemical and biological properties, nano-identification methods for the detection and evaluation of diseases need to be further highlighted. This study aims to review the current technological progress and recent research outcomes as well as possible prospective applications of nano-based technologies in endodontics. A comprehensive literature survey has been carried out on the utilizations of nanomaterials and nano-characterization techniques in endodontics. The current status and recent applications in endodontics are discussed with illustrative examples. The results have shown that the progress and improved accuracy of nano-identification techniques enabled a better characterization, evaluation and selection of appropriate treatment plans for endodontics-related diseases. The results have been inspiring for further clinical investigations. Nano-endodontics is still a developing field with a strong potential for revolutions of novel materials and techniques in the diagnosis and treatment of dental diseases. Further improvements in nanoparticles properties will pave the way for the development of many beneficial endodontic therapeutic agents. The future looks encouraging for sustainable products and testing methods for clinical endodontic applications.

Molecular Subtyping of Cancer Based on Distinguishing Co-Expression Modules and Machine Learning.

Molecular subtyping of cancer is recognized as a critical and challenging step towards individualized therapy. Most existing computational methods solve this problem via multi-classification of gene-expressions of cancer samples. Although these methods, especially deep learning, perform well in data classification, they usually require large amounts of data for model training and have limitations in interpretability. Besides, as cancer is a complex systemic disease, the phenotypic difference between cancer samples can hardly be fully understood by only analyzing single molecules, and differential expression-based molecular subtyping methods are reportedly not conserved. To address the above issues, we present here a new framework for molecular subtyping of cancer through identifying a robust specific co-expression module for each subtype of cancer, generating network features for each sample by perturbing correlation levels of specific edges, and then training a deep neural network for multi-class classification. When applied to breast cancer (BRCA) and stomach adenocarcinoma (STAD) molecular subtyping, it has superior classification performance over existing methods. In addition to improving classification performance, we consider the specific co-expressed modules selected for subtyping to be biologically meaningful, which potentially offers new insight for diagnostic biomarker design, mechanistic studies of cancer, and individualized treatment plan selection.

PD-0895 Evaluating a method of treatment plan selection from daily plans on the MR-Linac

PD-0895 Evaluating a method of treatment plan selection from daily plans on the MR-Linac

How to aggregate uncertain and incomplete cognitive evaluation information in lung cancer treatment plan selection? A method based on Dempster-Shafer theory

Multidisciplinary team is beneficial to select an appropriate treatment plan for a patient with lung cancer, where the collected cognitive evaluation information may be uncertain and incomplete. This study dedicates to dealing with a treatment plan selection problem of lung cancer through the multi-criteria analysis with generalised probabilistic linguistic term sets (GPLTSs) which are powerful in describing the uncertainty and incompleteness of subjective evaluations. The existing generalised probabilistic linguistic information aggregation method is based on the Dempster-Shafer combination rule, but the combined results may be counterintuitive. In addition, the GPLTS may not meet the conditions of applying the Dempster-Shafer combination rule. To make up for these gaps, a new combination rule based on Dempster-Shafer theory is introduced. Then, a multi-criteria decision-making (MCDM) process with generalised probabilistic linguistic information based on the proposed combination rule is formed and applied to select the treatment plans of lung cancer associated with a multidisciplinary team. Through the sensitivity analysis and comparative analysis, the advantages of the proposed method are highlighted.

Application of high-frequency ultrasound in detection and identification of nasal filling injection materials.

To access and determine the ultrasound images of different nasal filling injection materials. From November 2014 to November 2021, facial ultrasound images of Plastic Surgery Hospital of Chinese Academy of Medical Science were analyzed and judged. A total of 337 cases were enrolled, including 203 cases of hyaluronic acid, 102 cases of polyacrylamide hydrogel, 16 cases of calcium hydroxyapatite-based fillers, 10 cases of silicone oil, and 6 cases of growth factor. According to ultrasound images, hyaluronic acid is characterized by anechoic area with a clear boundary, which seems like a capsule, and the internal echo is uniform, there is no obvious blood flow signal in it. It is possible to see a stratified appearance if hyaluronic acid diffused into surrounding tissues, and it is mainly exhibited as hypoechoic area, with anechoic or hypoechoic areas in it. Polyacrylamide hydrogel showed irregular flocculent hypoechoic or fine punctured hypoechoic under ultrasound, which could aggregate into cystic hypoechoic area or disperse in tissue space, and echo floating or dislocation flow could be seen under probe pressure. Under ultrasound, calcium hydroxyapatite-based filler is characterized by heterogeneous hyperechoic or hypoechoic area, which spreads in the tissue space with unclear boundary with surrounding tissue, and no obvious liquid flow could be observed. Silicone oil is commonly found in the dermis, it is characterized by cloud-like high echo, the deep tissue is not clear. Growth factor is characterized by heterogeneous echo, which is similar to the echo of peripheral tissue, and the boundary is not clear. Plenty of blood flow signals suggest infection. If the image is characterized with posterior echogenic shadow, it suggests calcification. High-frequency ultrasound can identify the types of nasal filling injection materials and can guide the selection of clinical treatment plan according to the classification of imaging features.

The Value of Adding Ductography to Ultrasonography for the Evaluation of Pathologic Nipple Discharge in Women with Negative Mammography.

ObjectiveThe optimal imaging approach for evaluating pathological nipple discharge remains unclear. We investigated the value of adding ductography to ultrasound (US) for evaluating pathologic nipple discharge in patients with negative mammography findings.Materials and MethodsFrom July 2003 to December 2018, 101 women (mean age, 46.3 ± 12.2 years; range, 23–75 years) with pathologic nipple discharge were evaluated using pre-ductography (initial) US, ductography, and post-ductography US. The imaging findings were reviewed retrospectively. The standard reference was surgery (70 patients) or > 2 years of follow-up with US (31 patients). The diagnostic performances of initial US, ductography, and post-ductography US for detecting malignancy were compared using the McNemar’s test or a generalized estimating equation.ResultsIn total, 47 papillomas, 30 other benign lesions, seven high-risk lesions, and 17 malignant lesions were identified as underlying causes of pathologic nipple discharge. Only eight of the 17 malignancies were detected on the initial US, while the remaining nine malignancies were detected by ductography. Among the nine malignancies detected by ductography, eight were detected on post-ductography US and could be localized for US-guided intervention. The sensitivities of ductography (94.1% [16/17]) and post-ductography US (94.1% [16/17]) were significantly higher than those of initial US (47.1% [8/17]; p = 0.027 and 0.013, respectively). The negative predictive value of post-ductography US (96.9% [31/32]) was significantly higher than that of the initial US (83.3% [45/54]; p = 0.006). Specificity was significantly higher for initial US than for ductography and post-ductography US (p = 0.001 for all).ConclusionThe combined use of ductography and US has a high sensitivity for detecting malignancy in patients with pathologic nipple discharge and negative mammography. Ductography findings enable lesion localization on second-look post-ductography US, thus facilitating the selection of optimal treatment plans.

Aesthetic rehabilitation of a dental fluorosis case with porcelain laminate veneers

Fluorosis is a crippling disease and an ongoing challenge for India. It is a public health problem caused by excess intake of fluoride through drinking water, food products and industrial pollutants over a long period of time. Ingestion of excess fluoride, most commonly in drinking-water affects the teeth and bones. Repeated exposure to high concentrations of fluoride during tooth development, leading to enamel with reduced mineral content and increased porosity. Selection of appropriate treatment plan depends upon the severity of fluorosis. Porcelain laminate veneers are considered the treatment of choice for moderate to severe cases of fluorosis given the optimum aesthetics, wear resistance, biocompatibility, and long-term results of these veneers. This case report describes a step-by-step rehabilitation of dental fluorosis, using porcelain laminate veneers in a 28-year-old Indian female.

Framework for Dosimetry and Treatment Planning of TTFields

A post-hoc analysis study establishing the connection between TTFields dose at the tumor bed and overall survival in 340 newly diagnosed Glioblastoma patients from the pivotal EF-14 clinical trial (Stupp R, et al. JAMA. 2017;318:2306-2316) was published with our co-investigators in 2019 [Ballo M, et al. Int J Radiat Oncol Biol Phys. 2019;104(5):1106-1113]. More recently, utilizing patient data from that same trial, we were able to establish a connection between tumor progression patterns and TTFields dose distribution in TTFields treated patients. The results from these studies provide rationale for developing a framework for TTFields dosimetry and treatment planning. Utilizing this framework, physicians could maximize delivery of TTFields to target regions, and manipulate the dose as needed during the course of disease progression to address specific patterns of failure. Here we present a first effort to establish such a framework utilizing computational simulations, automated optimization algorithms and sophisticated visualization techniques.The framework we developed comprises the following steps. (a) Creation of a patient-specific computational algorithm: Semi-automatic and automatic algorithms are utilized to segment a patient MRI into different tissue types, and conductivity values are assigned to each tissue type. During this step the user is required to denote the target region in which dose should be optimized, as well as avoidance areas on the skin where it would be preferable not to place the transducer arrays. (b) Array placement optimization: During this phase virtual transducer arrays are placed on the computational model and an iterative optimization algorithm is utilized to find transducer arrays layouts that maximize TTFields dose in the target region. (c) Treatment plan selection: Several different array layouts identified by the optimization algorithm are presented to the user, so that an effective treatment plan for the patient can be empirically determined. Colormaps and isodose lines enable the user to compare field distributions generated by the different layouts. Tables and Dose Volume Histograms enable the user to quantitatively compare TTFields dose delivered to regions of interest.This treatment planning framework has been tested using over 20 image sets of glioblastoma patients. Our experience indicates this is a practical framework that can potentially increase TTFields dose delivered to targeted tumor regions significantly.We believe that this framework will assist the physicians with optimizing TTFields treatment by providing qualitative and quantitative tools for planning and also by normalizing the process of individualized treatment. Additionally, it will provide tools for adaptive treatment planning following any clinical need (e.g., tumor progression).

Three-dimensional mapping of distal humerus fracture

BackgroundDistal humerus fractures (DHFs) constitute one-third of elbow fractures approximately. In this study, we aim to define and analyze the fracture lines and morphological features of DHFs using mapping technique.MethodsOne hundred and two DHFs were retrospectively reviewed. All the computed tomography (CT) data were used to manually reconstruct and virtually reduce the DHF fragments to fit a standard 3D model. Smooth curves were depicted accurately onto the surface of the template to represent the fracture lines. All the curves were overlapped onto the model to create the 3D fracture map and heat map.ResultsOur analysis was based on 102 CT images of DHFs, contributed by 59 male and 43 female patients (mean age, 46 years; range, 18-93 years), and included 15 type A, 25 type B, and 62 type C fractures. On mapping, the hot zones were located in the radial fossa, coronoid fossa, olecranon fossa, and the external part of the trochlear. Conversely, the cold zones were noted in medial condyle, the medial side of the trochlear, and the anterolateral area on the supracondylar ridge.ConclusionsOur study firstly shows the fracture lines and morphological features of distal humeral fractures by three-dimensional mapping technology. Distal humerus fracture lines are characteristic and highly related to the micro-architecture difference of distal humerus, which may provide some guidance for the treatment plan selection and surgical fixation design.

Healthy-related quality of life in patients with cervical cancer in Southwest China: a cross-sectional study

BackgroundCervical cancer is the second most common female malignant tumor in the world. According to a study in 2018, the incidence of cervical cancer in Yunnan Province of China was 11.42 per 100,000, the mortality rate was 3.77 per 100,000, and higher than the national average. Health-related quality of life (HRQoL) can be used not only in the selection and effect evaluation of clinical treatment plans of cervical cancer, but also in the evaluation of prognosis and long-term survival status. In this study, 288 cervical cancer patients admitted to the Yunnan Cancer Hospital in Southwest China from 2018 to 2020 were used as the survey objects to understand the HRQoL of cervical cancer patients and explore the related factors that affect HRQoL.MethodsThe Chinese version of the functional assessment of cancer therapy-cervix (functional assessment of cancer therapy-cervix v4.0, FACT-Cx V4) was used to investigate 288 patients with cervical cancer in Yunnan Province. Statistical analysis was performed using t-test, analysis of variance, multiple linear regression and other methods.ResultsThe total FACT-Cx score of cervical cancer patients was (130.16 ± 14.20), the physical well-being (PWB) score was (22.02 ± 4.47), the social/family well-being (SWB) score was (25.66 ± 3.59), the emotional well-being (EWB) score was (19.75 ± 3.54), the functional well-being (FWB) score was (16.91 ± 5.01) and the additional focus area (cervical cancer subscale, CxS) score was (45.78 ± 4.61). From the multi-factor analysis results, the scores of PWB, FWB, Cxs and the total FACT-Cx were related to the choice of different treatment methods, the PWB scores of patients with concurrent chemoradiotherapy was low(β = − 1.67, P = 0.003), the FWB scores of patients with concurrent chemoradiotherapy was low(β = − 2.02, P = 0.001), the CxS scores of patients with concurrent chemoradiotherapy was low(β = − 1.61, P = 0.006), the total score of FACT-Cx of patients with concurrent chemoradiotherapy was low(β = − 5.91, P = 0.001). SWB score was affected by marital status, married patients had high PWB scores(β = 5.44, P = 0.006). The patients with heavy disease expenditures as aproportion of family disposable income(β = − 3.82, P = 0.002) and aged 60 and above(β = − 3.29, P = 0.003) had lower FWB scores. The total score FACT-Cx of patients participating in cervical cancer screening was higher(β = 7.61, P = 0.001).ConclusionThe choice of treatment method is the common influencing factor of PWB, FWB, Cxs and the total FACT-Cx. Disease expenditures as a proportion of family disposable income, the treatment method, the marital status and whether to participate in cervical cancer screening affect the patient’s evaluation of their own HRQoL. Medical staff should pay special attention to the choice of different treatment methods, popularize vaccination knowledge and cervical cancer screening, give more humanistic care and health education to cervical cancer patients who have low education level, poor economic conditions, divorced or separated, and encourage patients to participate in active treatment to improve the health-related quality of life.

Differential diagnosis and prevention of diabetic macular edema after cataract surgery in patients with nonproliferative diabetic retinopathy

Cataract surgery can increase the risk of diabetic macular edema (DME) and Irvine-Gass syndrome postoperatively in nonproliferative diabetic retinopathy (NPDR) patients. An accurate distinction between DME and Irvine-Gass syndrome in NPDR patients after cataract surgery is significantly important for the selection of subsequent treatment plans and guarantee of long-term vision quality. This article elaborates the differential diagnosis and prevention of DME, in order to provide a theoretical basis for the timely prevention, accurate diagnosis and standardized treatment of DME in NPDR patients after cataract surgery. (Chin J Ophthalmol, 2021, 57: 546-551).

Deep Learning-Based Magnetic Resonance Imaging Image Features for Diagnosis of Anterior Cruciate Ligament Injury.

To study and explore the adoption value of magnetic resonance imaging (MRI) in the diagnosis of anterior cruciate ligament (ACL) injuries, a multimodal feature fusion model based on deep learning was proposed for MRI diagnosis. After the related performance of the proposed algorithm was evaluated, it was utilized in the diagnosis of knee joint injuries. Thirty patients with knee joint injuries who came to our hospital for treatment were selected, and all patients were diagnosed with MRI based on deep learning multimodal feature fusion model (MRI group) and arthroscopy (arthroscopy group). The results showed that deep learning-based MRI sagittal plane detection had a great advantage and a high accuracy of 96.28% in the prediction task of ACL tearing. The sensitivity, specificity, and accuracy of MRI in the diagnosis of ACL injury was 96.78%, 90.62%, and 92.17%, respectively, and there was no considerable difference in contrast to the results obtained through arthroscopy (P > 0.05). The positive rate of acute ACL patients with bone contusion and medial collateral ligament injury was substantially superior to that of chronic injury. Moreover, the incidence of chronic injury ACL injury with meniscus tear and cartilage injury was notably higher than that of acute injury, with remarkable differences (P < 0.05). In summary, MRI images based on deep learning improved the sensitivity, specificity, and accuracy of ACL injury diagnosis and can accurately determined the type of ACL injury. In addition, it can provide reference information for clinical treatment plan selection and surgery and can be applied and promoted in clinical diagnosis.