OBJECTIVE: To explore the clinical effect of personalized puncture planning before surgery using Picture Archiving and Communication System (PACS) in the treatment of osteoporotic vertebral compression fractures in the elderly. METHODS: A total of 69 elderly patients with osteoporotic vertebral compression fractures treated by percutaneous vertebroplasty from January 2020 20 to December 2021 with more than 1 year of follow-up were analyzed retrospectively. Thirty-four patients were individualized for preoperative planning with PACS software (observation group), including 8 males and 26 females, with a mean age of (73.30±7.96) years old;and 35 patients were treated with conventional treatment (control group), including 7 males and 28 females, with a mean age of (77.30±7.84) years old. The operation time, the amount of cement injection, cement leakage rate, bone watertight diffusion and refracture within 1 year between two groups were observed and compared. The Cobb's angle, low back pain visual analogue scale(VAS) and the modified Oswsetry disability indexes(ODI) before surgery and 1 day, 1 year after surgery were compared between two groups. RESULTS: Both groups successfully completed the operation without serious surgical complications, 2 refractures occurred in the control group. The operation time in the observation group was(41.9±11.9) min, which was less than that in the control group (52.7±13.6) min (P<0.05). There was no significant difference in the cement injection volume between two groups (P>0.05). Two cases of cement leakage in the observation group was less than 8 in the control group (P<0.05). The bone cement distribution index of two groups had significant difference(P<0.05). There were no significant differences between two groups in Cobb's angle of the injured vertebras and ODI before and 1 day after surgery(P>0.05), however, the comparative differences were statistically significant at 1 year after surgery(P<0.05). There was no significant difference in the VAS between two groups at each time period(P>0.05). CONCLUSION Using the PACS software to plan personalized puncture scheme can reduce the operation time, reduce the cement leakage rate, improve the diffusion of bone cement and longer maintain the postoperative form of vertebral body and the functional state of patients' lumbar back.
Humans ; Male ; Female ; Aged ; Vertebroplasty/methods* ; Fractures, Compression/diagnostic imaging* ; Spinal Fractures/diagnostic imaging* ; Osteoporotic Fractures/diagnostic imaging* ; Aged, 80 and over ; Retrospective Studies ; Radiology Information Systems

OBJECTIVE: To implement radiological diagnostic guidelines and improve the standardization level of radiological reports. METHODS: A multimodal structured reporting system was designed. An integrated strategy of "standard coding + structural items + key images" was adopted to develop report templates for different diseases or anatomical sites, covering both text-only structured reports and comprehensive text-image structured reports. Horizontal comparisons with traditional (unstructured) reports were conducted to evaluate differences across four dimensions: efficiency, acceptability, completeness of disease sign description, and accuracy of data classification. RESULTS: The quality of comprehensive text-image structured reports was significantly superior to that of traditional reports ( P<0.01), while there was no statistically significant difference between text-only structured reports and traditional reports ( P>0.01). The information completeness and compliance with diagnostic guidelines of text-image reports were significantly higher than those of both traditional reports and text-only structured reports. The acceptability of text-image reports among senior radiologists (4.04±0.55) and clinicians (4.19±0.58) was higher than that among junior radiologists (3.04±1.55). In terms of data classification accuracy, the retrieval accuracy of structured reports based on natural language processing (NLP) (F1-Score: 0.85-1.00) was significantly better than the keyword retrieval method used for traditional reports. CONCLUSION Image-text-integrated structured reporting reduces heterogeneity in traditional reports and aids competency development among junior radiologists in primary care.
Radiology Information Systems ; Diagnostic Imaging ; Humans

OBJECTIVES: We propose a Contrastive Regional Attention and Prior Knowledge-Infused U-Transformer model (CRAKUT) to address the challenges of imbalanced text distribution, lack of contextual clinical knowledge, and cross-modal information transformation to enhance the quality of generated radiology reports. METHODS: The CRAKUT model comprises 3 key components, including an image encoder that utilizes common normal images from the dataset for extracting enhanced visual features, an external knowledge infuser that incorporates clinical prior knowledge, and a U-Transformer that facilitates cross-modal information conversion from vision to language. The contrastive regional attention in the image encoder was introduced to enhance the features of abnormal regions by emphasizing the difference between normal and abnormal semantic features. Additionally, the clinical prior knowledge infuser within the text encoder integrates clinical history and knowledge graphs generated by ChatGPT. Finally, the U-Transformer was utilized to connect the multi-modal encoder and the report decoder in a U-connection schema, and multiple types of information were used to fuse and obtain the final report. RESULTS: We evaluated the proposed CRAKUT model on two publicly available CXR datasets (IU-Xray and MIMIC-CXR). The experimental results showed that the CRAKUT model achieved a state-of-the-art performance on report generation with a BLEU-4 score of 0.159, a ROUGE-L score of 0.353, and a CIDEr score of 0.500 in MIMIC-CXR dataset; the model also had a METEOR score of 0.258 in IU-Xray dataset, outperforming all the comparison models. CONCLUSIONS The proposed method has great potential for application in clinical disease diagnoses and report generation.
Humans ; Radiology Information Systems ; Radiology

OBJECTIVE: To explore the integration method and technical realization of artificial intelligence bone age assessment system with the hospital RIS-PACS network and workflow. METHODS: Two sets of artificial intelligence based on bone age assessment systems (CHBoneAI 1.0/2.0) were developed. The intelligent system was further integrated with RIS-PACS based on the http protocol in Python flask web framework. RESULTS: The two sets of systems were successfully integrated into the local network and RIS-PACS in hospital. The deployment has been smoothly running for nearly 3 years. Within the current network setting, it takes less than 3 s to complete bone age assessment for a single patient. CONCLUSIONS The artificial intelligence based bone age assessment system has been deployed in clinical RIS-PACS platform and the "running in parallel", which is marking a success of Stage-I and paving the way to Stage-II where the intelligent systems can evolve to become more powerful in particular of the system self-evolution and the "running alternatively".
Age Determination by Skeleton ; Artificial Intelligence ; Bone and Bones ; Hospital Information Systems ; Hospitals ; Humans ; Radiology Information Systems ; Systems Integration

OBJECTIVE: To survey care providers' preference between structured reporting (SR) and free-text reporting (FTR) for appendiceal computed tomography (CT) in adolescents and young adults. MATERIALS AND METHODS: An ethical committee approved this prospective study. The requirement for participant consent was waived. We distributed the Likert scale-based SR form delivering the likelihood of appendicitis across 20 hospitals through a large clinical trial. In the final phase of the trial, we invited 706 potential care providers to participate in an online survey. The survey questions included usefulness in patient management, communicating the likelihood of appendicitis, convenience, style and format, and overall preference. Logistic regression analysis was performed for the overall preference. Three months after the completion of the trial, we checked if the use of the SR was sustained. RESULTS: Responses were analyzed from 594 participants (175 attendings and 419 trainees; 225 radiologists, 207 emergency physicians, and 162 surgeons). For each question, 47.3–64.8% of the participants preferred SR, 13.1–32.7% preferred FTR, and the remaining had no preference. The overall preference varied considerably across the hospitals, but slightly across the departments or job positions. The overall preference for SR over FTR was significantly associated with attendings, SR experience for appendiceal CT, hospitals with small appendectomy volume, and hospitals enrolling more patients in the trial. Five hospitals continued using the SR in usual care after the trial. CONCLUSION: Overall, the care providers preferred SR to FTR. Further investigation into the sustained use of the SR is needed.
Adolescent ; Appendectomy ; Appendicitis ; Emergencies ; Humans ; Logistic Models ; Prospective Studies ; Radiology Information Systems ; Surgeons ; Young Adult

OBJECTIVES: Conventional radiological processes have been replaced by digital images and information technology systems within South Africa and other developing countries. Picture Archiving and Communication Systems (PACS) technology offers many benefits to institutions, medical personnel and patients; however, the implementation of such systems can be a challenging task. It has been documented that South Africa has been using PACS for more than a decade in public hospitals with moderate success. The aim of this study was to identify and describe the PACS challenges endured by PACS vendors during implementation in the South African public healthcare sector. METHODS: This was achieved by engaging in a methodological approach that was qualitative in nature collecting data through semi structured interviews from 10 PACS experts/participants which were later analysed qualitatively. RESULTS: The findings show that PACS vendors have countless challenges, some of which include space, insufficient infrastructure, image storage capacity, system maturity and vendor related concerns. It was clear that the PACS experts readily offered contextually appropriate descriptions of their encounters during PACS implementations in South African public healthcare institutions. CONCLUSIONS: PACS vendors anticipate these challenges when facing a public healthcare institution and it is recommended that the hospital management and potential PACS stakeholders be made aware of these challenges to mitigate their effects and aid in a successful implementation.
Commerce ; Delivery of Health Care ; Developing Countries ; Health Care Sector ; Hospitals, Public ; Humans ; Information Storage and Retrieval ; Medical Informatics ; Medical Informatics Computing ; Radiography ; Radiology Information Systems ; South Africa

OBJECTIVE: To clarify the specificity of the ‘hot cross bun’ sign (HCBS) for multiple system atrophy (MSA) in adult cerebellar ataxia or parkinsonism. METHODS: The radiologic information systems at an academic center and affiliated veterans' hospital were queried using the keywords ‘hot cross bun,’ ‘pontocerebellar,’ ‘cruciate,’ ‘cruciform,’ ‘MSA,’ ‘multiple system atrophy,’ and ‘multisystem atrophy.’ Scans were reviewed by a neurologist and neuroradiologist to identify the HCBS. Subjects with the HCBS were reviewed by 2 neurologists to identify the most likely etiology of the patient's neurologic symptoms. RESULTS: Eleven cases were identified. Etiologies included MSA (4 probable, 2 possible), hereditary cerebellar ataxia (3/11), probable dementia with Lewy bodies (1/11), and uncertain despite autopsy (1/11). CONCLUSION: MSA was the most common etiology. However, 5 of the 11 patients did not have MSA. The most common alternate etiology was an undefined hereditary cerebellar ataxia (3/11).
Adult ; Autopsy ; Cerebellar Ataxia ; Dementia ; Hexachlorobenzene ; Humans ; Lewy Bodies ; Magnetic Resonance Imaging ; Multiple System Atrophy ; Neurologic Manifestations ; Olivopontocerebellar Atrophies ; Parkinsonian Disorders ; Radiology Information Systems ; Sensitivity and Specificity

No abstract available.
Radionuclide Imaging ; Imaging, Three-Dimensional ; Stereolithography ; Magnetic Resonance Imaging ; Software ; Technology, Radiologic ; Electronic Data Processing ; Radiology Information Systems

A noteworthy change in recent medical research is the rapid increase of research using big data obtained from electrical medical records (EMR), order communication systems (OCS), and picture archiving and communication systems (PACS). It is often difficult to apply traditional statistical techniques to research using big data because of the vastness of the data and complexity of the relationships. Therefore, the application of artificial intelligence (AI) techniques which can handle such problems is becoming popular. Classical machine learning techniques, such as k-means clustering, support vector machine, and decision tree are still efficient and useful for some research problems. The deep learning techniques, such as multi-layer perceptron, convolutional neural network, and recurrent neural network have been spotlighted by the success of deep belief networks and convolutional neural networks in solving various problems that are difficult to solve by conventional methods. The results of recent research using artificial intelligence techniques are comparable to human experts. This article introduces technologies that help researchers conduct medical research and understand previous literature in the era of AI.
Anesthesia* ; Artificial Intelligence* ; Decision Trees ; Humans ; Learning ; Machine Learning ; Medical Records ; Neural Networks (Computer) ; Radiology Information Systems ; Support Vector Machine

PURPOSE: This study was performed to evaluate the reliability of the identification of anatomical landmarks in panoramic and lateral cephalometric radiographs on a standard medical grade picture archiving communication system (PACS) monitor and a tablet computer (iPad 5). MATERIALS AND METHODS: A total of 1000 radiographs, including 500 panoramic and 500 lateral cephalometric radiographs, were retrieved from the de-identified dataset of the archive of the Section of Oral and Maxillofacial Radiology of the University Of Connecticut School Of Dental Medicine. Major radiographic anatomical landmarks were independently reviewed by two examiners on both displays. The examiners initially reviewed ten panoramic and ten lateral cephalometric radiographs using each imaging system, in order to verify interoperator agreement in landmark identification. The images were scored on a four-point scale reflecting the diagnostic image quality and exposure level of the images. RESULTS: Statistical analysis showed no significant difference between the two displays regarding the visibility and clarity of the landmarks in either the panoramic or cephalometric radiographs. CONCLUSION: Tablet computers can reliably show anatomical landmarks in panoramic and lateral cephalometric radiographs.
Archives ; Connecticut ; Dataset ; Humans ; Radiography, Dental, Digital ; Radiography, Panoramic ; Radiology Information Systems