No abstract available.

Independent Component Analysis (ICA) is a signal processing algorithm to separate independent sources from unknown mixed signals and can be applied to separate artifacts and independent neural sources from EEG recordings. This study was designed to extract individual components of eyeball movements from scalp EEG. Digital EEG signals were recorded using the international 10-20 system during eye closure, eye opening, and blinking. 18 EEG tracings using bipolar montage were analyzed by ICA algorithm into 18 independent components. Each of the components was reviewed, selected, and reconstructed into an original montage. Among 18 components, two components which were thought to represent eyeball movements were obtained. Each of the components was inversely projected into the original bipolar montage. This inverse projection showed separated vertical and horizontal eyeball movements components. These results suggest that the ICA analysis of EEG can separate vertical and horizontal eyeball movements and may be applied to separate other EEG artifacts and source signals from unknown mixed sources recordings of EEG.
Artifacts ; Blinking ; Electroencephalography ; Scalp

No abstract available.
Debridement* ; Knee* ; Osteoarthritis* ; Osteotomy*

Large language models (LLMs) have revolutionized the global landscape of technology beyond the field of natural language processing. Owing to their extensive pre-training using vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without the need for additional fine-tuning. Importantly, LLMs are on a trajectory of rapid evolution, addressing challenges such as hallucination, bias in training data, high training costs, performance drift, and privacy issues, along with the inclusion of multimodal inputs. The concept of small, on-premise open source LLMs has garnered growing interest, as fine-tuning to medical domain knowledge, addressing efficiency and privacy issues, and managing performance drift can be effectively and simultaneously achieved. This review provides conceptual knowledge, actionable guidance, and an overview of the current technological landscape and future directions in LLMs for radiologists.

Large language models (LLMs) have revolutionized the global landscape of technology beyond the field of natural language processing. Owing to their extensive pre-training using vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without the need for additional fine-tuning. Importantly, LLMs are on a trajectory of rapid evolution, addressing challenges such as hallucination, bias in training data, high training costs, performance drift, and privacy issues, along with the inclusion of multimodal inputs. The concept of small, on-premise open source LLMs has garnered growing interest, as fine-tuning to medical domain knowledge, addressing efficiency and privacy issues, and managing performance drift can be effectively and simultaneously achieved. This review provides conceptual knowledge, actionable guidance, and an overview of the current technological landscape and future directions in LLMs for radiologists.

Large language models (LLMs) have revolutionized the global landscape of technology beyond the field of natural language processing. Owing to their extensive pre-training using vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without the need for additional fine-tuning. Importantly, LLMs are on a trajectory of rapid evolution, addressing challenges such as hallucination, bias in training data, high training costs, performance drift, and privacy issues, along with the inclusion of multimodal inputs. The concept of small, on-premise open source LLMs has garnered growing interest, as fine-tuning to medical domain knowledge, addressing efficiency and privacy issues, and managing performance drift can be effectively and simultaneously achieved. This review provides conceptual knowledge, actionable guidance, and an overview of the current technological landscape and future directions in LLMs for radiologists.

A 54-year-old man had complained of proptosis on his right eye. Computed tomography showedlarge mass on superotemporal portion of right orbit. Surgical removal was done through the lateral orbitotomy. The histopathological diagnosis demonstrated pleomophic adenoma. Seven Years later, the patient revisited complaing of proptosis on his right eye. Magnetic resonance image demonstrated ill defined mass on the same iste. We excised mass including psuedocapsule and surrounding tissue.
Adenoma ; Adenoma, Pleomorphic* ; Diagnosis ; Exophthalmos ; Humans ; Middle Aged ; Orbit

Hallervorden-Spatz disease (HSD) is a rare, progressive, autosomal recessive hereditary disorder characterized by pyramidal and extrapyramidal signs, speech disturbances, mental deterioration and retinal degeneration during childhood or adolescence. In late-onset form after the age of 20, parkinsonian features may be the predominant clinical manifestation. Meanwhile, involuntary tongue movements are rare and poorly understood, which have been reported in tardive dyskinesia, neuroacanthocytosis, chronic epilepsy, and after head trauma. We report a case of a patient with 'fly catcher's tongue' as a major clinical presentation, accompanied with mild parkinsonism, and typical MR findings of HSD.
Adolescent ; Craniocerebral Trauma ; Diptera* ; Epilepsy ; Humans ; Movement Disorders ; Neuroacanthocytosis ; Pantothenate Kinase-Associated Neurodegeneration* ; Parkinsonian Disorders ; Retinal Degeneration ; Tongue*

Large language models (LLMs) have revolutionized the global landscape of technology beyond natural language processing. Owing to their extensive pre-training on vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without additional fine-tuning. General-purpose chatbots based on LLMs can optimize the efficiency of radiologists in terms of their professional work and research endeavors. Importantly, these LLMs are on a trajectory of rapid evolution, wherein challenges such as “hallucination,” high training cost, and efficiency issues are addressed, along with the inclusion of multimodal inputs. In this review, we aim to offer conceptual knowledge and actionable guidance to radiologists interested in utilizing LLMs through a succinct overview of the topic and a summary of radiology-specific aspects, from the beginning to potential future directions.

Podophyllin is known as a neurotoxin, We recently observed a 34-year-old woman with podophyllin induced peripheral neuropathy. She was treated with topical podophyllin for perianal multiple condyloma acuminata. One day after application, she complained of G-I symptoms ( abdominal pain, nausea, vomiting, diarrhea), followed by tingling sensation on all extremities. We confirmed peripheral neuropathy with electrophysiologic study and sural nerve biopsy. She has improved on follow-up.
Abdominal Pain ; Adult ; Biopsy ; Extremities ; Female ; Follow-Up Studies ; Humans ; Nausea ; Peripheral Nervous System Diseases* ; Podophyllin* ; Sensation ; Sural Nerve ; Vomiting