Objectives: Auditory sensation can be elicited by applying a bone conduction vibrator to skin sites on the head, neck, and thorax over soft tissues. This is called soft tissue conduction (STC). We hypothesized that introducing substances with acoustic impedances that sharply deviate from those of soft tissues, such as air pockets, into the soft tissues beneath soft tissue stimulation sites would have an effect on the auditory threshold to stimulation at skin sites over soft tissue.
Methods: In human subjects, we assessed the auditory threshold with a bone vibrator applied to several STC sites, especially the cheek, and to several bone conduction sites on the skull. The subjects were equipped with bilateral earplugs. The subject then filled his or her cheek with either air or water, and the auditory threshold was again determined. We also recorded the auditory brain stem response to STC stimulation under the chin in fat sand rats in the absence and presence of subcutaneous air or saline solution pockets (0.4 mL) under the chin.
Results: In humans, the threshold to stimulation on the cheek was elevated (13 to 18 dB) in the presence of an air-inflated cheek, but not with a water-filled cheek. In animals, in the presence of an air pocket, the auditory brain stem response threshold was elevated by 10 to 20 dB; no threshold change occurred with a saline solution pocket.
Conclusions: The introduction of air (but not water) into the soft tissues beneath the soft tissue stimulation sites led to a threshold elevation in both humans and animals. This was not the case when an identical volume of water was introduced, which would also have interrupted a possible parallel bone conduction pathway. These results provide evidence that soft tissue stimulation at low intensities induces tissue vibrations that are transmitted to the cochlea along a series of soft tissues with similar acoustic impedances.
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http://dx.doi.org/10.1177/000348941312200808 | DOI Listing |
Chin Med J (Engl)
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BMC Genomics
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Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.
View Article and Find Full Text PDFZhonghua Bing Li Xue Za Zhi
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