An anatomical study of the transverse part of the infraspinatus muscle that is closely related with the supraspinatus muscle.

BACKGROUND: Detailed anatomical information of the infraspinatus is important in order to discuss muscle function. The aim of this study was to investigate the morphology, histology and innervation of the infraspinatus muscle, in order to construct an anatomical basis for diagnoses and operative procedures. MATERIALS AND METHODS: We used 51 shoulders without rotator cuff tears of 27 Japanese cadavers embalmed by 8% formalin. We observed the detailed morphology of the infraspinatus in 20 specimens macroscopically, and we also examined histologically in 7 specimens. In addition, we examined the innervation patterns of the supraspinatus and infraspinatus muscles in 24 specimens. RESULTS: The infraspinatus was composed of oblique and transverse parts in accordance with muscle fiber direction. Both parts had partially independent morphology, and the transverse part inserted into the main tendinous portion of the oblique part as a thin tendinous membrane. The transverse part was innervated by branches arising from the suprascapular nerve proximal to the spinoglenoid notch. The innervating branches ran on the superoposterior surface of the part, and entered the part from the posterior surface. CONCLUSION: Although the transverse part is a part of the infraspinatus, according to its innervation, the transverse part might be closely related to the supraspinatus. The independent transverse part of the infraspinatus has not been noticed. When we diagnose and treat the rotator cuff region, it will be important to consider this part as well as the main oblique part of the muscle. LEVEL OF EVIDENCE: Basic science study.

The superior capsule of the shoulder joint complements the insertion of the rotator cuff.

BACKGROUND: To date, there are no studies about the attachment of the articular capsule of the superior shoulder joint. The aim of this study was to measure the width of the attachment of the articular capsule on the humerus, and to clarify the anatomy and the relationship to the footprint of the rotator cuff. METHODS: The attachment of the articular capsule on the greater tuberosity was exposed. The width of the attachment of the capsule and the footprint of the rotator cuff were measured. RESULTS: The maximum capsular width was located at the border between the infraspinatus and the teres minor, and measured 9.1 mm. The minimum capsular width was 3.5 mm, and it was located at 10.9 mm posterior to the anterior margin of the greater tuberosity and 1.5 mm anterior to the posterior margin of the supraspinatus. CONCLUSION: Prior studies have overestimated the rotator cuff footprint width due to the lack of discrimination between the actual cuff insertion and capsule. The attachment of the articular capsule of the shoulder joint occupied a substantial area of the greater tuberosity. In particular, at the border between the infraspinatus and the teres minor, the very thick attachment of the articular capsule compensated for the lack of attachment of muscular components. The thinnest point of the articular capsule was 11 mm posterior to the anterior margin of the greater tuberosity and very close to the posterior edge of the tapered insertion of the supraspinatus, which could contribute to the etiology of degenerative rotator cuff tears.

A model of neuro-musculo-skeletal system for human locomotion under position constraint condition.

The human locomotion was studied on the basis of the interaction of the musculo-skeletal system, the neural system and the environment. A mathematical model of human locomotion under position constraint condition was established. Besides the neural rhythm generator, the posture controller and the sensory system, the environment feedback controller and the stability controller were taken into account in the model. The environment feedback controller was proposed for two purposes, obstacle avoidance and target position control of the swing foot. The stability controller was proposed to imitate the self-balancing ability of a human body and improve the stability of the model. In the stability controller, the ankle torque was used to control the velocity of the body gravity center. A prediction control algorithm was applied to calculate the torque magnitude of the stability controller. As an example, human stairs climbing movement was simulated and the results were given. The simulation result proved that the mathematical modeling of the task was successful.