Accurate measurement of thyroid volume is important for thyroid disease diagnosis and therapy. In nuclear medicine, the thyroid volume is usually estimated from scintigraphy images using empirical equations. However, due to the lack of volumetric information from the scintigraphy image, the accuracy of equation-based estimation is imperfect. To solve this problem, this paper proposes a method which registers a 3D thyroid statistical shape model (SSM) to a single-view scintigraphy image to achieve more accurate volume estimation. The SSM was constructed based on a training set of segmented 3D CT images, and the thyroid shape variations between the training subjects were modelled using the point distribution model. For thyroid volume estimation, the SSM was projected into the scintigraphy image of the target patient, and then the projected model shape was nonrigidly registered with the patient’s scintigraphy image. The resultant 2D deformation file was back-projected to 3D space to guide the deformation of the 3D SSM. This process was repeated iteratively until convergence, and the volume of the finally deformed SSM was considered as the estimation of the patient’s thyroid volume. For validation, this method was evaluated based on a test set of 20 scintigraphy images, achieving an estimation error of  −2.10%  ±  5.20% which was much less than the error of the conventional equation-based method (35.76%  ±  15.20%) based on the same test set. The robustness of this method was further tested using a challenging case, i.e. a scintigraphy image with a large thyroid tumor. For this case, the volume estimation error was only 6.08%. Our method has significantly improved the accuracy of thyroid volume estimation from scintigraphy images, and it will enhance the value of scintigraphy imaging for thyroid disease diagnosis and radioiodine therapy.

Traumatic brain injury (TBI) is a universal leading cause of long-term neurological disability and causes a huge burden to an ever-growing population. Moderate intensity of treadmill exercise has been recognized as an efficient intervention to combat TBI-induced motor and cognitive disorders, yet the underlying mechanism is still unclear. Ferroptosis is known to be highly implicated in TBI pathophysiology, and the anti-ferroptosis effects of treadmill exercise have been reported in other neurological diseases except for TBI. In addition to cytokine induction, recent evidence has demonstrated the involvement of the stimulator of interferon genes (STING) pathway in ferroptosis. Therefore, we examined the possibility that treadmill exercise might inhibit TBI-induced ferroptosis via STING pathway. In this study, we first found that a series of ferroptosis-related characteristics, including abnormal iron homeostasis, decreased glutathione peroxidase 4 (Gpx4), and increased lipid peroxidation, were detected at 44 days post TBI, substantiating the involvement of ferroptosis at the chronic stage following TBI. Furthermore, treadmill exercise potently decreased the aforementioned ferroptosis-related changes, suggesting the anti-ferroptosis role of treadmill exercise following TBI. In addition to alleviating neurodegeneration, treadmill exercise effectively reduced anxiety, enhanced spatial memory recovery, and improved social novelty post TBI. Interestingly, STING knockdown also obtained the similar anti-ferroptosis effects after TBI. More importantly, overexpression of STING largely reversed the ferroptosis inactivation caused by treadmill exercise following TBI. To conclude, moderate-intensity treadmill exercise rescues TBI-induced ferroptosis and cognitive deficits at least in part via STING pathway, broadening our understanding of neuroprotective effects induced by treadmill exercise against TBI.

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