The Preprocessed Connectomes Project Repository of Manually Corrected Skull-stripped T1-weighted Anatomical MRI Data

AbstractBackgroundSkull-stripping is the procedure of removing non-brain tissue from anatomical MRI data. This procedure is necessary for calculating brain volume and for improving the quality of other image processing steps. Developing new skull-stripping algorithms and evaluating their performance requires gold standard data from a variety of different scanners and acquisition methods. We complement existing repositories with manually-corrected brain masks for 125 T1-weighted anatomical scans from the Nathan Kline Institute Enhanced Rockland Sample Neurofeedback Study.FindingsSkull-stripped images were obtained using a semi-automated procedure that involved skull-stripping the data using the brain extraction based on non local segmentation technique (BEaST) software and manually correcting the worst results. Corrected brain masks were added into the BEaST library and the procedure was reiterated until acceptable brain masks were available for all images. In total, 85 of the skull-stripped images were hand-edited and 40 were deemed to not need editing. The results are brain masks for the 125 images along with a BEaST library for automatically skull-stripping other data.ConclusionSkull-stripped anatomical images from the Neurofeedback sample are available for download from the Preprocessed Connectomes Project. The resulting brain masks can be used by researchers to improve their preprocessing of the Neurofeedback data, and as training and testing data for developing new skull-stripping algorithms and evaluating the impact on other aspects of MRI preprocessing. We have illustrated the utility of these data as a reference for comparing various automatic methods and evaluated the performance of the newly created library on independent data.

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Automated skull stripping in mouse fMRI analysis using 3D U-Net

10.1101/2021.10.08.462356 ◽

2021 ◽

Author(s):

Guohui Ruan ◽

Jiaming Liu ◽

Ziqi An ◽

Kaiibin Wu ◽

Chuanjun Tong ◽

...

Keyword(s):

Hausdorff Distance ◽

Automatic Segmentation ◽

Resting State Fmri ◽

Jaccard Index ◽

Brain Extraction ◽

Functional Images ◽

Skull Stripping ◽

Anatomical Images ◽

Fmri Analysis ◽

T2 Weighted Images

Skull stripping is an initial and critical step in the pipeline of mouse fMRI analysis. Manual labeling of the brain usually suffers from intra- and inter-rater variability and is highly time-consuming. Hence, an automatic and efficient skull-stripping method is in high demand for mouse fMRI studies. In this study, we investigated a 3D U-Net based method for automatic brain extraction in mouse fMRI studies. Two U-Net models were separately trained on T2-weighted anatomical images and T2*-weighted functional images. The trained models were tested on both interior and exterior datasets. The 3D U-Net models yielded a higher accuracy in brain extraction from both T2-weighted images (Dice > 0.984, Jaccard index > 0.968 and Hausdorff distance < 7.7) and T2*-weighted images (Dice > 0.964, Jaccard index > 0.931 and Hausdorff distance < 3.3), compared with the two widely used mouse skull-stripping methods (RATS and SHERM). The resting-state fMRI results using automatic segmentation with the 3D U-Net models are identical to those obtained by manual segmentation for both the seed-based and group independent component analysis. These results demonstrate that the 3D U-Net based method can replace manual brain extraction in mouse fMRI analysis.

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Self-Compassion and Quality of Life in Adults Who Stutter

American Journal of Speech-Language Pathology ◽

10.1044/2020_ajslp-20-00055 ◽

2020 ◽

Vol 29 (4) ◽

pp. 2097-2108

Author(s):

Robyn L. Croft ◽

Courtney T. Byrd

Keyword(s):

Quality Of Life ◽

Social Connectedness ◽

The Self ◽

Future Research ◽

Self Compassion ◽

Adults Who Stutter ◽

And Gender ◽

Relationship Of ◽

The Impact

Purpose The purpose of this study was to identify levels of self-compassion in adults who do and do not stutter and to determine whether self-compassion predicts the impact of stuttering on quality of life in adults who stutter. Method Participants included 140 adults who do and do not stutter matched for age and gender. All participants completed the Self-Compassion Scale. Adults who stutter also completed the Overall Assessment of the Speaker's Experience of Stuttering. Data were analyzed for self-compassion differences between and within adults who do and do not stutter and to predict self-compassion on quality of life in adults who stutter. Results Adults who do and do not stutter exhibited no significant differences in total self-compassion, regardless of participant gender. A simple linear regression of the total self-compassion score and total Overall Assessment of the Speaker's Experience of Stuttering score showed a significant, negative linear relationship of self-compassion predicting the impact of stuttering on quality of life. Conclusions Data suggest that higher levels of self-kindness, mindfulness, and social connectedness (i.e., self-compassion) are related to reduced negative reactions to stuttering, an increased participation in daily communication situations, and an improved overall quality of life. Future research should replicate current findings and identify moderators of the self-compassion–quality of life relationship.

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Surgery for Lung Cancer and the Consequences for the Swallow

Perspectives of the ASHA Special Interest Groups ◽

10.1044/persp1.sig13.162 ◽

2016 ◽

Vol 1 (13) ◽

pp. 162-168

Author(s):

Pippa Hales ◽

Corinne Mossey-Gaston

Keyword(s):

Lung Cancer ◽

Treatment Options ◽

Vocal Cord Palsy ◽

Subsequent Treatment ◽

Physiological Reserve ◽

Palliative Phase ◽

And Function ◽

The Impact ◽

Swallow Function

Lung cancer is one of the most commonly diagnosed cancers across Northern America and Europe. Treatment options offered are dependent on the type of cancer, the location of the tumor, the staging, and the overall health of the person. When surgery for lung cancer is offered, difficulty swallowing is a potential complication that can have several influencing factors. Surgical interaction with the recurrent laryngeal nerve (RLN) can lead to unilateral vocal cord palsy, altering swallow function and safety. Understanding whether the RLN has been preserved, damaged, or sacrificed is integral to understanding the effect on the swallow and the subsequent treatment options available. There is also the risk of post-surgical reduction of physiological reserve, which can reduce the strength and function of the swallow in addition to any surgery specific complications. As lung cancer has a limited prognosis, the clinician must also factor in the palliative phase, as this can further increase the burden of an already compromised swallow. By understanding the surgery and the implications this may have for the swallow, there is the potential to reduce the impact of post-surgical complications and so improve quality of life (QOL) for people with lung cancer.

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