Update on the Diagnosis and Management of Early-onset Scoliosis
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Cited by 3 publications
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Auto-segmentation of thoraco-abdominal organs in pediatric dynamic MRI
Purpose: Analysis of the abnormal motion of thoraco-abdominal organs in respiratory disorders such as the Thoracic Insufficiency Syndrome (TIS) and scoliosis such as adolescent idiopathic scoliosis (AIS) or early onset scoliosis (EOS) can lead to better surgical plans. We can use healthy subjects to find out the normal architecture and motion of a rib cage and associated organs and attempt to modify the patient's deformed anatomy to match to it. Dynamic magnetic resonance imaging (dMRI) is a practical and preferred imaging modality for capturing dynamic images of healthy pediatric subjects. In this paper, we propose an auto-segmentation set-up for the lungs, kidneys, liver, spleen, and thoraco-abdominal skin in these dMRI images which have their own challenges such as poor contrast, image non-standardness, and similarity in texture amongst gas, bone, and connective tissue at several inter-object interfaces. Methods: The segmentation set-up has been implemented in two steps: recognition and delineation using two deep neural network (DL) architectures (say DL-R and DL-D) for the recognition step and delineation step, respectively. The encoder-decoder framework in DL-D utilizes features at four different resolution levels to counter the challenges involved in the segmentation. We have evaluated on dMRI sagittal acquisitions of 189 (near-)normal subjects. The spatial resolution in all dMRI acquisitions is 1.46 mm in a sagittal slice and 6.00 mm between sagittal slices. We utilized images of 89 (10) subjects at end inspiration for training (validation). For testing we experimented with three scenarios: utilizing (1) the images of 90 (=189-89-10) different (remaining) subjects at end inspiration for testing, (2) the images of the aforementioned 90 subjects at end expiration for testing, and (3) the images of the aforesaid 99 (=89+10) subjects but at end expiration for testing. In some situations, we can take advantage of already available ground truth (GT) of a subject at a particular respiratory phase to automatically segment the object in the image of the same subject at a different respiratory phase and then refining the segmentation to create the final GT. We anticipate that this process of creating GT would require minimal post hoc correction. In this spirit, we conducted separate experiments where we assume to have the ground truth of the test subjects at end expiration for scenario (1), end inspiration for (2), and end inspiration for (3). Results: Amongst these three scenarios of testing, for the DL-R, we achieve a best average location error (LE) of about 1 voxel for the lungs, kidneys, and spleen and 1.5 voxels for the liver and the thoraco-abdominal skin. The standard deviation (SD) of LE is about 1 or 2 voxels. For the delineation approach, we achieve an average Dice coefficient (DC) of about 0.92 to 0.94 for the lungs, 0.82 for the kidneys, 0.90 for the liver, 0.81 for the spleen, and 0.93 for the thoraco-abdominal skin. The SD of DC is lower for the lungs, liver, and the thoraco-abdominal skin, and slightly higher for the spleen and kidneys. Conclusions: Motivated by applications in surgical planning for disorders such as TIS, AIS, and EOS, we have shown an auto-segmentation system for thoraco-abdominal organs in dMRI acquisitions. This proposed setup copes with the challenges posed by low resolution, motion blur, inadequate contrast, and image intensity non-standardness quite well. We are in the process of testing its effectiveness on TIS patient dMRI data.
Auto-segmentation of thoraco-abdominal organs in pediatric dynamic MRI
Purpose: Analysis of the abnormal motion of thoraco-abdominal organs in respiratory disorders such as the Thoracic Insufficiency Syndrome (TIS) and scoliosis such as adolescent idiopathic scoliosis (AIS) or early onset scoliosis (EOS) can lead to better surgical plans. We can use healthy subjects to find out the normal architecture and motion of a rib cage and associated organs and attempt to modify the patient's deformed anatomy to match to it. Dynamic magnetic resonance imaging (dMRI) is a practical and preferred imaging modality for capturing dynamic images of healthy pediatric subjects. In this paper, we propose an auto-segmentation set-up for the lungs, kidneys, liver, spleen, and thoraco-abdominal skin in these dMRI images which have their own challenges such as poor contrast, image non-standardness, and similarity in texture amongst gas, bone, and connective tissue at several inter-object interfaces. Methods: The segmentation set-up has been implemented in two steps: recognition and delineation using two deep neural network (DL) architectures (say DL-R and DL-D) for the recognition step and delineation step, respectively. The encoder-decoder framework in DL-D utilizes features at four different resolution levels to counter the challenges involved in the segmentation. We have evaluated on dMRI sagittal acquisitions of 189 (near-)normal subjects. The spatial resolution in all dMRI acquisitions is 1.46 mm in a sagittal slice and 6.00 mm between sagittal slices. We utilized images of 89 (10) subjects at end inspiration for training (validation). For testing we experimented with three scenarios: utilizing (1) the images of 90 (=189-89-10) different (remaining) subjects at end inspiration for testing, (2) the images of the aforementioned 90 subjects at end expiration for testing, and (3) the images of the aforesaid 99 (=89+10) subjects but at end expiration for testing. In some situations, we can take advantage of already available ground truth (GT) of a subject at a particular respiratory phase to automatically segment the object in the image of the same subject at a different respiratory phase and then refining the segmentation to create the final GT. We anticipate that this process of creating GT would require minimal post hoc correction. In this spirit, we conducted separate experiments where we assume to have the ground truth of the test subjects at end expiration for scenario (1), end inspiration for (2), and end inspiration for (3). Results: Amongst these three scenarios of testing, for the DL-R, we achieve a best average location error (LE) of about 1 voxel for the lungs, kidneys, and spleen and 1.5 voxels for the liver and the thoraco-abdominal skin. The standard deviation (SD) of LE is about 1 or 2 voxels. For the delineation approach, we achieve an average Dice coefficient (DC) of about 0.92 to 0.94 for the lungs, 0.82 for the kidneys, 0.90 for the liver, 0.81 for the spleen, and 0.93 for the thoraco-abdominal skin. The SD of DC is lower for the lungs, liver, and the thoraco-abdominal skin, and slightly higher for the spleen and kidneys. Conclusions: Motivated by applications in surgical planning for disorders such as TIS, AIS, and EOS, we have shown an auto-segmentation system for thoraco-abdominal organs in dMRI acquisitions. This proposed setup copes with the challenges posed by low resolution, motion blur, inadequate contrast, and image intensity non-standardness quite well. We are in the process of testing its effectiveness on TIS patient dMRI data.
Diagnostic and therapeutic strategies in early onset scoliosis: A current concept review
Substantial advances in the treatment of early onset scoliosis (EOS) over the past two to three decades have resulted in significant improvements in health-related quality of life of affected children. In addition to classifications that address the marked heterogeneity of this patient population, increasing understanding of the natural history of the disease, and new implants and treatment techniques have resulted in innovations unlike any other area of pediatric orthopedics. The growing understanding of the interaction between spinal and thoracic growth, as well as dependent lung maturation, has had a lasting impact on the treatment strategy of this potentially life-threatening disease. The previous treatment approach with early corrective fusion gave way to a growth-friendly concept. Despite the steady development of new growth-friendly surgical treatment options, whose efficacy still needs to be validated, as well as a revival of conservative growth control with serial casts and/or braces, the psychosocial burden of the long lasting and complication-prone treatments remains high. As a consequence, EOS still represents one of the greatest pediatric orthopedic challenges.
Modern Internet Search Analytics: Is There a Difference in What Patients are Searching Regarding the Operative and Nonoperative Management of Scoliosis?
Study Design Observational Study. Objectives This study aimed to investigate the most searched types of questions and online resources implicated in the operative and nonoperative management of scoliosis. Methods Six terms related to operative and nonoperative scoliosis treatment were searched on Google’s People Also Ask section on October 12, 2023. The Rothwell classification was used to sort questions into fact, policy, or value categories, and associated websites were classified by type. Fischer’s exact tests compared question type and websites encountered between operative and nonoperative questions. Statistical significance was set at the .05 level. Results The most common questions concerning operative and nonoperative management were fact (53.4%) and value (35.5%) questions, respectively. The most common subcategory pertaining to operative and nonoperative questions were specific activities/restrictions (21.7%) and evaluation of treatment (33.3%), respectively. Questions on indications/management (13.2% vs 31.2%, P < .001) and evaluation of treatment (10.1% vs 33.3%, P < .001) were associated with nonoperative scoliosis management. Medical practice websites were the most common website to which questions concerning operative (31.9%) and nonoperative (51.4%) management were directed to. Operative questions were more likely to be directed to academic websites (21.7% vs 10.0%, P = .037) and less likely to be directed to medical practice websites (31.9% vs 51.4%, P = .007) than nonoperative questions. Conclusions During scoliosis consultations, spine surgeons should emphasize the postoperative recovery process and efficacy of conservative treatment modalities for the operative and nonoperative management of scoliosis, respectively. Future research should assess the impact of website encounters on patients’ decision-making.
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