scholarly journals Improved detection of air trapping on expiratory computed tomography using deep learning

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248902
Author(s):  
Sundaresh Ram ◽  
Benjamin A. Hoff ◽  
Alexander J. Bell ◽  
Stefanie Galban ◽  
Aleksa B. Fortuna ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Relative Volume ◽  
Ct Scans ◽  
Dice Coefficient ◽  
Air Trapping ◽  
Linear Mixed Effects ◽  
Limited Efficacy ◽  
Clinical Scores ◽  
Standard Techniques ◽  
Radiologic Evidence

Background Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression. Objective To investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques. Materials and methods Paired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model. Results QAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach. Conclusion The CNN model effectively delineated AT on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring AT in CF patients.

scholarly journals Improved Detection of Air Trapping on Expiratory Computed Tomography Using Deep Learning

2020 ◽  
Author(s):  
Sundaresh Ram ◽  
Benjamin A. Hoff ◽  
Alexander J. Bell ◽  
Stefanie Galban ◽  
Aleksa B. Fortuna ◽  
...  
Keyword(s):  
Relative Volume ◽  
Ct Scans ◽  
Radiographic Assessment ◽  
Dice Coefficient ◽  
Air Trapping ◽  
Linear Mixed Effects ◽  
Limited Efficacy ◽  
Clinical Scores ◽  
Standard Techniques ◽  
Radiologic Evidence

ABSTRACTBackgroundRadiologic evidence of air trapping (AT) on expiratory CT scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression.ObjectiveTo investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques.Materials and MethodsPaired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model.ResultsQAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach.ConclusionThe CNN model effectively delineated air trapping on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring air trapping in CF patients.

SPECIFIC CHARACTERISTICS OF BONE STRUCTURES ON CT-SCANS OF PATIENTS WITH SINONASAL INVERTED PAPILLOMAS

2019 ◽  
Vol 65 (4) ◽  
pp. 590-595
Author(s):  
Arkadiy Naumenko ◽  
Kseniya Sapova ◽  
Oleg Konoplev ◽  
Svetlana Astashchenko ◽  
Igor Chernushevich
Keyword(s):  
Computed Tomography ◽  
Tumor Recurrence ◽  
Inverted Papilloma ◽  
Ct Scans ◽  
Precise Localization ◽  
Sinonasal Inverted Papilloma ◽  
Bone Structures ◽  
Inverted Papillomas

Precise localization and excision of the originating site of a sinonasal inverted papilloma is essential for decreasing tumor recurrence. In this study we evaluated the use of preoperative computed tomography (CT) to pinpoint the attachment/origi-nating sites of the tumor.

scholarly journals Metacarpal Bony Dimensions Related to Headless Compression Screw Sizes

2019 ◽  
Vol 12 (S 01) ◽  
pp. S39-S44
Author(s):  
Michael Okoli ◽  
Kevin Lutsky ◽  
Michael Rivlin ◽  
Brian Katt ◽  
Pedro Beredjiklian
Keyword(s):  
Computed Tomography ◽  
Fracture Fixation ◽  
Ct Scans ◽  
Compression Screw ◽  
Metacarpal Head ◽  
Headless Compression Screw ◽  
Metacarpal Bones ◽  
Headless Compression Screws ◽  
The Mean ◽  
Distal Aspect

Abstract Introduction The purpose of this study is to determine the radiographic dimensions of the finger metacarpals and to compare these measurements with headless compression screws commonly used for fracture fixation. Materials and Methods We analyzed computed tomography (CT) scans of the index, long, ring, and small metacarpal bones and measured the metacarpal length, distance from the isthmus to the metacarpal head, and intramedullary diameter of the isthmus. Metacarpals with previous fractures or hardware were excluded. We compared these dimensions with the size of several commercially available headless screws used for intramedullary fixation. Results A total of 223 metacarpals from 57 patients were analyzed. The index metacarpal was the longest, averaging 67.6 mm in length. The mean distance from the most distal aspect of the metacarpal head to the isthmus was 40.3, 39.5, 34.4, and 31 mm for the index, long, ring, and small metacarpals, respectively. The narrowest diameter of the isthmus was a mean of 2.6, 2.7, 2.3, and 3 mm for the index, long, ring, and small metacarpals, respectively. Of 33 commercially available screws, only 27% percent reached the isthmus of the index metacarpal followed by 42, 48, and 58% in the long, ring, and small metacarpals, respectively. Conclusion The index and long metacarpals are at a particular risk of screw mismatch given their relatively long lengths and narrow isthmus diameters.

scholarly journals Conditional CT Strategy—An Effective Tool to Reduce Negative Appendectomy Rate and the Overuse of the CT

2021 ◽  
Vol 10 (11) ◽  
pp. 2456
Author(s):  
Raminta Luksaite-Lukste ◽  
Ruta Kliokyte ◽  
Arturas Samuilis ◽  
Eugenijus Jasiunas ◽  
Martynas Luksta ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Acute Appendicitis ◽  
Sensitivity And Specificity ◽  
Surgical Outcomes ◽  
Imaging Modality ◽  
Ct Scans ◽  
Negative Appendectomy ◽  
Transabdominal Ultrasound ◽  
First Choice ◽  
Negative Appendectomy Rate

(1) Background: Diagnosis of acute appendicitis (AA) remains challenging; either computed tomography (CT) is universally used or negative appendectomy rates of up to 30% are reported. Transabdominal ultrasound (TUS) as the first-choice imaging modality might be useful in adult patients to reduce the need for CT scans while maintaining low negative appendectomy (NA) rates. The aim of this study was to report the results of the conditional CT strategy for the diagnosis of acute appendicitis. (2) Methods: All patients suspected of acute appendicitis were prospectively registered from 1 January 2016 to 31 December 2018. Data on their clinical, radiological and surgical outcomes are presented. (3) Results: A total of 1855 patients were enrolled in our study: 1206 (65.0%) were women, 649 (35.0%) were men, and the median age was 34 years (IQR, 24.5–51). TUS was performed in 1851 (99.8%) patients, and CT in 463 (25.0%) patients. Appendices were not visualized on TUS in 1320 patients (71.3%). Furthermore, 172 (37.1%) of 463 CTs were diagnosed with AA, 42 (9.1%) CTs revealed alternative emergency diagnosis and 249 (53.8%) CTs were normal. Overall, 519 (28.0%) patients were diagnosed with AA: 464 appendectomies and 27 diagnostic laparoscopies were performed. The NA rate was 4.2%. The sensitivity and specificity for TUS and CT are as follows: 71.4% and 96.2%; 93.8% and 93.6%. (4) Conclusion: A conditional CT strategy is effective in reducing NA rates and avoids unnecessary CT in a large proportion of patients. Observation and repeated TUS might be useful in unclear cases.

scholarly journals Fully automated preoperative segmentation of temporal bone structures from clinical CT scans

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. A. Neves ◽  
E. D. Tran ◽  
I. M. Kessler ◽  
N. H. Blevins
Keyword(s):  
Facial Nerve ◽  
Inner Ear ◽  
Temporal Bone ◽  
Hausdorff Distance ◽  
Sigmoid Sinus ◽  
Ct Scans ◽  
Automated Segmentation ◽  
Dice Coefficient ◽  
Lateral Skull Base ◽  
End To End

AbstractMiddle- and inner-ear surgery is a vital treatment option in hearing loss, infections, and tumors of the lateral skull base. Segmentation of otologic structures from computed tomography (CT) has many potential applications for improving surgical planning but can be an arduous and time-consuming task. We propose an end-to-end solution for the automated segmentation of temporal bone CT using convolutional neural networks (CNN). Using 150 manually segmented CT scans, a comparison of 3 CNN models (AH-Net, U-Net, ResNet) was conducted to compare Dice coefficient, Hausdorff distance, and speed of segmentation of the inner ear, ossicles, facial nerve and sigmoid sinus. Using AH-Net, the Dice coefficient was 0.91 for the inner ear; 0.85 for the ossicles; 0.75 for the facial nerve; and 0.86 for the sigmoid sinus. The average Hausdorff distance was 0.25, 0.21, 0.24 and 0.45 mm, respectively. Blinded experts assessed the accuracy of both techniques, and there was no statistical difference between the ratings for the two methods (p = 0.93). Objective and subjective assessment confirm good correlation between automated segmentation of otologic structures and manual segmentation performed by a specialist. This end-to-end automated segmentation pipeline can help to advance the systematic application of augmented reality, simulation, and automation in otologic procedures.

scholarly journals Modelling growth curves of the normal infant’s mandible: 3D measurements using computed tomography

2021 ◽  
Author(s):  
Jan Aart M. Schipper ◽  
Manouk J. S. van Lieshout ◽  
Stefan Böhringer ◽  
Bonnie L. Padwa ◽  
Simon G. F. Robben ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Growth Models ◽  
Normal Growth ◽  
Growth Patterns ◽  
Ct Scans ◽  
Mandibular Ramus ◽  
Linear Measurements ◽  
Mandibular Growth ◽  
Gonial Angle ◽  
Mandibular Body

Abstract Objectives Data on normal mandibular development in the infant is lacking though essential to understand normal growth patterns and to discriminate abnormal growth. The aim of this study was to provide normal linear measurements of the mandible using computed tomography performed in infants from 0 to 2 years of age. Material and methods 3D voxel software was used to calculate mandibular body length, mandibular ramus length, bicondylar width, bigonial width and the gonial angle. Intra- and inter-rater reliability was assessed for these measurements. They were found to be sufficient for all distances; intra-class correlation coefficients were all above 0.9. Regression analysis for growth modelling was performed. Results In this multi-centre retrospective study, 109 CT scans were found eligible that were performed for various reasons (e.g. trauma, craniosynostosis, craniofacial abscesses). Craniosynostosis patients had larger mandibular measurements compared to non-craniosynostosis patients and were therefore excluded. Fifty-one CT scans were analysed. Conclusions Analysis showed that the mandible increases more in size vertically (the mandibular ramus) than horizontally (the mandibular body). Most of the mandibular growth occurs in the first 6 months. Clinical relevance These growth models provide insight into normal mandibular development in the first 2 years of life. This reference data facilitates discrimination between normal and abnormal mandibular growth.

Diagnostic Accuracy of Magnetic Resonance Imaging and Computed Tomography Scan in Young Athletes With Spondylolysis

2019 ◽  
Vol 58 (6) ◽  
pp. 671-676
Author(s):  
Amy M. West ◽  
Pierre A. d’Hemecourt ◽  
Olivia J. Bono ◽  
Lyle J. Micheli ◽  
Dai Sugimoto
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
Magnetic Resonance ◽  
Ct Scan ◽  
False Negative ◽  
False Negative Rate ◽  
Ct Scans ◽  
Resonance Imaging ◽  
Young Athletes ◽  
Negative Rate

The objective of this study was to determine diagnostic accuracy of magnetic resonance imaging (MRI) and computed tomography (CT) scans in young athletes diagnosed with spondylolysis. A cross-sectional study was used. Twenty-two young athletes (14.7 ± 1.5 years) were diagnosed as spondylolysis based on a single-photon emission CT. Following the diagnosis, participants underwent MRI and CT scan imaging tests on the same day. The sensitivity and false-negative rate of the MRI and CT scans were analyzed. MRI test confirmed 13 (+) and 9 (−) results while CT test showed 17 (+) and 5 (−) results. The sensitivity and false-negative rate of MRI were, respectively, 59.1% (95% confidence interval [CI] = 36.7% to 78.5%) and 40.9% (95% CI = 21.5% to 63.3%). Furthermore, the sensitivity and false-negative rate of CT scan were 77.3% (95% CI = 54.2% to 91.3%) and 22.7% (95% CI = 0.09% to 45.8%). Our results indicated that CT scan is a more accurate imaging modality to diagnose spondylolysis compared with MRI in young athletes.

X-RAY TOMOGRAPHY STUDIES OF PREHISTORIC CERAMIC ARTIFACTS

2014 ◽  
Vol 27 ◽  
pp. 1460135
Author(s):  
CARMEN PAVEL ◽  
FLORIN CONSTANTIN ◽  
COSMIN IOAN SUCIU ◽  
ROXANA BUGOI
Keyword(s):  
Computed Tomography ◽  
Cultural Heritage ◽  
Nuclear Physics ◽  
Structural Information ◽  
Ct Scans ◽  
Visual Examination ◽  
X Ray ◽  
X Ray Computed ◽  
Internal Configuration ◽  
Non Destructive

X-ray Computed Tomography (CT) is a powerful non-destructive technique that can yield interesting structural information not discernible through visual examination only. This paper presents the results of the CT scans of four objects belonging to the Romanian cultural heritage attributed to the Vinča, Cucuteni and Cruceni-Belegiš cultures. The study was performed with an X-ray tomographic device developed at the Department for Applied Nuclear Physics from Horia Hulubei National Institute for Nuclear Physics and Engineering in Măgurele, Romania. This apparatus was specially designed for archaeometric studies of low-Z artifacts: ceramic, wood, bone. The tomographic investigations revealed the internal configuration of the objects and provided information about the degree to which the previous manipulations affected the archaeological items. Based on the X-ray images resulting from the CT scans, hints about the techniques used in the manufacturing of the artifacts were obtained, as well as some indications useful for conservation/restoration purposes.

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