Patient-Specific 3-D Magnetic Resonance Imaging–Based Dynamic Simulation of Hip Impingement and Range of Motion Can Replace 3-D Computed Tomography–Based Simulation for Patients With Femoroacetabular Impingement: Implications for Planning Open Hip Preservation Surgery and Hip Arthroscopy

Background: Femoroacetabular impingement (FAI) is a complex 3-dimensional (3D) hip abnormality that can cause hip pain and osteoarthritis in young and active patients of childbearing age. Imaging is static and based on 2-dimensional radiographs or computed tomography (CT) scans. Recently, CT-based 3D impingement simulation was introduced for patient-specific assessments of hip deformities, whereas magnetic resonance imaging (MRI) offers a radiation-free alternative for surgical planning before hip arthroscopic surgery. Purpose: To (1) investigate the difference between 3D models of the hip, (2) correlate the location of hip impingement and range of motion (ROM), and (3) correlate diagnostic parameters while comparing CT- and MRI-based osseous 3D models of the hip in symptomatic patients with FAI. Study Design: Cohort study (Diagnosis); Level of evidence, 2. Methods: The authors performed an institutional review board–approved comparative and retrospective study of 31 hips in 26 symptomatic patients with FAI. We compared CT- and MRI-based osseous 3D models of the hip in the same patients. 3D CT scans (slice thickness, 1 mm) of the entire pelvis and the distal femoral condyles were obtained. Preoperative MRI of the hip was performed including an axial-oblique T1 VIBE sequence (slice thickness, 1 mm) and 2 axial anisotropic (1.2 × 1.2 × 1 mm) T1 VIBE Dixon sequences of the entire pelvis and the distal femoral condyles. Threshold-based semiautomatic reconstruction of 3D models was performed using commercial software. CT- and MRI-based 3D models were compared with specifically developed software. Results: (1) The difference between MRI- and CT-based 3D models was less than 1 mm for the proximal femur and the acetabulum (median surface distance, 0.4 ± 0.1 mm and 0.4 ± 0.2 mm, respectively). (2) The correlation for ROM values was excellent ( r = 0.99, P < .001) between CT and MRI. The mean absolute difference for flexion and extension was 1.9°± 1.5° and 2.6°± 1.9°, respectively. The location of impingement did not differ between CT- and MRI-based 3D ROM analysis in all 12 of 12 acetabular and 11 of 12 femoral clock-face positions. (3) The correlation for 6 diagnostic parameters was excellent ( r = 0.98, P < .001) between CT and MRI. The mean absolute difference for inclination and anteversion was 2.0°± 1.8° and 1.0°± 0.8°, respectively. Conclusion: Patient-specific and radiation-free MRI-based dynamic 3D simulation of hip impingement and ROM can replace CT-based 3D simulation for patients with FAI of childbearing age. On the basis of these excellent results, we intend to change our clinical practice, and we will use MRI-based 3D models for future clinical practice instead of CT-based 3D models. This allows radiation-free and patient-specific preoperative 3D impingement simulation for surgical planning and simulation of open hip preservation surgery and hip arthroscopic surgery.

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Three-Dimensional Magnetic Resonance Imaging Bone Models of the Hip Joint Using Deep Learning: Dynamic Simulation of Hip Impingement for Diagnosis of Intra- and Extra-articular Hip Impingement

Orthopaedic Journal of Sports Medicine ◽

10.1177/23259671211046916 ◽

2021 ◽

Vol 9 (11) ◽

pp. 232596712110469

Author(s):

Guodong Zeng ◽

Celia Degonda ◽

Adam Boschung ◽

Florian Schmaranzer ◽

Nicolas Gerber ◽

...

Keyword(s):

Hip Joint ◽

Automatic Segmentation ◽

3D Models ◽

Bone Segmentation ◽

Resonance Imaging ◽

Hip Impingement ◽

Mri Scans ◽

Fully Automatic ◽

The Difference ◽

Ct And Mri

Background: Dynamic 3-dimensional (3D) simulation of hip impingement enables better understanding of complex hip deformities in young adult patients with femoroacetabular impingement (FAI). Deep learning algorithms may improve magnetic resonance imaging (MRI) segmentation. Purpose: (1) To evaluate the accuracy of 3D models created using convolutional neural networks (CNNs) for fully automatic MRI bone segmentation of the hip joint, (2) to correlate hip range of motion (ROM) between manual and automatic segmentation, and (3) to compare location of hip impingement in 3D models created using automatic bone segmentation in patients with FAI. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: The authors retrospectively reviewed 31 hip MRI scans from 26 symptomatic patients (mean age, 27 years) with hip pain due to FAI. All patients had matched computed tomography (CT) and MRI scans of the pelvis and the knee. CT- and MRI-based osseous 3D models of the hip joint of the same patients were compared (MRI: T1 volumetric interpolated breath-hold examination high-resolution sequence; 0.8 mm3 isovoxel). CNNs were used to develop fully automatic bone segmentation of the hip joint, and the 3D models created using this method were compared with manual segmentation of CT- and MRI-based 3D models. Impingement-free ROM and location of hip impingement were calculated using previously validated collision detection software. Results: The difference between the CT- and MRI-based 3D models was <1 mm, and the difference between fully automatic and manual segmentation of MRI-based 3D models was <1 mm. The correlation of automatic and manual MRI-based 3D models was excellent and significant for impingement-free ROM ( r = 0.995; P < .001), flexion ( r = 0.953; P < .001), and internal rotation at 90° of flexion ( r = 0.982; P < .001). The correlation for impingement-free flexion between automatic MRI-based 3D models and CT-based 3D models was 0.953 ( P < .001). The location of impingement was not significantly different between manual and automatic segmentation of MRI-based 3D models, and the location of extra-articular hip impingement was not different between CT- and MRI-based 3D models. Conclusion: CNN can potentially be used in clinical practice to provide rapid and accurate 3D MRI hip joint models for young patients. The created models can be used for simulation of impingement during diagnosis of intra- and extra-articular hip impingement to enable radiation-free and patient-specific surgical planning for hip arthroscopy and open hip preservation surgery.

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Performance Evaluation of Different Cost Functions in Motion Vector Estimation

International Journal of Service Science Management Engineering and Technology ◽

10.4018/ijssmet.2014010103 ◽

2014 ◽

Vol 5 (1) ◽

pp. 45-65 ◽

Cited By ~ 12

Author(s):

Suvojit Acharjee ◽

Sayan Chakraborty ◽

Wahiba Ben Abdessalem Karaa ◽

Ahmad Taher Azar ◽

Nilanjan Dey

Keyword(s):

Video Compression ◽

Motion Vector ◽

Video Data ◽

Cost Functions ◽

Absolute Difference ◽

Surveillance Video ◽

Mean Absolute Difference ◽

Vector Estimation ◽

The Difference ◽

Temporal Redundancy

Video is an important medium in terms of information sharing in this present era. The tremendous growth of video use can be seen in the traditional multimedia application as well as in many other applications like medical videos, surveillance video etc. Raw video data is usually large in size, which demands for video compression. In different video compressing schemes, motion vector is a very important step to remove the temporal redundancy. A frame is first divided into small blocks and then motion vector for each block is computed. The difference between two blocks is evaluated by different cost functions (i.e. mean absolute difference (MAD), mean square error (MSE) etc).In this paper the performance of different cost functions was evaluated and also the most suitable cost function for motion vector estimation was found.

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P1559 3D echocardiography improves the agreement between left ventricular and right ventricular stroke volumes in healthy individuals

European Heart Journal - Cardiovascular Imaging ◽

10.1093/ehjci/jez319.980 ◽

2020 ◽

Vol 21 (Supplement_1) ◽

Author(s):

A P Pilalidou ◽

V K Kantartzi ◽

C A Adamopoulos ◽

L Z Zitiridou ◽

M D Dimtsa ◽

...

Keyword(s):

Healthy Subjects ◽

Left Ventricular ◽

Absolute Difference ◽

P Value ◽

Healthy Individuals ◽

Mean Absolute Difference ◽

Mean Values ◽

Intracardiac Shunt ◽

The Mean ◽

The Difference

Abstract Funding Acknowledgements None Background/Introduction: Calculation of the LV and RV stroke volumes (SV) with the volumetric method can be useful for assessment of valvular regurgitant volumes and intracardiac shunt ratios. However, this method often yields significant differences between the estimated LV and RV SV even in healthy subjects. We hypothesized that this discrepancy can be largely due to the assumption of LV and RV outflow tract circularity which forms the basis of 2D derived areas. Purpose To assess if the use of 3D transoesophageal (TOE) derived LVOT and RVOT areas can improve the agreement between LV and RV stroke volumes using the volumetric approach in healthy subjects with no valvular abnormality or intracardiac shunt. Methods We studied 20 patients (9 Males, age: 51 ± 19 y) submitted to TOE for various reasons, who had normal cardiac anatomy and function and good quality 3D TOE LVOT and RVOT data. Two dimensional TOE measurements of the LVOT and RVOT diameters were made in a zoomed mid oesophageal long axis and short axis view respectively; using these measurements 2D TOE LVOT and RVOT derived areas were calculated assuming circularity. In a similar way, we calculated the 2D LVOT and RVOT areas using data from transthoracic echo (TTE) for each patient. Offline analysis of the 3D TOE data allowed direct planimetry of the LVOT and RVOT areas devoid of any geometric assumptions. Finally, calculation of the 2D TTE, 2D TOE and 3D TOE LV and RV stroke volumes were performed for each patient based on the acquired data. The difference between LV and RV stroke volume (which theoretically should be around zero) for each technique and for each patient was also calculated. Results The mean LV and RV SV for the whole cohort, did not differ significantly within each method: 2D-TTE. However, the mean absolute difference between LV and RV stoke volumes for each technique was significantly lower with the use of 3D TOE compared to both 2D TTE and 2D TOE. Mean values and dispersion of absolute differences for each method are shown in Figure 1. Conclusions Compared to 2D, use of direct 3D TOE RVOT and LVOT planimetry yielded significantly less difference between RV and LV stroke volumes in healthy individuals. This finding can have potential clinical implications for more accurate assessment of valvular regurgitant volumes or intracardiac shunts. The mean absolute difference LV-RV Absolute mean defference between LV and RV 95%ΔΕ F(2.38) p-value TTE 2D 18,65 ± 11,72 (13,2-24,1) 8.63 0.001 TOE 2D 13,45 ± 12,44 (7,6-19.3) 8.63 0.001 TOE 3D 6,45 ± 3,62 (4,8-8,1) 8.63 0.001 Abstract P1559 Figure. Bland Altaman Analysis

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Abstract P154: Results From A Randomized Trial Of Different Rest Times Before Initiating BP Measurements

Hypertension ◽

10.1161/hyp.76.suppl_1.p154 ◽

2020 ◽

Vol 76 (Suppl_1) ◽

Author(s):

Tammy M Brady ◽

Junichi Ishigami ◽

Edgar R Miller ◽

Kunihiro Matsushita ◽

Lawrence J Appel ◽

...

Keyword(s):

Rest Period ◽

Wait Time ◽

Community Dwelling ◽

Absolute Difference ◽

Resource Constrained ◽

Mean Absolute Difference ◽

Rest Periods ◽

The Difference ◽

Mean Differences ◽

Design And Methods

Background: BP measurement guidelines recommend ≥5 min of rest before initiation of readings; this wait time is challenging to implement, especially in resource-constrained settings. Objective: Compare the effects of resting 0 or 2 min vs. 5 min on BP. Design and methods: RCT of community-dwelling adults, 18-80yrs. Participants had 4 sets of BP measurements (Omron HEM 970XL). In a cross-over design, the order of rest for the 1 st 3 sets [0min, 2min, 5min 1 ] was random. The 4 th set was always a 2nd 5min rest period (5min 2 ) to estimate repeatability. Mean BP for each rest period, mean absolute difference between each participant’s mean BP after 5min 1 and the other rest periods were determined. To determine if resting 0min and/or 2min was non-inferior to 5min 1 , we calculated the difference of differences, with ≤ ±2 mmHg considered non-inferior. Analyses were for the population overall and stratified by SBP ≥ vs. < 140mmHg. Results: N=113, mean age 55yrs, 36% male (n=41), 74% AA (n=84), 28% SBP > 140mmHg (n=32). Overall, mean 5min 1 BP was 128/75 and 5min 2 BP was 127/76 (p=NS), similar to mean BP at 2min and 0min (127/74 for both). The absolute difference of differences between 2min and 5min 1 SBP for the population overall was > ±2 mmHg, but for those with SBP <140, resting 2min and 0min BP was ≤ ±2 mmHg (Table). Conclusion: In this RCT, mean differences in BP by rest period were small. BPs obtained after shorter rest periods were non-inferior than those obtained after 5min when SBP <140. This suggests shorter rest times, even 0 min, may be reasonable for screening when the initial SBP is <140. These findings could improve the efficiency of hypertension screening, especially in resource-constrained settings.

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Interpretation of Coastal HF Radar–Derived Surface Currents with High-Resolution Drifter Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1998.1 ◽

2007 ◽

Vol 24 (4) ◽

pp. 666-680 ◽

Cited By ~ 89

Author(s):

Carter Ohlmann ◽

Peter White ◽

Libe Washburn ◽

Brian Emery ◽

Eric Terrill ◽

...

Keyword(s):

San Diego ◽

Surface Current ◽

Hf Radar ◽

Absolute Difference ◽

Time And Space ◽

Santa Barbara ◽

Mean Absolute Difference ◽

The Difference ◽

Surface Drifters ◽

Good Agreement

Abstract Dense arrays of surface drifters are used to quantify the flow field on time and space scales over which high-frequency (HF) radar observations are measured. Up to 13 drifters were repetitively deployed off the Santa Barbara and San Diego coasts on 7 days during 18 months. Each day a regularly spaced grid overlaid on a 1-km2 (San Diego) or 4-km2 (Santa Barbara) square, located where HF radar radial data are nearly orthogonal, was seeded with drifters. As drifters moved from the square, they were retrieved and replaced to maintain a spatially uniform distribution of observations within the sampling area during the day. This sampling scheme resulted in up to 56 velocity observations distributed over the time (1 h) and space (1 and 4 km2) scales implicit in typical surface current maps from HF radar. Root-mean-square (RMS) differences between HF radar radial velocities obtained using measured antenna patterns, and average drifter velocities, are mostly 3–5 cm s−1. Smaller RMS differences compared with past validation studies that employ current meters are due to drifter resolution of subgrid-scale velocity variance included in time and space average HF radar fields. Roughly 5 cm s−1 can be attributed to sampling on disparate time and space scales. Despite generally good agreement, differences can change dramatically with time. In one instance, the difference increases from near zero to more than 20 cm s−1 within 2 h. The RMS difference and bias (mean absolute difference) for that day exceed 7 and 12 cm s−1, respectively.

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Combined deep CNN–LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features

Scientific Reports ◽

10.1038/s41598-021-92997-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Da Un Jeong ◽

Ki Moo Lim

Keyword(s):

Blood Pressure ◽

Blood Pressure Measurement ◽

Patient Specific ◽

Peak Time ◽

Simultaneous Prediction ◽

Deep Cnn ◽

Pressure Estimation ◽

The Difference ◽

Blood Pressure Estimation ◽

Continuous Blood Pressure

AbstractThe pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) signal and the systolic peak of photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. However, it is difficult to accurately measure PAT from ECG and PPG signals because they have inconsistent shapes owing to patient-specific physical characteristics, pathological conditions, and movements. Accordingly, complex preprocessing is required to estimate blood pressure based on PAT. In this paper, as an alternative solution, we propose a noninvasive continuous algorithm using the difference between ECG and PPG as a new feature that can include PAT information. The proposed algorithm is a deep CNN–LSTM-based multitasking machine learning model that outputs simultaneous prediction results of systolic (SBP) and diastolic blood pressures (DBP). We used a total of 48 patients on the PhysioNet website by splitting them into 38 patients for training and 10 patients for testing. The prediction accuracies of SBP and DBP were 0.0 ± 1.6 mmHg and 0.2 ± 1.3 mmHg, respectively. Even though the proposed model was assessed with only 10 patients, this result was satisfied with three guidelines, which are the BHS, AAMI, and IEEE standards for blood pressure measurement devices.

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Mask-R$$^{2}$$CNN: a distance-field regression version of Mask-RCNN for fetal-head delineation in ultrasound images

International Journal of Computer Assisted Radiology and Surgery ◽

10.1007/s11548-021-02430-0 ◽

2021 ◽

Author(s):

Sara Moccia ◽

Maria Chiara Fiorentino ◽

Emanuele Frontoni

Keyword(s):

Fetal Growth ◽

A Priori ◽

Absolute Difference ◽

Ultrasound Images ◽

Fetal Head ◽

Mean Absolute Difference ◽

Distance Field ◽

Feature Pyramid ◽

End To End ◽

Ablation Study

Abstract Background and objectives Fetal head-circumference (HC) measurement from ultrasound (US) images provides useful hints for assessing fetal growth. Such measurement is performed manually during the actual clinical practice, posing issues relevant to intra- and inter-clinician variability. This work presents a fully automatic, deep-learning-based approach to HC delineation, which we named Mask-R$$^{2}$$ 2 CNN. It advances our previous work in the field and performs HC distance-field regression in an end-to-end fashion, without requiring a priori HC localization nor any postprocessing for outlier removal. Methods Mask-R$$^{2}$$ 2 CNN follows the Mask-RCNN architecture, with a backbone inspired by feature-pyramid networks, a region-proposal network and the ROI align. The Mask-RCNN segmentation head is here modified to regress the HC distance field. Results Mask-R$$^{2}$$ 2 CNN was tested on the HC18 Challenge dataset, which consists of 999 training and 335 testing images. With a comprehensive ablation study, we showed that Mask-R$$^{2}$$ 2 CNN achieved a mean absolute difference of 1.95 mm (standard deviation $$=\pm 1.92$$ = ± 1.92 mm), outperforming other approaches in the literature. Conclusions With this work, we proposed an end-to-end model for HC distance-field regression. With our experimental results, we showed that Mask-R$$^{2}$$ 2 CNN may be an effective support for clinicians for assessing fetal growth.

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Quality Control in 3D Printing: Accuracy Analysis of 3D-Printed Models of Patient-Specific Anatomy

Materials ◽

10.3390/ma14041021 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1021

Author(s):

Bernhard Dorweiler ◽

Pia Elisabeth Baqué ◽

Rayan Chaban ◽

Ahmed Ghazy ◽

Oroa Salem

Keyword(s):

Wall Thickness ◽

Large Scale ◽

Fused Deposition Modeling ◽

Vascular Anatomy ◽

3D Models ◽

Patient Specific ◽

Stl File ◽

Fused Deposition ◽

3D Printed ◽

The Mean

As comparative data on the precision of 3D-printed anatomical models are sparse, the aim of this study was to evaluate the accuracy of 3D-printed models of vascular anatomy generated by two commonly used printing technologies. Thirty-five 3D models of large (aortic, wall thickness of 2 mm, n = 30) and small (coronary, wall thickness of 1.25 mm, n = 5) vessels printed with fused deposition modeling (FDM) (rigid, n = 20) and PolyJet (flexible, n = 15) technology were subjected to high-resolution CT scans. From the resulting DICOM (Digital Imaging and Communications in Medicine) dataset, an STL file was generated and wall thickness as well as surface congruency were compared with the original STL file using dedicated 3D engineering software. The mean wall thickness for the large-scale aortic models was 2.11 µm (+5%), and 1.26 µm (+0.8%) for the coronary models, resulting in an overall mean wall thickness of +5% for all 35 3D models when compared to the original STL file. The mean surface deviation was found to be +120 µm for all models, with +100 µm for the aortic and +180 µm for the coronary 3D models, respectively. Both printing technologies were found to conform with the currently set standards of accuracy (<1 mm), demonstrating that accurate 3D models of large and small vessel anatomy can be generated by both FDM and PolyJet printing technology using rigid and flexible polymers.

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Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images

International Journal of Computer Assisted Radiology and Surgery ◽

10.1007/s11548-021-02334-z ◽

2021 ◽

Vol 16 (4) ◽

pp. 597-607

Author(s):

Annika Niemann ◽

Samuel Voß ◽

Riikka Tulamo ◽

Simon Weigand ◽

Bernhard Preim ◽

...

Keyword(s):

Wall Thickness ◽

Vessel Wall ◽

Intracranial Aneurysms ◽

Geometric Model ◽

Image Data ◽

Outer Wall ◽

3D Models ◽

Patient Specific ◽

Intracranial Vessel ◽

Hemodynamic Simulations

Abstract Purpose For the evaluation and rupture risk assessment of intracranial aneurysms, clinical, morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall. Methods In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations. Result We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious. Conclusion The presented approach enables the creation of a geometric model with differentiated wall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.

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Comparing the Tibial Tuberosity–Trochlear Groove Distance Between CT and MRI in Skeletally Immature Patients With and Without Patellar Instability

Orthopaedic Journal of Sports Medicine ◽

10.1177/2325967120973665 ◽

2021 ◽

Vol 9 (1) ◽

pp. 232596712097366

Author(s):

Zhen-Zhen Dai ◽

Lin Sha ◽

Zi-Ming Zhang ◽

Zhen-Peng Liang ◽

Hao Li ◽

...

Keyword(s):

Patellar Instability ◽

Intraclass Correlation ◽

Mean Difference ◽

Tibial Tubercle ◽

Control Group ◽

Trochlear Groove ◽

Skeletally Immature ◽

Bony Landmarks ◽

The Difference ◽

Ct And Mri

Background: The tibial tubercle–trochlear groove (TT-TG) distance was originally described for computed tomography (CT), but it has been measured on magnetic resonance imaging (MRI) in patients with patellar instability (PI). Whether the TT-TG measured on CT versus MRI can be considered equivalent in skeletally immature children remains unclear. Purpose: To investigate in skeletally immature patients (1) the effects of CT versus MRI imaging modality and cartilage versus bony landmarks on consistency of TT-TG measurement, (2) the difference between CT and MRI measurements of the TT-TG, and (3) the difference in TT-TG between patients with and without PI. Study Design: Cross-sectional study; Level of evidence, 3. Methods: We retrospectively identified 24 skeletally immature patients with PI and 24 patients with other knee disorders or injury but without PI. The bony and cartilaginous TT-TG distances on CT and MRI were measured by 2 researchers, and related clinical data were collected. The interrater, interperiod (bony vs cartilaginous), and intermethod (CT vs MRI) reliabilities of TT-TG measurement were assessed with intraclass correlation coefficients. Results: The 48 study patients (19 boys, 29 girls) had a mean age of 11.3 years (range, 7-14 years). TT-TG measurements had excellent interrater reliability and good or excellent interperiod reliability but fair or poor intermethod reliability. TT-TG distance was greater on CT versus MRI (mean difference, 4.07 mm; 95% CI, 2.6-5.5 mm), and cartilaginous distance was greater than bony distance (mean difference, 2.3 mm; 95% CI, 0.79-3.8 mm). The TT-TG measured on CT was found to increase with the femoral width. Patients in the PI group had increased TT-TG distance compared with those in the control group, regardless of landmarks or modality used ( P > .05 for all). Conclusion: For skeletally immature patients, the TT-TG distance could be evaluated on MRI, regardless of whether cartilage or bony landmarks were used. Its value could not be interchanged with CT according to our results; however, further research on this topic is needed.

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