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Al-Ubeidy, H., Alshamari, M., Widell, J., Eriksson, T. & Lidén, M. (2019). High-pitch, low-kVp computed tomography for ruling out pulmonary embolism with 17-mL contrast media. In: : . Paper presented at European Conference of Radiology (ECR), Vienna, Austria, 2019.
Open this publication in new window or tab >>High-pitch, low-kVp computed tomography for ruling out pulmonary embolism with 17-mL contrast media
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2019 (English)Conference paper, Oral presentation with published abstract (Refereed)
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:oru:diva-73820 (URN)
Conference
European Conference of Radiology (ECR), Vienna, Austria, 2019
Available from: 2019-04-16 Created: 2019-04-16 Last updated: 2019-04-16Bibliographically approved
Lidén, M. (2018). A new method for predicting uric acid composition in urinary stones using routine single-energy CT. Urolithiasis, 46(4), 325-332
Open this publication in new window or tab >>A new method for predicting uric acid composition in urinary stones using routine single-energy CT
2018 (English)In: Urolithiasis, ISSN 2194-7228, Vol. 46, no 4, p. 325-332Article in journal (Refereed) Published
Abstract [en]

Urinary stones composed of uric acid can be treated medically. Prediction of uric acid stone type is, therefore, desirable when a urinary stone is diagnosed with unenhanced CT. The purpose of the present study was to describe single-energy thin slice quantitative CT parameters of urinary stones correlated to chemical stone type and to develop a method to distinguish pure uric acid stones (UA) from other stones (non-UA/Mix). Unenhanced thin slice single-energy CT images of 126 urinary stones (117 patients) with known chemical stone type were retrospectively included in the study. Among the included stones, 22 were UA and 104 were non-UA/Mix. The included CT images and Laplacian filtered images of the stones were quantitatively analyzed using operator-independent methods. A post hoc classification method for pure UA stones was created using a combination of cutoff values for the peak attenuation and peak point Laplacian. The stone types differed in most quantitative image characteristics including mean attenuation (p < 0.001), peak attenuation (p < 0.001), and peak point Laplacian (p < 0.001). The sensitivity for the post hoc-developed peak attenuation-peak point Laplacian method for classifying pure UA stones was 95% [21/22, 95% CI (77-100%)] and the specificity was 99% [103/104, 95% CI (95-100%)]. In conclusion, quantitative image analysis of thin slice routine single-energy CT images is promising for predicting pure UA content in urinary stones, with results comparable to double energy methods.

Place, publisher, year, edition, pages
Springer, 2018
Keywords
Urinary stone, Kidney stone, Uric acid, Computed tomography, Image analysis, Urolithiasis
National Category
Medical Image Processing Urology and Nephrology
Identifiers
urn:nbn:se:oru:diva-60803 (URN)10.1007/s00240-017-0994-x (DOI)000438600700002 ()28660283 (PubMedID)
Note

Funding Agency:

Universitetssjukhuset Örebro  OLL-523931

Available from: 2017-10-16 Created: 2017-10-16 Last updated: 2018-08-06Bibliographically approved
Längkvist, M., Jendeberg, J., Thunberg, P., Loutfi, A. & Lidén, M. (2018). Computer aided detection of ureteral stones in thin slice computed tomography volumes using Convolutional Neural Networks. Computers in Biology and Medicine, 97, 153-160
Open this publication in new window or tab >>Computer aided detection of ureteral stones in thin slice computed tomography volumes using Convolutional Neural Networks
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2018 (English)In: Computers in Biology and Medicine, ISSN 0010-4825, E-ISSN 1879-0534, Vol. 97, p. 153-160Article in journal (Refereed) Published
Abstract [en]

Computed tomography (CT) is the method of choice for diagnosing ureteral stones - kidney stones that obstruct the ureter. The purpose of this study is to develop a computer aided detection (CAD) algorithm for identifying a ureteral stone in thin slice CT volumes. The challenge in CAD for urinary stones lies in the similarity in shape and intensity of stones with non-stone structures and how to efficiently deal with large high-resolution CT volumes. We address these challenges by using a Convolutional Neural Network (CNN) that works directly on the high resolution CT volumes. The method is evaluated on a large data base of 465 clinically acquired high-resolution CT volumes of the urinary tract with labeling of ureteral stones performed by a radiologist. The best model using 2.5D input data and anatomical information achieved a sensitivity of 100% and an average of 2.68 false-positives per patient on a test set of 88 scans.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Computer aided detection, Ureteral stone, Convolutional neural networks, Computed tomography, Training set selection, False positive reduction
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:oru:diva-67139 (URN)10.1016/j.compbiomed.2018.04.021 (DOI)000435623700015 ()29730498 (PubMedID)2-s2.0-85046800526 (Scopus ID)
Note

Funding Agencies:

Nyckelfonden  OLL-597511 

Vinnova under the project "Interactive Deep Learning for 3D image analysis"  

Available from: 2018-06-04 Created: 2018-06-04 Last updated: 2018-08-30Bibliographically approved
Lidén, M., Jendeberg, J., Längkvist, M., Loutfi, A. & Thunberg, P. (2018). Discrimination between distal ureteral stones and pelvic phleboliths in CT using a deep neural network: more than local features needed. In: : . Paper presented at European Congress of Radiology (ECR) 2018, Vienna, Austria, 28 Feb.-4 Mar., 2018.
Open this publication in new window or tab >>Discrimination between distal ureteral stones and pelvic phleboliths in CT using a deep neural network: more than local features needed
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2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Purpose: To develop a deep learning method for assisting radiologists in the discrimination between distal ureteral stones and pelvic phleboliths in thin slice CT images, and to evaluate whether this differentiation is possible using only local features.

Methods and materials: A limited field-of-view image data bank was retrospectively created, consisting of 5x5x5 cm selections from 1 mm thick unenhanced CT images centered around 218 pelvis phleboliths and 267 distal ureteral stones in 336 patients. 50 stones and 50 phleboliths formed a validation cohort and the remainder a training cohort. Ground truth was established by a radiologist using the complete CT examination during inclusion.The limited field-of-view CT stacks were independently reviewed and classified as containing a distal ureteral stone or a phlebolith by seven radiologists. Each cropped stack consisted of 50 slices (5x5 cm field-of-view) and was displayed in a standard PACS reading environment. A convolutional neural network using three perpendicular images (2.5D-CNN) from the limited field-of-view CT stacks was trained for classification.

Results: The 2.5D-CNN obtained 89% accuracy (95% confidence interval 81%-94%) for the classification in the unseen validation cohort while the accuracy of radiologists reviewing the same cohort was 86% (range 76%-91%). There was no statistically significant difference between 2.5D-CNN and radiologists.

Conclusion: The 2.5D-CNN achieved radiologist level classification accuracy between distal ureteral stones and pelvic phleboliths when only using the local features. The mean accuracy of 86% for radiologists using limited field-of-view indicates that distant anatomical information that helps identifying the ureter’s course is needed.

National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:oru:diva-67372 (URN)
Conference
European Congress of Radiology (ECR) 2018, Vienna, Austria, 28 Feb.-4 Mar., 2018
Available from: 2018-06-20 Created: 2018-06-20 Last updated: 2018-06-20Bibliographically approved
Jendeberg, J., Geijer, H., Alshamari, M. & Lidén, M. (2018). Prediction of spontaneous ureteral stone passage: Automated 3D-measurements perform equal to radiologists, and linear measurements equal to volumetric. European Radiology, 28(6), 2474-2483
Open this publication in new window or tab >>Prediction of spontaneous ureteral stone passage: Automated 3D-measurements perform equal to radiologists, and linear measurements equal to volumetric
2018 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 28, no 6, p. 2474-2483Article in journal (Refereed) Published
Abstract [en]

OBJECTIVES: To compare the ability of different size estimates to predict spontaneous passage of ureteral stones using a 3D-segmentation and to investigate the impact of manual measurement variability on the prediction of stone passage.

METHODS: We retrospectively included 391 consecutive patients with ureteral stones on non-contrast-enhanced CT (NECT). Three-dimensional segmentation size estimates were compared to the mean of three radiologists' measurements. Receiver-operating characteristic (ROC) analysis was performed for the prediction of spontaneous passage for each estimate. The difference in predicted passage probability between the manual estimates in upper and lower stones was compared.

RESULTS: The area under the ROC curve (AUC) for the measurements ranged from 0.88 to 0.90. Between the automated 3D algorithm and the manual measurements the 95% limits of agreement were 0.2 ± 1.4 mm for the width. The manual bone window measurements resulted in a > 20 percentage point (ppt) difference between the readers in the predicted passage probability in 44% of the upper and 6% of the lower ureteral stones.

CONCLUSIONS: All automated 3D algorithm size estimates independently predicted the spontaneous stone passage with similar high accuracy as the mean of three readers' manual linear measurements. Manual size estimation of upper stones showed large inter-reader variations for spontaneous passage prediction.

KEY POINTS:• An automated 3D technique predicts spontaneous stone passage with high accuracy.• Linear, areal and volumetric measurements performed similarly in predicting stone passage.• Reader variability has a large impact on the predicted prognosis for stone passage.

Place, publisher, year, edition, pages
Springer, 2018
Keywords
Computed tomography, Ureteral calculi, Kidney stone, Ureter, Renal colic
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:oru:diva-64712 (URN)10.1007/s00330-017-5242-9 (DOI)000431653200024 ()29368161 (PubMedID)
Note

Funding Agency

Research Committee of Region Orebro County 

Available from: 2018-02-02 Created: 2018-02-02 Last updated: 2018-08-20Bibliographically approved
Lidén, M., Wodecki, M., Thunberg, P. & Rask, P. (2017). Impact of Heart Rate on Flow Measurements in Aortic Regurgitation. Journal of Heart Valve Disease, 26(5), 502-508, Article ID 4562.
Open this publication in new window or tab >>Impact of Heart Rate on Flow Measurements in Aortic Regurgitation
2017 (English)In: Journal of Heart Valve Disease, ISSN 0966-8519, E-ISSN 2053-2644, Vol. 26, no 5, p. 502-508, article id 4562Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Flow measurements using cardiac magnetic resonance imaging (CMRI) enable quantification of the stroke volume, regurgitant volume (RV) and regurgitant fraction (RF) in patients with aortic regurgitation (AR). These variables are used to assess the severity of the valve disease and for the timing of surgery. The aim of the study was to investigate the impact of an increased heart rate on measurement of the RV and RF in patients with AR.

METHODS: Among 13 patients with known moderate or severe AR, regurgitant flow measurements, using phase-contrast cine magnetic resonance imaging, were obtained in the ascending aorta. Flow measurements were obtained at rest and at increased heart rates after intravenous administration of atropine.

RESULTS: The mean heart rate was 61 beats per min at rest and 91 beats per min after atropine administration. The RV and RF were 52 ml and 35% at rest, respectively, and 34 ml (p <0.001) and 30% (p = 0.065) at increased heart rate, respectively.

CONCLUSIONS: An increased heart rate leads to a decreased RV. The RF is more stable and may therefore be preferable for severity grading in AR.

Place, publisher, year, edition, pages
I C R Publishers Ltd., 2017
National Category
Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:oru:diva-67603 (URN)29762918 (PubMedID)
Available from: 2018-06-28 Created: 2018-06-28 Last updated: 2019-03-26Bibliographically approved
Alshamari, M., Geijer, M., Norrman, E., Lidén, M., Krauss, W., Jendeberg, J., . . . Geijer, H. (2017). Impact of iterative reconstruction on image quality of low-dose CT of the lumbar spine. Acta Radiologica, 58(6), 702-709
Open this publication in new window or tab >>Impact of iterative reconstruction on image quality of low-dose CT of the lumbar spine
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2017 (English)In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 58, no 6, p. 702-709Article in journal (Refereed) Published
Abstract [en]

Background: Iterative reconstruction (IR) is a recent reconstruction algorithm for computed tomography (CT) that can be used instead of the standard algorithm, filtered back projection (FBP), to reduce radiation dose and/or improve image quality.

Purpose: To evaluate and compare the image quality of low-dose CT of the lumbar spine reconstructed with IR to conventional FBP, without further reduction of radiation dose.

Material and Methods: Low-dose CT on 55 patients was performed on a Siemens scanner using 120 kV tube voltage, 30 reference mAs, and automatic dose modulation. From raw CT data, lumbar spine CT images were reconstructed with a medium filter (B41f) using FBP and four levels of IR (levels 2-5). Five reviewers scored all images on seven image quality criteria according to the European guidelines on quality criteria for CT, using a five-grade scale. A side-by-side comparison was also performed.

Results: There was significant improvement in image quality for IR (levels 2-4) compared to FBP. According to visual grading regression, odds ratios of all criteria with 95% confidence intervals for IR2, IR3, IR4, and IR5 were: 1.59 (1.39-1.83), 1.74 (1.51-1.99), 1.68 (1.46-1.93), and 1.08 (0.94-1.23), respectively. In the side-by-side comparison of all reconstructions, images with IR (levels 2-4) received the highest scores. The mean overall CTDIvol was 1.70 mGy (SD 0.46; range, 1.01-3.83 mGy). Image noise decreased in a linear fashion with increased strength of IR.

Conclusion: Iterative reconstruction at levels 2, 3, and 4 improves image quality of low-dose CT of the lumbar spine compared to FPB.

Place, publisher, year, edition, pages
London: Sage Publications, 2017
Keywords
X-ray computed tomography (CT), image manipulation/reconstruction, lumbar vertebrae, radiation dosage, spine
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:oru:diva-57646 (URN)10.1177/0284185116669870 (DOI)000399995700011 ()28157395 (PubMedID)2-s2.0-85019010032 (Scopus ID)
Available from: 2017-05-12 Created: 2017-05-12 Last updated: 2019-03-26Bibliographically approved
Jorstig, S., Waldenborg, M., Lidén, M. & Thunberg, P. (2017). Right ventricular ejection fraction measurements using two-dimensional transthoracic echocardiography by applying an ellipsoid model. Cardiovascular Ultrasound, 15, Article ID 4.
Open this publication in new window or tab >>Right ventricular ejection fraction measurements using two-dimensional transthoracic echocardiography by applying an ellipsoid model
2017 (English)In: Cardiovascular Ultrasound, ISSN 1476-7120, E-ISSN 1476-7120, Vol. 15, article id 4Article in journal (Refereed) Published
Abstract [en]

Background: There is today no established approach to estimate right ventricular ejection fraction (RVEF) using 2D transthoracic echocardiography (TTE). The aim of this study was to evaluate a new method for RVEF calculations using 2D TTE and compare the results with cardiac magnetic resonance (CMR) imaging and tricuspid annular plane systolic excursion (TAPSE).

Methods: A total of 37 subjects, 25 retrospectively included patients and twelve healthy volunteers, were included to give a wide range of RVEF. The right ventricle (RV) was modeled as a part of an ellipsoid enabling calculation of the RV volume by combining three distance measurements. RVEF calculated according to the model, RVEFTTE, were compared with reference CMR-derived RVEF, RVEFCMR. Further, TAPSE was measured in the TTE images and the correlations were calculated between RVEFTTE, TAPSE and RVEFCMR.

Results: The mean values were RVEFCMR = 43 +/- 12% (range 20-66%) and RVEFTTE = 50 +/- 9% (range 34-65%). There was a high correlation (r = 0.80, p < 0.001) between RVEFTTE and RVEFCMR. Bland-Altman analysis showed a mean difference between RVEFCMR and RVEFTTE of 6 percentage points (ppt) with limits of agreement from -11 to 23 ppt. The mean value for TAPSE was 19 +/- 5 mm and the correlation between TAPSE and RVEFCMR was moderate (r = 0.54, p < 0.001). The correlation between RVEFTTE and RVEFCMR was significantly higher (p < 0.05) than the correlation between TAPSE and RVEFCMR.

Conclusions: The ellipsoid model shows promise for RVEF calculations using 2D TTE for a wide range of RVEF, providing RVEF estimates that were significantly better correlated to RVEF obtained from CMR compared to TAPSE.

Place, publisher, year, edition, pages
BioMed Central, 2017
Keywords
Right ventricle, Right ventricular function, Echocardiography, Cardiac magnetic resonance imaging
National Category
Cardiac and Cardiovascular Systems
Research subject
Cardiology
Identifiers
urn:nbn:se:oru:diva-57065 (URN)10.1186/s12947-017-0096-5 (DOI)000396781100001 ()28270161 (PubMedID)2-s2.0-85014670050 (Scopus ID)
Note

Funding Agency:

Research Committee of Region Orebro County  OLL-573211

Available from: 2017-04-18 Created: 2017-04-18 Last updated: 2019-03-26Bibliographically approved
Jendeberg, J., Geijer, H., Alshamari, M., Cierzniak, B. & Lidén, M. (2017). Size matters: The width and location of a ureteral stone accurately predict the chance of spontaneous passage. European Radiology, 27(11), 4775-4785
Open this publication in new window or tab >>Size matters: The width and location of a ureteral stone accurately predict the chance of spontaneous passage
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2017 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 27, no 11, p. 4775-4785Article in journal (Refereed) Published
Abstract [en]

OBJECTIVES: To determine how to most accurately predict the chance of spontaneous passage of a ureteral stone using information in the diagnostic non-enhanced computed tomography (NECT) and to create predictive models with smaller stone size intervals than previously possible.

METHODS: Retrospectively 392 consecutive patients with ureteric stone on NECT were included. Three radiologists independently measured the stone size. Stone location, side, hydronephrosis, CRP, medical expulsion therapy (MET) and all follow-up radiology until stone expulsion or 26 weeks were recorded. Logistic regressions were performed with spontaneous stone passage in 4 weeks and 20 weeks as the dependent variable.

RESULTS: The spontaneous passage rate in 20 weeks was 312 out of 392 stones, 98% in 0-2 mm, 98% in 3 mm, 81% in 4 mm, 65% in 5 mm, 33% in 6 mm and 9% in ≥6.5 mm wide stones. The stone size and location predicted spontaneous ureteric stone passage. The side and the grade of hydronephrosis only predicted stone passage in specific subgroups.

CONCLUSION: Spontaneous passage of a ureteral stone can be predicted with high accuracy with the information available in the NECT. We present a prediction method based on stone size and location.

KEY POINTS: • Non-enhanced computed tomography can predict the outcome of ureteral stones. • Stone size and location are the most important predictors of spontaneous passage. • Prediction models based on stone width or length and stone location are introduced. • The observed passage rates for stone size in mm-intervals are reported. • Clinicians can make better decisions about treatment.

Place, publisher, year, edition, pages
Springer, 2017
Keywords
Spiral computed tomography; Ureteral calculi; Kidney stone; Ureter; Renal colic
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:oru:diva-61961 (URN)10.1007/s00330-017-4852-6 (DOI)000412820500037 ()28593428 (PubMedID)2-s2.0-85020305726 (Scopus ID)
Note

Funding Agency:

Research Committee of Region Örebro County

Available from: 2017-10-26 Created: 2017-10-26 Last updated: 2018-08-07Bibliographically approved
Hellstrandh Jorstig, S., Waldenborg, M., Lidén, M., Wodecki, M. & Thunberg, P. (2016). Determination of Right Ventricular Volume by Combining Echocardiographic Distance Measurements. Echocardiography, 33(6), 844-853
Open this publication in new window or tab >>Determination of Right Ventricular Volume by Combining Echocardiographic Distance Measurements
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2016 (English)In: Echocardiography, ISSN 0742-2822, E-ISSN 1540-8175, Vol. 33, no 6, p. 844-853Article in journal (Refereed) Published
Abstract [en]

Background: The position of the right ventricle (RV), often partly behind the sternum, implies difficulties to image the RV free wall using transthoracic echocardiography (TTE) and consequently limits the possibilities of stroke volume calculations. The aim of this study was to evaluate whether the volume of the right ventricle (RV) can be determined by combining TTE distance measurements that do not need the RV free wall to be fully visualized.

Methods: The RV volume was approximated by an ellipsoid composed of three distances. Distance measurements, modeled RV stroke volumes (RVSV), and RV ejection fraction (RVEF) were compared to reference values obtained from cardiac magnetic resonance (CMR) imaging for 12 healthy volunteers.

Results: Inter-modality comparisons showed that distance measurements were significantly underestimated in TTE compared to CMR. The modeled RV volumes using TTE distance measurements were underestimated compared to reference CMR volumes. There was, however, for TTE an agreement between modeled RVSV and left ventricular stroke volumes determined by biplane Simpson's rule. Similar agreement was shown between modeled RVSV based on CMR distance measurements and the CMR reference. Regarding RVEF, further studies including patients with a wider range of RVEF are needed to evaluate the method.

Conclusion: In conclusion, the ellipsoid model of the RV provides good estimates of RVSVs, but volumes based on distance measurements from different modalities cannot be used interchangeably.

Place, publisher, year, edition, pages
Hoboken, USA: Wiley-Blackwell Publishing Inc., 2016
Keywords
Right ventricle, right ventricular volume, ejection fraction, echoc ardiography, cardiac magnetic resonance imaging
National Category
Cardiac and Cardiovascular Systems
Research subject
Cardiology
Identifiers
urn:nbn:se:oru:diva-50370 (URN)10.1111/echo.13173 (DOI)000379944600005 ()26841195 (PubMedID)2-s2.0-84975297303 (Scopus ID)
Note

Funding Agency:

Örebro County Council

Available from: 2016-05-23 Created: 2016-05-23 Last updated: 2019-03-26Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-1346-1450

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