Partner: Piotr Kalinowski |
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Recent publications
1. | Byra M., Szmigielski C.♦, Kalinowski P.♦, Paluszkiewicz R.♦, Ziarkiewicz-Wróblewska B.♦, Zieniewicz K.♦, Styczyński G.♦, Ultrasound and biomarker based assessment of hepatic steatosis in patients with severe obesity, POLISH ARCHIVES OF INTERNAL MEDICINE, ISSN: 1897-9483, DOI: 10.20452/pamw.16343, Vol.1, pp.1-23, 2022 Abstract: Introduction: Nonalcoholic fatty liver disease (NAFLD) is a common liver abnormality, but its non-invasive diagnosis in patients with severe obesity remains difficult. biomarkers, fatty liver disease, hepatorenal index, obesity, ultrasound Affiliations:
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2. | Strzelczyk J.♦, Kalinowski P.♦, Zieniewicz K.♦, Szmigielski C.♦, Byra M., Styczyński G.♦, The influence of surgical weight reduction on left atrial strain, Obesity Surgery, ISSN: 0960-8923, DOI: 10.1007/s11695-021-05710-5, Vol.31, pp.5243-5250, 2021 Abstract: Background: Obesity increases and surgical weight reduction decreases the risk of atrial fibrillation (AF) and heart failure (HF). We hypothesized that surgically induced weight loss may favorably affect left atrial (LA) mechanical function measured by longitudinal strain, which has recently emerged as an independent imaging biomarker of increased AF and HF risk. Methods: We retrospectively evaluated echocardiograms performed before and 12.2 ± 2.2 months after bariatric surgery in 65 patients with severe obesity (mean age 39 [36; 47] years, 72% of females) with no known cardiac disease or arrhythmia. The LA mechanical function was measured by the longitudinal strain using the semi-automatic speckle tracking method. Results: After surgery, body mass index decreased from 43.72 ± 4.34 to 30.04 ± 4.33 kg/m2. We observed a significant improvement in all components of the LA strain. LA reservoir strain (LASR) and LA conduit strain (LASCD) significantly increased (35.7% vs 38.95%, p = 0.0005 and − 19.6% vs − 24.4%, p < 0.0001) and LA contraction strain (LASCT) significantly decreased (− 16% vs − 14%, p = 0.0075). There was a significant correlation between an increase in LASR and LASCD and the improvement in parameters of left ventricular diastolic and longitudinal systolic function (increase in E’ and MAPSE). Another significant correlation was identified between the decrease in LASCT and an improvement in LA function (decrease in A’). Conclusions: The left atrial mechanical function improves after bariatric surgery. It is partially explained by the beneficial effect of weight reduction on the left ventricular diastolic and longitudinal systolic function. This effect may contribute to decreased risk of AF and HF after bariatric surgery. Keywords:left atrial strain, bariatric surgery, atrial fibrillation, heart failure Affiliations:
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3. | Byra M., Styczyński G.♦, Szmigielski C.♦, Kalinowski P.♦, Michałowski Ł.♦, Paluszkiewicz R.♦, Ziarkiewicz-Wróblewska B.♦, Zieniewicz K.♦, Sobieraj P.♦, Nowicki A., Transfer learning with deep convolutiona lneural network for liver steatosis assessment in ultrasound images, International Journal of Computer Assisted Radiology and Surgery, ISSN: 1861-6410, DOI: 10.1007/s11548-018-1843-2, Vol.13, No.12, pp.1895-1903, 2018 Abstract: Purpose Nonalcoholic fatty, liver disease, Ultrasound imaging Deep learning, Convolutional neural networks, Hepatorenal index, Transfer learning Affiliations:
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Conference papers
1. | Byra M., Styczyński G.♦, Szmigielski C.♦, Kalinowski P.♦, Michałowski Ł.♦, Paluszkiewicz R.♦, Ziarkiewicz-Wróblewska B.♦, Zieniewicz K.♦, Nowicki A., Adversarial attacks on deep learning models for fatty liver disease classification by modification of ultrasound image reconstruction method, IUS 2020, IEEE International Ultrasonics Symposium, 2020-09-07/09-11, Las Vegas (US), DOI: 10.1109/IUS46767.2020.9251568, pp.1-4, 2020 Abstract: Convolutional neural networks (CNNs) have achieved remarkable success in medical image analysis tasks. In ultrasound (US) imaging, CNNs have been applied to object classification, image reconstruction and tissue characterization. However, CNNs can be vulnerable to adversarial attacks, even small perturbations applied to input data may significantly affect model performance and result in wrong output. In this work, we devise a novel adversarial attack, specific to ultrasound (US) imaging. US images are reconstructed based on radio-frequency signals. Since the appearance of US images depends on the applied image reconstruction method, we explore the possibility of fooling deep learning model by perturbing US B-mode image reconstruction method. We apply zeroth order optimization to find small perturbations of image reconstruction parameters, related to attenuation compensation and amplitude compression, which can result in wrong output. We illustrate our approach using a deep learning model developed for fatty liver disease diagnosis, where the proposed adversarial attack achieved success rate of 48%. Keywords:adversarial attacks, deep learning, fatty liver, transfer learning, ultrasound imaging Affiliations:
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