The use of extracorporeal shock wave therapy for the treatment of bone marrow oedema — a systematic review and meta-analysis

Background Extracorporeal shock wave therapy (ESWT) has been used for various pathologies associated with bone marrow oedema (BME). However, it is still not clear whether ESWT may be favourable in the treatment of BME. Therefore, the aim of this systematic review was to assess the efficacy of ESWT for the treatment of BME. Methods MEDLINE was searched for relevant literature with no time constraints. Both randomized and non-randomized trials were included. Case reports and conference abstracts were excluded. Titles and abstracts were screened and full-text articles of included studies were retrieved. Data on the effect of ESWT on pain, function, and the BME area on magnet resonance imaging were extracted. Results Pain, function, and magnet resonance imaging results all improved across the studies — regardless of whether it was a randomized or non-randomized study. This effect was consistent across multiple pathologies such as osteonecrosis of the femoral head, BME associated with knee osteoarthritis, Kienböck’s disease, and osteitis pubis. The meta-analysis showed that pain (after 1 month: weighted mean difference (WMD) = − 2.23, 95% CI − 2.58 to − 1.88, P < 0.0001; after 3–6 month: WMD = − 1.72, 95% CI − 2.52 to − 0.92, P < 0.00001) and function (after 1 month: WMD = − 1.59, 95% CI − 2.04 to − 1.14, P < 0.0001; after 3–6 month: WMD = − 2.06, 95% CI − 3.16 to − 0.96, P = 0.0002; after ≥ 12 month: WMD = − 1.20, 95% CI − 1.83 to − 0.56, P = 0.0002) was reduced in terms of ESWT treatment compared to a control group. Conclusions Based on the available evidence, ESWT may be an adequate option for conservative therapy in pathologies involving BME. Trial registration PROSPERO, CRD42021201719. Registered 23 December 2020

Impact of qualitative, semi-quantitative, and quantitative analyses of dynamic contrast-enhanced magnet resonance imaging on prostate cancer detection

Dynamic contrast enhanced imaging (DCE) as an integral part of multiparametric prostate magnet resonance imaging (mpMRI) can be evaluated using qualitative, semi-quantitative, or quantitative assessment methods. Aim of this study is to analyze the clinical benefits of these evaluations of DCE regarding clinically significant prostate cancer (csPCa) detection and grading. 209 DCE data sets of 103 consecutive patients with mpMRI (T2, DWI, and DCE) and subsequent MRI-(in-bore)-biopsy were retrospectively analyzed. Qualitative DCE evaluation according to PI-RADS v2.1, semi-quantitative (curve type; DCE score according to PI-RADS v1), and quantitative Tofts analyses (Ktrans, kep, and ve) as well as PI-RADS v1 and v2.1 overall classification of 209 lesions (92 PCa, 117 benign lesions) were performed. Of each DCE assessment method, cancer detection, discrimination of csPCa, and localization were assessed and compared to histopathology findings. All DCE analyses (p<0.01–0.05), except ve (p = 0.02), showed significantly different results for PCa and benign lesions in the peripheral zone (PZ) with area under the curve (AUC) values of up to 0.92 for PI-RADS v2.1 overall classification. In the transition zone (TZ) only the qualitative DCE evalulation within PI-RADS (v1 and v2.1) could distinguish between PCa and benign lesions (p<0.01; AUC = 0.95). None of the DCE parameters could differentiate csPCa from non-significant (ns) PCa (p ≥ 0.1). Qualitative analysis of DCE within mpMRI according to PI-RADS version 2.1 showed excellent results regarding (cs)PCa detection. Semi-quantitative and quantitative parameters provided no additional improvements. DCE alone wasn’t able to discriminate csPCa from nsPCa.

Evaluation of Biomedical Imaging in Deep Neural Networks

Whereas the historical background of medical field started in 1895 with Roentgen Wilhelm participating in the first x-rays photograph and proceeded through 1913 with the discovery of mammogram and 1927 with first cerebellar echocardiogram, advanced medicine tomography came into focus in the 1950s with the discovery of PET and ultrasonic image processing. The first computed tomography (CT) scanners was created by Hounsfield Godfrey and CoreMark Allanin 1972, while the first commercialized Magnet Resonance Imaging (MRI) scanners were produced by Raymond Dalmatian in 1977. The creation of general methods and terminology of digitized signal and image processing occurred in tandem with the growth of medical imaging technology in the 1970s and beyond, as well as the advent of digital processors. In an examination of biological applications and analysis in the era of big data and deep learning, this article analyzes background and phraseology: Pattern Classification, Artificial Intelligence, Machine Learning, Big Data.

Historical development of estimated fetal weight calculation

Accurate calculation of the estimated fetal weight is necessary for the choice of a correct approach to management of labour. Th e existing methods are not universal and require complex application. Th is article presents a review of literatures published in PubMed and Google Scholar databases in 1955-2021 and devoted to historical aspects in development of the existing clinical and instrumental approaches to calculation of estimated fetal weight. The paper presents existing methods for calculation of estimated fetal weight at diff erent gestational ages as well as methods making it possible to predict fetal weight before gestation onset. Data on their informative value during the third trimester and alterations in their accuracy depending on the pregnant patient’s BMI are presented. Th e topic of application of magnet-resonance imaging for fetometry is considered with comparison of this approach to a more common method of ultrasonography.

Towards Analyzing the Influence of Measurement Errors in Magnetic Resonance Imaging of Fluid Flows

Magnet resonance imaging does not only have a large number of applications in the field of medical examinations. In addition, several promising applications were also reported for the measurement of technical fluid flows and for the measurement of temperature fields in technical devices which do not allow for a classical access by either arrays of flow meters on the one hand or by arrays of temperature sensors such as thermocouples on the other hand. Due to the fact that magnet resonance imaging can be performed in a non-invasive manner, it has the advantage to provide relevant data without disturbing the velocity and temperature fields by external sensor devices. Moreover, measurement information can also be obtained for scenarios in which a direct access to the media under investigation is hardly possible due to constructive limitations. To make this kind of measurement applicable also for dynamic scenarios, not only the spatial resolution but also the temporal one needs to be sufficiently accurate. If the temporal resolution is of interest, an acceleration of the measurement process becomes possible by compressed sensing techniques which make use of an undersampling of the so-called $k$-space. However, such compressed sensing approaches require a reconstruction of the original fields of the physical variables to be measured. In this paper, it is shown how interval arithmetic approaches can be employed to solve the necessary optimality criteria for the fluid velocity reconstruction under the assumption of bounded measurement errors.