Dynamic Magnetic Resonance Imaging Research Articles

SPINNED: Simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast MRI perfusion data.

To propose the simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast (DSC) MRI (SPINNED) as an alternative for more robust and accurate deconvolution compared to existing methods. The SPINNED method was developed by generating synthetic tissue residue functions and arterial input functions through mathematical simulations and by using them to create synthetic DSC MRI time series. The SPINNED model was trained using these simulated data to learn the underlying physical relation (deconvolution) between the DSC-MRI time series and the arterial input functions. The accuracy and robustness of the proposed SPINNED method were assessed by comparing it with two common deconvolution methods in DSC MRI data analysis, circulant singular value decomposition, and Volterra singular value decomposition, using both simulation data and real patient data. The proposed SPINNED method was more accurate than the conventional methods across all SNR levels and showed better robustness against noise in both simulation and real patient data. The SPINNED method also showed much faster processing speed than the conventional methods. These results support that the proposed SPINNED method can be a good alternative to the existing methods for resolving the deconvolution problem in DSC MRI. The proposed method does not require any separate ground-truth measurement for training and offers additional benefits of quick processing time and coverage of diverse clinical scenarios. Consequently, it will contribute to more reliable, accurate, and rapid diagnoses in clinical applications compared with the previous methods including those based on supervised learning.

Pathophysiologic Mapping of Chronic Liver Diseases With Longitudinal Multiparametric MRI in Animal Models.

Chronic liver diseases (CLDs) have diverse etiologies. To better classify CLDs, we explored the ability of longitudinal multiparametric MRI (magnetic resonance imaging) in depicting alterations in liver morphology, inflammation, and hepatocyte and macrophage activity in murine high-fat diet (HFD)- and carbon tetrachloride (CCl 4 )-induced CLD models. Mice were either untreated, fed an HFD for 24 weeks, or injected with CCl 4 for 8 weeks. Longitudinal multiparametric MRI was performed every 4 weeks using a 7 T MRI scanner, including T1/T2 relaxometry, morphological T1/T2-weighted imaging, and fat-selective imaging. Diffusion-weighted imaging was applied to assess fibrotic remodeling and T1-weighted and T2*-weighted dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI using gadoxetic acid and ferucarbotran to target hepatocytes and the mononuclear phagocyte system, respectively. Imaging data were associated with histopathological and serological analyses. Principal component analysis and clustering were used to reveal underlying disease patterns. The MRI parameters significantly correlated with histologically confirmed steatosis, fibrosis, and liver damage, with varying importance. No single MRI parameter exclusively correlated with 1 pathophysiological feature, underscoring the necessity for using parameter patterns. Clustering revealed early-stage, model-specific patterns. Although the HFD model exhibited pronounced liver fat content and fibrosis, the CCl 4 model indicated reduced liver fat content and impaired hepatocyte and macrophage function. In both models, MRI biomarkers of inflammation were elevated. Multiparametric MRI patterns can be assigned to pathophysiological processes and used for murine CLD classification and progression tracking. These MRI biomarker patterns can directly be explored clinically to improve early CLD detection and differentiation and to refine treatments.

Evaluation of Cervical Vertebral Motion and Foraminal Changes During the Spurling Test Using Zero Echo Time Magnetic Resonance Imaging and Computed Tomography-Based Micromotion Analysis.

Clinical experimental diagnostic study. The objective of the study was to investigate cervical spine dynamics including changes in the cervical foramina in patients experiencing intermittent arm radiculopathy. Cervical foraminal stenosis is a frequent cause of radicular arm pain. The Spurling test, while specific, lacks the precision to identify symptomatic nerve roots. The relationship among vertebral motion, foraminal changes, and radiculopathy during a Spurling test remains underexplored. Ten patients with positive Spurling tests and magnetic resonance imaging (MRI) confirmed 1 or 2-level cervical foraminal stenosis were scanned using the Dynamic MRI Compression System enabling a simulated Spurling test inside the MRI gantry of a 3T MRI scanner with a dedicated neck coil. First, a relaxed image acquisition was undertaken, followed by slowly applying the Spurling test until the patient reported aggravation of radiculopathy or discomfort, where the next image series was taken. Zero echo time MRI was employed to obtain computed tomography (CT)-like images. The images were thereafter analyzed using the Sectra® CT-based Micromotion Analysis software for motion analysis. The C4/C5 level exhibited the most significant movements both in translation and rotation, with less movements observed in C5 to C6 and C6 to C7 levels. No uniform pattern emerged that differentiated suspected stenotic levels from nonsuspected levels. Despite relatively small vertebral movements, 9/10 of patients reported arm pain during provocation, indicating extremely narrow margins of tolerance. This study demonstrates the utility of zero echo time MRI and CT-based Micromotion Analysis in detecting subtle yet clinically relevant vertebral motions influencing the foramina in the cervical spine during the Spurling maneuver. These findings could lead to a better understanding and potentially improved diagnostic strategies for cervical foraminal stenosis, although further research with a larger cohort is necessary to confirm these results.

Validation of Dynamic 3D MRI for Urodynamics Assessment Using an Anatomically Realistic In Vitro Model of the Bladder.

Lowery urinary tract symptoms (LUTS) affect a large majority of the aging population. 3D Dynamic MRI shows promise as a noninvasive diagnostic tool that can assess bladder anatomy and function (urodynamics) while overcoming challenges associated with current urodynamic assessment methods. However, validation of this technique remains an unmet need. In this study, an anatomically realistic, bladder-mimicking in vitro flow model was created and used to systematically benchmark 3D dynamic MRI performance using a highly controllable syringe pump. Time-resolved volumes of the synthetic bladder model were obtained during simulated filling and voiding events and used to calculate volumetric flowrate. During MRI acquisitions, pressure during each event was recorded and used to create PV loops for work assessment. Error between control and MRI-derived volume for voiding and filling events exhibited 3.36% and 4.66% differences, respectively. A slight increase in average error was observed for MRI-derived flowrate when compared to the control flowrate (4.90% and 7.67% for voiding and filling, respectively). Overall, average error in segmented volumes increased with decreasing volume flowrate. Pressure drops were observed during voiding. Pressure increased during filling. Enhanced validation of novel 3D MRI urodynamics is achieved by using high-resolution PIV for visualizing and quantifying velocity inside the bladder model, which is not currently possible with 3D Dynamic MRI.

Formant indicators of «velarization». Part I

This article discusses the problem of determining velarization from acoustic data and its relationship to articulation. The aim of the study is to identify the range of formants by which «velarization» can be determined, as well as to determine the location of the highest point of localization of the part of the back of the tongue of the relative palatine arch with this articulation, modeling the sound quality of a specific consonantal sound type. In the course of the study, the methods used at the V.M. Nadelyaev LFEI of the sector of languages of the peoples of Siberia of the IFL SB RAS (Novosibirsk), as well as in the LEFI of the Department of Foreign Languages of the AmSU (Blagoveshchensk). The object of the study is dynamic speech. The subject of the study is «velarization» in languages of different families. The material for the analysis was static and dynamic MRI scans and audio recordings recorded at different times by employees (including the author of this work) of the V.M. Nadelyaev LEFI, made on time and after tomography from the appropriate media. Scientific novelty and theoretical significance of the study: the correlation between F2 , articulation and auditory perception of amplifying articulation of hardness – “velarization” is presented for the first time. The materials and results of the research can be used to develop textbooks on general phonetics, at seminars on dynamic speech analysis, and when writing scientific articles on experimental phonetics. The main conclusions presented in this paper are: 1) the acoustic effect of “velarization” is achieved not only as a result of lifting the back of the tongue to the soft palate not in guttural consonants (velarization), but also between the last third of the second half of the hard palate (prevelarization); 2) correlation analysis of somatic and acoustic material revealed the dependence of format indicators on a certain articulation; 3) a possible range of “velarization” in consonants has been identified – F2 = 1500 Hz – 550 Hz; 4) in the range from 1500 Hz to 1301 Hz, velarization sounds slightly “softer” by ear – a prevelarized consonant than from 1300 Hz to 550 Hz – a velarized consonant.

Grading of pelvic floor dysfunction on dynamic magnetic resonance imaging

Abstract Background: Pelvic floor disorders are often complex due to symptoms ranging from vague low back pain to major faecal incontinence and urinary incontinence. It is important to perform a dynamic study because certain abnormalities can be identified only during the straining or defaecation phase; for example, rectal prolapse or intussusception. Methods: This observational and descriptive study conducted over 18 months had included 50 patients (34 females). Cystocele was graded as mild, moderate and severe based on descent of urinary bladder below the pubococcygeal line (PCL). All of them underwent dynamic magnetic resonance imaging (MRI) of the pelvic floor. Uterine and vaginal vault prolapse was graded as mild, moderate and severe based on uterus, cervix and vaginal vault prolapse below the PCL line. Results: Their mean age was 52.4 (range 11-86) years. Cystocele was present in 59% of females and 19% of males. Urethral hypermobility seen in 6% females and 9% males. Conclusions: Dynamic MRI can be used as an important investigation before surgery to plan an appropriate surgical procedure based on grading of the pelvic organ prolapsed and involved compartment.

Dynamic contrast-enhanced MR imaging in identifying active anal fistula after surgery

BackgroundIt is challenging to identify residual or recurrent fistulas from the surgical region, while MR imaging is feasible. The aim was to use dynamic contrast-enhanced MR imaging (DCE-MRI) technology to distinguish between active anal fistula and postoperative healing (granulation) tissue.MethodsThirty-six patients following idiopathic anal fistula underwent DCE-MRI. Subjects were divided into Group I (active fistula) and Group IV (postoperative healing tissue), with the latter divided into Group II (≤ 75 days) and Group III (> 75 days) according to the 75-day interval from surgery to postoperative MRI reexamination. MRI classification and quantitative analysis were performed. Correlation between postoperative time intervals and parameters was analyzed. The difference of parameters between the four groups was analyzed, and diagnostic efficiency was tested by receiver operating characteristic curve.ResultsWash-in rate (WI) and peak enhancement intensity (PEI) were significantly higher in Group I than in Group II (p = 0.003, p = 0.040), while wash-out rate (WO), time to peak (TTP), and normalized signal intensity (NSI) were opposite (p = 0.031, p = 0.007, p = 0.010). Area under curves for discriminating active fistula from healing tissue within 75 days were 0.810 in WI, 0.708 in PEI, 0.719 in WO, 0.783 in TTP, 0.779 in NSI. All MRI parameters were significantly different between Group I and Group IV, but not between Group II and Group III, and not related to time intervals.ConclusionIn early postoperative period, DCE-MRI can be used to identify active anal fistula in the surgical area.Trial registrationChinese Clinical Trial Registry: ChiCTR2000033072.

Comparison between triphasic CT and dynamic MRI in assessment of tumor response in HCC patients after Transarterial chemoembolization

Comparison between triphasic CT and dynamic MRI in assessment of tumor response in HCC patients after Transarterial chemoembolization

The added value of diffusion-weighted imaging to dynamic MRI in detecting and characterizing hepatic focal lesions

Background Noninvasive diagnostic methods of hepatic lesions are often accomplished using contrast material-enhanced computed tomography and magnetic resonance imaging. Diffusion-weighted imaging (DWI) has evolved as a standard technique in liver imaging. Aim The work aimed to evaluate the added value of DWI to magnetic resonance imaging in identifying and characterizing hepatic focal lesions. Patients and methods In all, 100 participants having the clinical criteria of hepatic focal lesions detected on ultrasound or computed tomography screening were involved in our research. Dynamic magnetic resonance imaging of the liver and DWI were done. Results Correlation between the nature of lesions, magnetic resonance imaging findings, and comorbidity of liver cirrhosis show a highly statistically significant difference between benign and malignant hepatic focal lesions according to DWI and apparent diffusion coefficient (ADC) values. Receiver-operating characteristic curve analysis between the nature of lesions and lesions’ ADC value shows that at a cutoff value less than or equal to 1.5 (×10-3mm/s), with a sensitivity of 61.76% and specificity of 90.32%. It can predict malignant lesions with an area under the curve of 0.745 and a significant P value of less than 0.001. Conclusion DWI could identify malignant and benign hepatic tumors through ADC values producing high sensitivity and specificity; moreover, it is possible to identify subgroups of hepatic lesions depending on such values.

Assessment of cervical spondylosis by dynamic MRI and its advantages over routine MRI

Background and objectives. Cervical spondylosis is an age-related condition that influences the various components of the spine. Attributed to its exceptional tissue contrast, magnetic resonance imaging (MRI) is the preferred diagnostic modality for assessing cervical spondylosis. Dynamic MRI examination adds diagnostic information obtained from imaging the patient in flexion and extension. Our study had the purpose of evaluating the flexion-extension MRI’s diagnostic utility. Materials and methods. 40 patients with cervical spondylosis joined our prospective cross-sectional study. The patients were examined by flexion and extension sagittal T2 weighted images (Dynamic MRI) in addition to static MRI cervical spine protocol. The study was carried out in our department and lasted for two years. Results. Total central spinal stenosis (TCSS) was considerably higher in extension in comparison to neutral MRI (Mean ± SD =6.1± 1.45 compared to 4.7 ± 1.29) (p<0.001) showing that extension raises the severity of the cervical spinal stenosis. TCSS was significantly decreased in flexion compared to neutral MRI (Mean ± SD = 3.2 ± 0.79 compared to 4.7 ± 1.29) (p<0.001) assuming flexion reduces the radiological severity of stenosis. Conclusion. Dynamic MRI is a valuable imaging modality. It provides useful information by highlighting more central spinal stenosis, particularly in the extension position, which enhances the treatment regimens for patients with cervical spondylosis.

An estimation of the biomechanical properties of the continent and incontinent woman bladder via inverse finite element analysis.

Stress urinary incontinence often results from pelvic support structures' weakening or damage. This dysfunction is related to direct injury of the pelvic organ's muscular, ligamentous or connective tissue structures due to aging, vaginal delivery or increase of the intra-abdominal pressure, for example, defecation or due to obesity. Mechanical changes alter the soft tissues' microstructural composition and therefore may affect their biomechanical properties. This study focuses on adapting an inverse finite element analysis to estimate the in vivo bladder's biomechanical properties of two groups of women (continent group (G1) and incontinent group (G2)). These properties were estimated based on MRI, by comparing measurement of the bladder neck's displacements during dynamic MRI acquired in Valsalva maneuver with the results from inverse analysis. For G2, the intra-abdominal pressure was adjusted after applying a 95% impairment to the supporting structures. The material parameters were estimated for the two groups using the Ogden hyperelastic constitutive model. Finite element analysis results showed that the bladder tissue of women with stress urinary incontinence have the highest stiffness (α1 = 0.202 MPa and µ1 = 7.720 MPa) approximately 47% higher when compared to continent women. According to the bladder neck's supero-inferior displacement measured in the MRI, the intra-abdominal pressure values were adjusted for the G2, presenting a difference of 20% (4.0 kPa for G1 and 5.0 kPa for G2). The knowledge of the pelvic structures' biomechanical properties, through this non-invasive methodology, can be crucial in the choice of the synthetic mesh to treat dysfunction when considering personalized options.

Comparison of urethral parameters in females presenting cystoceles with and without stress urinary incontinence based on dynamic magnetic resonance imaging: are they different?

To compare urethral parameters between cystocele patients with and without stress urinary incontinence (SUI) and explore factors influencing SUI in cystocele patients via dynamic MRI. The two-dimensional parameters evaluated included the paravaginal defects, levator ani muscle defects, urethral length, urethral funnel shape, bladder neck funnel width, bladder neck funnel depth, urethral angle, posterior vesicourethral angle, and anterior bladder protrusion. The three-dimensional parameters included the proximal urethra rotation angle, the distal urethra rotation angle, bladder neck mobility, urethral midpoint mobility, and externalurethralmeatus mobility. The independent samples t test was used for continuous variables, and the chi-square test was used for categorical variables. Binary logistic regression was used to identify factors independently associated with SUI in cystocele patients. The baseline parameters were similar between the 2 groups. Cystocele patients with SUI had a significantly higher point Aa (1.63 ± 1.06cm vs. 0.81 ± 1.51cm, p = 0.008); more anterior bladder protrusion (33.3% vs. 11.4%, p = 0.017); greater bladder neck mobility (36.38 ± 11.46mm vs. 28.81 ± 11.72mm, p = 0.005); mid-urethral mobility (22.94 ± 6.50mm vs. 19.23 ± 6.65mm, p = 0.014); and external urethral meatus mobility (22.42 ± 8.16mm vs. 18.03 ± 8.51mm, p = 0.022) than did cystocele patients without SUI. The other urethral parameters were similar in the groups (p > 0.05). Binary logistic regression showed that bladder neck mobility was independently associated with SUI in females with cystoceles (odds ratio, 1.06; 95% CI 1.015-1.107; p = 0.009). Cystocele patients with SUI have a higher point Aa, more anterior bladder protrusion, and greater urethral mobility than those without SUI. Bladder neck mobility is independently associated with SUI in females with cystoceles. NCT03146195.

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. Prospective analysis of retrospectively acquired data. A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. 3 TECHNICAL EFFICACY: Stage 3.

Assessment of pelvic organ prolapse with the Pelvic Inclination Correction System: defining the normal range and threshold to pathology

PurposeTo define the normal range and threshold values for pathologic prolapse on MRI using the PICS line and assess its correlation with the pubococcygeal line (PCL).MethodsThis prospective, IRB-approved study included 20 nulliparous volunteers and 18 prolapse patients (POP-Q Stage ≥ 2). Organ positions (bladder, cervix, anorectal junction) relative to PICS and PCL were measured on dynamic MRI. Differences in organ position were compared. Receiver-operating characteristic (ROC) analysis was performed to identify cutoff values for prolapse using the PICS line. The correlation between PICS and PCL measurements was tested with Spearman’s rank correlation.ResultsIn volunteers, median bladder and cervix positions measured to the PICS at rest were − 2.7 cm and − 5.3 cm compared to − 1.9 cm and − 2.7 cm in patients (p < 0.001). During straining, bladder and cervix were at − 0.9 cm and − 3.2 cm in volunteers versus + 2.5 cm and + 2.5 cm in patients (p < 0.001). Correlation was strong for PICS and PCL measurements for all three compartments (δ = 0.883–0.970, p ≤ 0.001). AUCs of PICS for the anterior and middle compartment were 0.98 (95% confidence interval [CI] 0.96–1.00, p < 0.001) and 0.96 (95% CI 0.89–1.00, p < 0.001) for differentiating patients from healthy volunteers. AUC for the posterior compartment was 0.76 (95% CI 0.57–0.96, p = 0.034).ConclusionPICS measurements reliably differentiate patients from volunteers in the anterior and middle compartment. Future studies need to identify a reliable threshold for the posterior compartment. PICS and PCL measurements are strongly correlated.Graphical abstract

Dynamic Magnetic Resonance Imaging (MRI) in Inguinal-Related Chronic Groin Pain (CGP): Comparison With Systematic Surgical Assessment.

Objective This study aimed to assess the performance of dynamic MRI in Chronic Groin Pain (CGP) related to the inguinal region, comparing it with surgery as the gold standard. Materials and methods A cohort of 25 consecutive patients exhibiting persistent clinical inguinal-related CGP underwent a pre-surgical pelvis MRI. Imaging encompassed strictly axial Fast Spin Echo (FSE) T1 sequences, both without (static sequence) and with Valsalva Maneuver (VM, dynamic sequence), alongside axial-oblique Proton Density weighted with Fat Saturation (PDFS). Evaluation of these sequences focused on identifying Abdominal Wall (AW) injuries. A consistent surgical approach was employed by the same surgeon across all patients (34 AW injuries in 25 patients). Specificity (Sp), Sensitivity (Se), Negative Predictive Value (NPV), Positive Predictive Value (PPV), and overall accuracy of MRI sequences and their combinations for detecting AW injuries were computed by comparing them to surgical findings. Results Ninety sequences were obtained, revealing that the axial PDFS oblique sequence emerged as the most singularly reliable (Accuracy: 58.82%). The optimal sequence combination was found to be axial T1 combined with axial T1 VM, exhibiting an accuracy of 75.00% (Se: 85.71%, Sp: 70.59%, PPV: 54.55%, NPV: 92.31%, with an average duration of 4 minutes and 31 seconds). Conclusion Based on our findings, we advocate for the adoption of the axial FSE T1 combined with Valsalva Maneuver as a dependable protocol for inguinal-related CGP, characterized by a highly reasonable examination duration.

Challenges, limitations, and pitfalls of PET and advanced MRI in patients with brain tumors: A report of the PET/RANO group.

Brain tumor diagnostics have significantly evolved with the use of positron emission tomography (PET) and advanced magnetic resonance imaging (MRI) techniques. In addition to anatomical MRI, these modalities may provide valuable information for several clinical applications such as differential diagnosis, delineation of tumor extent, prognostication, differentiation between tumor relapse and treatment-related changes, and the evaluation of response to anticancer therapy. In particular, joint recommendations of the Response Assessment in Neuro-Oncology (RANO) Group, the European Association of Neuro-oncology, and major European and American Nuclear Medicine societies highlighted that the additional clinical value of radiolabeled amino acids compared to anatomical MRI alone is outstanding and that its widespread clinical use should be supported. For advanced MRI and its steadily increasing use in clinical practice, the Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition provided more recently an updated acquisition protocol for the widely used dynamic susceptibility contrast perfusion MRI. Besides amino acid PET and perfusion MRI, other PET tracers and advanced MRI techniques (e.g. MR spectroscopy) are of considerable clinical interest and are increasingly integrated into everyday clinical practice. Nevertheless, these modalities have shortcomings which should be considered in clinical routine. This comprehensive review provides an overview of potential challenges, limitations, and pitfalls associated with PET imaging and advanced MRI techniques in patients with gliomas or brain metastases. Despite these issues, PET imaging and advanced MRI techniques continue to play an indispensable role in brain tumor management. Acknowledging and mitigating these challenges through interdisciplinary collaboration, standardized protocols, and continuous innovation will further enhance the utility of these modalities in guiding optimal patient care.

Deep learning-based tumor segmentation and classification in breast MRI with 3TP method

Background and Objective:Timely diagnosis of early breast cancer plays a critical role in improving patient outcome and increasing treatment effectiveness. Dynamic contrast-enhancing magnetic resonance imaging (DCE-MRI) is a minimally invasive test widely used in the analysis of breast cancer. Manual analysis of DCE-MRI images by the specialist is extremely complex, exhaustive, and can lead to misunderstandings. Thus, the development of automated methods for analyzing DCE-MRI images of the breast is increasing. In this research, we propose an automatic methodology capable of detecting tumors and classifying their malignancy in a DCE-MRI breast image. Methodology:The proposed method consists of the use of two deep learning architectures, that is, SegNet and UNet, for breast tumor segmentation and the three-time-point (3TP) method for classifying the malignancy of segmented tumors. Results:The proposed methodology was tested on the public Quantitative Imaging Network (QIN) Breast DCE-MRI image set, and the best result in segmentation was a Dice of 0.9332 and IoU of 0.9799. For the classification of tumor malignancy, the methodology presented an accuracy of 100%. Conclusions:In our research, we demonstrate that the problem of mammary tumor segmentation in DCE-MRI images can be efficiently solved using deep learning architectures, and tumor malignancy classification can be done through the three-time method. The method can be integrated as a support system for the specialist in treating patients with breast cancer.

Evaluation of molecular subtypes of breast cancer using MRI BI-RADS Lexicon

BackgroundMolecular subtyping of breast cancer is one of the prognostic factors which play a very important role in managing patient’s treatment plan. The MRI BI-RADS Lexicon is initially used to categorize breast lesions but recent attempts were employed to differentiate breast lesions based on their molecular subtypes using this lexicon. The study aimed to evaluate of the role of the MRI BI-RADS Lexicon in classifying different molecular subtypes of breast cancer especially after coupling with Kaiser scoring system.MethodsThis retrospective study was conducted on 147 patients with 170 malignant breast lesions. They underwent Pre-contrast and a Dynamic contrast MRI study. Retrospective interpretation of the morphological and dynamic criteria of the breast lesions based on the MRI BI-RADS criteria was carried out followed by reassessment of the same lesions by Kaiser scoring. Resulting data were correlated with histopathological and immunological characterization.ResultsLuminal subtypes were more frequently encountered as mass lesions, contrary to the Non-Luminal lesions which showed a more frequent non-mass presentation value (P 0.002). The shape, margin, internal enhancement pattern of the mass lesions showed significant variability between different molecular subtypes (P < 0.001, < 0.001, < 0.001) respectively. On Dynamic study, Plateau curve was a more evident pattern with Luminal lesions contrasting with their Non-Luminal counterparts which showed a washout pattern more frequently (P 0.0004). Most of luminal A cancers were presented as mass lesions with rim enhancement and categorized as BIRADS 4 while most of Her2neu positive cancers (including luminal B entity) were presented as non-mass lesions with irregular shape and dark internal septations and categorized as BIRADS 5 with statistically significant values (P < 0.001). Coupling with Kaiser scoring system improved the categorization of non-luminal tumors as BIRADS 5 lesions especially the aggressive TN cancers.ConclusionsMRI-BIRADS lexicon can be of great value in the non-invasive molecular characterization of breast cancer. Kaiser score improved the categorization of TN cancers which were upgraded to BIRADS 5 category.

Prospectively accelerated dynamic speech magnetic resonance imaging at 3 T using a self-navigated spiral-based manifold regularized scheme.

This work develops and evaluates a self-navigated variable density spiral (VDS)-based manifold regularization scheme to prospectively improve dynamic speech magnetic resonance imaging (MRI) at 3 T. Short readout duration spirals (1.3-ms long) were used to minimize sensitivity to off-resonance. A custom 16-channel speech coil was used for improved parallel imaging of vocal tract structures. The manifold model leveraged similarities between frames sharing similar vocal tract postures without explicit motion binning. The self-navigating capability of VDS was leveraged to learn the Laplacian structure of the manifold. Reconstruction was posed as a sensitivity-encoding-based nonlocal soft-weighted temporal regularization scheme. Our approach was compared with view-sharing, low-rank, temporal finite difference, extra dimension-based sparsity reconstruction constraints. Undersampling experiments were conducted on five volunteers performing repetitive and arbitrary speaking tasks at different speaking rates. Quantitative evaluation in terms of mean square error over moving edges was performed in a retrospective undersampling experiment on one volunteer. For prospective undersampling, blinded image quality evaluation in the categories of alias artifacts, spatial blurring, and temporal blurring was performed by three experts in voice research. Region of interest analysis at articulator boundaries was performed in both experiments to assess articulatory motion. Improved performance with manifold reconstruction constraints was observed over existing constraints. With prospective undersampling, a spatial resolution of 2.4 × 2.4 mm2/pixel and a temporal resolution of 17.4 ms/frame for single-slice imaging, and 52.2 ms/frame for concurrent three-slice imaging, were achieved. We demonstrated implicit motion binning by analyzing the mechanics of the Laplacian matrix. Manifold regularization demonstrated superior image quality scores in reducing spatial and temporal blurring compared with all other reconstruction constraints. While it exhibited faint (nonsignificant) alias artifacts that were similar to temporal finite difference, it provided statistically significant improvements compared with the other constraints. In conclusion, the self-navigated manifold regularized scheme enabled robust high spatiotemporal resolution dynamic speech MRI at 3 T.

Computerized Segmentation Method for Nonmasses on Breast DCE-MRI Images Using ResUNet++ with Slice Sequence Learning and Cross-Phase Convolution

The purpose of this study was to develop a computerized segmentation method for nonmasses using ResUNet++ with a slice sequence learning and cross-phase convolution to analyze temporal information in breast dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI) images. The dataset consisted of a series of DCE-MRI examinations from 54 patients, each containing three-phase images, which included one image that was acquired before contrast injection and two images that were acquired after contrast injection. In the proposed method, the region of interest (ROI) slice images are first extracted from each phase image. The slice images at the same position in each ROI are stacked to generate a three-dimensional (3D) tensor. A cross-phase convolution generates feature maps with the 3D tensor to incorporate the temporal information. Subsequently, the feature maps are used as the input layers for ResUNet++. New feature maps are extracted from the input data using the ResUNet++ encoders, following which the nonmass regions are segmented by a decoder. A convolutional long short-term memory layer is introduced into the decoder to analyze a sequence of slice images. When using the proposed method, the average detection accuracy of nonmasses, number of false positives, Jaccard coefficient, Dice similarity coefficient, positive predictive value, and sensitivity were 90.5%, 1.91, 0.563, 0.712, 0.714, and 0.727, respectively, larger than those obtained using 3D U-Net, V-Net, and nnFormer. The proposed method achieves high detection and shape accuracies and will be useful in differential diagnoses of nonmasses.