Clinical Utilization of Multimodality Imaging for Myocarditis and Cardiac Sarcoidosis.

Myocarditis is defined as inflammation of the myocardium according to clinical, histological, biochemical, immunohistochemical, or imaging findings. Inflammation can be categorized histologically by cell type or pattern, and many causes have been implicated, including infectious, most commonly viral, systemic autoimmune diseases, vaccine-associated processes, environmental factors, toxins, and hypersensitivity to drugs. Sarcoid myocarditis is increasingly recognized as an important cause of cardiomyopathy and has important diagnostic, prognostic, and therapeutic implications in patients with systemic sarcoidosis. The clinical presentation of myocarditis may include an asymptomatic, subacute, acute, fulminant, or chronic course and may have focal or diffuse involvement of the myocardium depending on the cause and time point of the disease. For most causes of myocarditis except sarcoidosis, myocardial biopsy is the gold standard but is limited due to risk, cost, availability, and variable sensitivity. Diagnostic criteria have been established for both myocarditis and cardiac sarcoidosis and include clinical and imaging findings particularly the use of cardiac magnetic resonance and positron emission tomography. Beyond diagnosis, imaging findings may also provide prognostic value. This case-based review focuses on the current state of multimodality imaging for the diagnosis and management of myocarditis and cardiac sarcoidosis, highlighting multimodality imaging approaches with practical clinical vignettes, with a discussion of knowledge gaps and future directions.

Research on Diagnosis Architecture of Cardiovascular Diseases Based on Multimedical Images.

OBJECTIVE: To study the effect of a multi-image source 3D modeling imaging examination system on the diagnosis of cardiovascular diseases in cardiac surgery. METHODS: The data of 680 confirmed patients and 1590 suspected patients in the cardiac surgery department of all hospitals of a large chain hospital management group were selected. All patients gave the examination results of multiple image sources and independent examination results of multiple image sources, respectively, their examination sensitivity, specificity, and reliability were compared, and the treatment efficiency and nursing satisfaction of the virtual reference group were deduced in MATLAB. Perform the bivariate t-test and comparative statistics in SPSS. RESULTS: The multi-image source 3D modeling examination system had higher examination sensitivity, specificity, and reliability and higher examination sensitivity in the early stage of the disease. It was deduced that the clinical efficiency and nursing satisfaction based on the examination results were significantly improved (t < 10.000, p < 0.01). CONCLUSION: The multi-image source 3D modeling imaging examination system is suitable for the diagnosis of cardiovascular diseases in cardiac surgery.

Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine.

Image fusion can be performed on images either in spatial domain or frequency domain methods. Frequency domain methods will be most preferred because these methods can improve the quality of edges in an image. In image fusion, the resultant fused images will be more informative than individual input images, thus more suitable for classification problems. Artificial intelligence (AI) algorithms play a significant role in improving patient's treatment in the health care industry and thus improving personalized medicine. This research work analyses the role of image fusion in an improved brain tumour classification model, and this novel fusion-based cancer classification model can be used for personalized medicine more effectively. Image fusion can improve the quality of resultant images and thus improve the result of classifiers. Instead of using individual input images, the high-quality fused images will provide better classification results. Initially, the contrast limited adaptive histogram equalization technique preprocess input images such as MRI and SPECT images. Benign and malignant class brain tumor images are applied with discrete cosine transform-based fusion method to obtain fused images. AI algorithms such as support vector machine classifier, KNN classifier, and decision tree classifiers are tested with features obtained from fused images and compared with the result obtained from individual input images. Performances of classifiers are measured using the parameters accuracy, precision, recall, specificity, and F1 score. SVM classifier provided the maximum accuracy of 96.8%, precision of 95%, recall of 94%, specificity of 93%, F1 score of 91%, and performed better than KNN and decision tree classifiers when extracted features from fused images are used. The proposed method results are compared with existing methods and provide satisfactory results.

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures.

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e-11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e-14). Extending the radiomics approach to high-dimensional optical data-termed "optomics" in this study-offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.

Multimodal Medical Image Fusion Based on Multiple Latent Low-Rank Representation.

A multimodal medical image fusion algorithm based on multiple latent low-rank representation is proposed to improve imaging quality by solving fuzzy details and enhancing the display of lesions. Firstly, the proposed method decomposes the source image repeatedly using latent low-rank representation to obtain several saliency parts and one low-rank part. Secondly, the VGG-19 network identifies the low-rank part's features and generates the weight maps. Then, the fused low-rank part can be obtained by making the Hadamard product of the weight maps and the source images. Thirdly, the fused saliency parts can be obtained by selecting the max value. Finally, the fused saliency parts and low-rank part are superimposed to obtain the fused image. Experimental results show that the proposed method is superior to the traditional multimodal medical image fusion algorithms in the subjective evaluation and objective indexes.

18F-FDG-PET-MRI for the assessment of acute intestinal graft-versus-host-disease (GvHD).

BACKGROUND: Graft versus host disease (GvHD) is a frequent complication of allogeneic stem cell transplantation (alloSCT), significantly increasing mortality. Previous imaging studies focused on the assessment of intestinal GvHD with contrast-enhanced MRI/CT or 18F-FDG-PET imaging alone. The objective of this retrospective study was to elucidate the diagnostic value of a combined 18F-FDG-PET-MRI protocol in patients with acute intestinal GvHD. METHODS: Between 2/2015 and 8/2019, 21 patients with acute intestinal GvHD underwent 18F-FDG-PET-MRI. PET, MRI and PET-MRI datasets were independently reviewed. Readers assessed the number of affected segments of the lower gastrointestinal tract and the reliability of the diagnosis on a 5-point Likert scale and quantitative PET (SUVmax, SUVpeak, metabolic volume (MV)) and MRI parameter (wall thickness), were correlated to clinical staging of acute intestinal GvHD. RESULTS: The detection rate for acute intestinal GvHD was 56.8% for PET, 61.4% for MRI and 100% for PET-MRI. PET-MRI (median Likert-scale value: 5; range: 4-5) offers a significantly higher reliability of the diagnosis compared to PET (median: 4; range: 2-5; p = 0.01) and MRI alone (median: 4; range: 3-5; p = 0.03). The number of affected segments in PET-MRI (rs = 0.677; p <  0.001) and the MV (rs = 0.703; p <  0.001) correlated significantly with the clinical stage. SUVmax (rs = 0.345; p = 0.14), SUVpeak (rs = 0.276; p = 0.24) and wall thickening (rs = 0.174; p = 0.17) did not show a significant correlation to clinical stage. CONCLUSION: 18F-FDG-PET-MRI allows for highly reliable assessment of acute intestinal GvHD and adds information indicating clinical severity.

Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information.

Multimodal imaging is an active branch of research as it has the potential to improve common medical imaging techniques. Diffuse optical tomography (DOT) is an example of a low resolution, functional imaging modality that typically has very low resolution due to the ill-posedness of its underlying inverse problem. Combining the functional information of DOT with a high resolution structural imaging modality has been studied widely. In particular, the combination of DOT with ultrasound (US) could serve as a useful tool for clinicians for the formulation of accurate diagnosis of breast lesions. In this paper, we propose a novel method for US-guided DOT reconstruction using a portable time-domain measurement system. B-mode US imaging is used to retrieve morphological information on the probed tissues by means of a semi-automatical segmentation procedure based on active contour fitting. A two-dimensional to three-dimensional extrapolation procedure, based on the concept of distance transform, is then applied to generate a three-dimensional edge-weighting prior for the regularization of DOT. The reconstruction procedure has been tested on experimental data obtained on specifically designed dual-modality silicon phantoms. Results show a substantial quantification improvement upon the application of the implemented technique. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Musiré: multimodal simulation and reconstruction framework for the radiological imaging sciences.

A software-based workflow is proposed for managing the execution of simulation and image reconstruction for SPECT, PET, CBCT, MRI, BLI and FMI packages in single and multimodal biomedical imaging applications. The workflow is composed of a Bash script, the purpose of which is to provide an interface to the user, and to organize data flow between dedicated programs for simulation and reconstruction. The currently incorporated simulation programs comprise GATE for Monte Carlo simulation of SPECT, PET and CBCT, SpinScenario for simulating MRI, and Lipros for Monte Carlo simulation of BLI and FMI. Currently incorporated image reconstruction programs include CASToR for SPECT and PET as well as RTK for CBCT. MetaImage (mhd) standard is used for voxelized phantom and image data format. Meshlab project (mlp) containers incorporating polygon meshes and point clouds defined by the Stanford triangle format (ply) are employed to represent anatomical structures for optical simulation, and to represent tumour cell inserts. A number of auxiliary programs have been developed for data transformation and adaptive parameter assignment. The software workflow uses fully automatic distribution to, and consolidation from, any number of Linux workstations and CPU cores. Example data are presented for clinical SPECT, PET and MRI systems using the Mida head phantom and for preclinical X-ray, PET and BLI systems employing the Digimouse phantom. The presented method unifies and simplifies multimodal simulation setup and image reconstruction management and might be of value for synergistic image research. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging.

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

The Risk of Prostate Cancer Progression in Active Surveillance Patients with Bilateral Disease Detected by Combined Magnetic Resonance Imaging-Fusion and Systematic Biopsy.

PURPOSE: We sought to evaluate whether bilateral prostate cancer detected at active surveillance (AS) enrollment is associated with progression to Grade Group (GG) ≥2 and to compare the efficacy of combined targeted biopsy plus systematic biopsy (Cbx) vs systematic biopsy (Sbx) or targeted biopsy alone to detect bilateral disease. MATERIALS AND METHODS: A prospectively maintained database of patients referred to our institution from 2007-2020 was queried. The study cohort included all AS patients with GG1 on confirmatory Cbx and followup of at least 1 year. Cox proportional hazard analysis identified baseline characteristics associated with progression to ≥GG2 at any point throughout followup. RESULTS: Of 579 patients referred, 103 patients had GG1 on Cbx and were included in the study; 49/103 (47.6%) patients progressed to ≥GG2, with 30/72 (41.7%) patients with unilateral disease progressing and 19/31 (61.3%) patients with bilateral disease progressing. Median time to progression was 68 months vs 52 months for unilateral and bilateral disease, respectively (p=0.006). Both prostate specific antigen density (HR 1.72, p=0.005) and presence of bilateral disease (HR 2.21, p=0.012) on confirmatory biopsy were associated with AS progression. At time of progression, GG and risk group were significantly higher in patients with bilateral versus unilateral disease. Cbx detected 16% more patients with bilateral disease than Sbx alone. CONCLUSIONS: Bilateral disease and prostate specific antigen density at confirmatory Cbx conferred greater risk of earlier AS progression. Cbx was superior to Sbx for identifying bilateral disease. AS risk-stratification protocols may benefit from including presence of bilateral disease and should use Cbx to detect bilateral disease.

Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer.

PURPOSE: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. MATERIALS AND METHODS: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. RESULTS: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p <0.001 and p=0.004, respectively) but was similar to RTB (p=0.71), which used on average 3.8 (22%) fewer cores per patient. In 102 patients who underwent prostatectomy, there was no significant difference in upgrading rates between RTB and combined biopsy (p=0.84). CONCLUSIONS: A RTB approach can maintain state-of-the-art detection rates while requiring fewer retrieved cores. This result informs decision making about biopsy site selection and total retrieved core count.

Real-time ultrasound virtual navigation in 3D PET/CT volumes for superficial lymph-node evaluation: innovative fusion examination.

OBJECTIVE: To evaluate the feasibility and clinical application of fusion imaging with virtual navigation, combining 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography/computed tomography (PET/CT) with real-time ultrasound imaging, in assessing superficial lymph nodes in breast-cancer and gynecological-cancer patients. METHODS: This was a pilot study of breast- and gynecological-cancer patients with abnormal uptake of 18 F-FDG by axillary or groin lymph nodes on PET/CT scan, examined at our institution between January 2017 and May 2019. Fusion imaging was performed, uploading preacquired PET/CT DICOM images onto the ultrasound machine and synchronizing them with real-time ultrasound scanning performed at the lymph-node site. In the first phase, we assessed the feasibility and reliability of fusion imaging in a series of 10 patients with suspicious lymph nodes on both PET/CT and ultrasound, and with full correspondence between both techniques in terms of size, shape and morphology of the lymph nodes (Group A). In the second phase, we included 20 patients with non-corresponding findings between PET/CT and ultrasound: 10 patients with lymph nodes that were suspicious or pathological on PET/CT scan but not suspicious on ultrasound assessment (Group B), and 10 patients with suspicious or pathological lymph nodes on both PET/CT and ultrasound but with no correspondence between the two techniques in terms of number of affected lymph nodes (Group C). RESULTS: In the 30 selected patients, fusion imaging was assessed at 30 lymph-node sites (22 inguinal and eight axillary nodes). In the first phase (Group A), the fusion technique was shown to be feasible in all 10 lymph-node sites evaluated. In the second phase, fusion imaging was completed successfully in nine of 10 cases in Group B and in all 10 cases in Group C. In all groups, fusion imaging was able to identify the target lymph node, guiding the examiner to perform a core-needle aspiration biopsy or to inject radiotracer for selective surgical nodal excision, according to the radio-guided occult lesion localization technique. CONCLUSION: Fusion imaging with virtual navigation, combining PET/CT and real-time ultrasound imaging, is technically feasible and able to detect target lymph nodes even when PET/CT and ultrasound findings are inconsistent. Fusion imaging can also be used to guide the performance of core-needle aspiration biopsy, avoiding further surgical diagnostic procedures, or the injection of radiotracer for selective surgical nodal excision, enabling more sparing, selective surgery. This innovative technique could open up multiple diagnostic and therapeutic opportunities in breast and gynecological oncology. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

A Collaborative Dictionary Learning Model for Nasopharyngeal Carcinoma Segmentation on Multimodalities MR Sequences.

Nasopharyngeal carcinoma (NPC) is the most common malignant tumor of the nasopharynx. The delicate nature of the nasopharyngeal structures means that noninvasive magnetic resonance imaging (MRI) is the preferred diagnostic technique for NPC. However, NPC is a typically infiltrative tumor, usually with a small volume, and thus, it remains challenging to discriminate it from tightly connected surrounding tissues. To address this issue, this study proposes a voxel-wise discriminate method for locating and segmenting NPC from normal tissues in MRI sequences. The located NPC is refined to obtain its accurate segmentation results by an original multiviewed collaborative dictionary classification (CODL) model. The proposed CODL reconstructs a latent intact space and equips it with discriminative power for the collective multiview analysis task. Experiments on synthetic data demonstrate that CODL is capable of finding a discriminative space for multiview orthogonal data. We then evaluated the method on real NPC. Experimental results show that CODL could accurately discriminate and localize NPCs of different volumes. This method achieved superior performances in segmenting NPC compared with benchmark methods. Robust segmentation results show that CODL can effectively assist clinicians in locating NPC.

Tumor size and focality in breast carcinoma: Analysis of concordance between radiological imaging modalities and pathological examination at a cancer center.

CONTEXT: Accurate assessment of clinical and pathological tumor stage is crucial for patient treatment and prognosis. OBJECTIVE: The aim of this study was to assess the concordance between the tumor size and focality between radiological studies and pathology and to evaluate the impact of discrepancies on staging. DESIGN: Patients who underwent surgery for invasive breast carcinoma from January 1, 2014, to December 31, 2015, were identified. RESULTS: Three imaging modalities (mammogram, ultrasound and MRI) were compared with gross examination and final pathology. 1152 preoperative radiological studies were evaluated for focality and 1019 were evaluated for tumor size. For all 3 radiographic modalities, there was a statistically significant difference between the mean tumor size on radiology and the final pathology report (mammogram, P < .001; ultrasound, P = .004; MRI, P < .001). In 29% of radiology studies, there was a discrepancy in stage. The error rate for determining focality was 28% for mammograms, 27% for ultrasounds, and 29% for MRIs. Tumor size from gross examination correlated with microscopic tumor size in 57% of cases, but gross examination had 88% concordance with the final pathology report in determining focality. CONCLUSION: Our study revealed statistically significant differences in mean tumor size reported across all 3 imaging modalities when compared to the final pathology report. MRI had the highest error rate, with a tendency to overestimate tumor size and number of foci. Among all diagnoses, cases of invasive carcinoma with an extensive intraductal component were most prone to discrepancies with imaging.

Clinical-stage Approaches for Imaging Chronic Inflammation and Fibrosis in Crohn's Disease.

The number of imaging-based indices developed for inflammatory bowel disease as research tools, objectively measuring ileocolonic and perianal activity and treatment response, has expanded in the past 2 decades. Created primarily to assess Crohn's disease (CD), there is increasing adoption of these indices into the clinical realm to guide patient care. This translation has been facilitated by validation in adult and pediatric populations, prompted by simplification of score calculations needed for practical application outside the research environment. The majority of these indices utilize magnetic resonance imaging (MRI), specifically MR enterography (MRE) and pelvic MRI, and more recently ultrasound. This review explores validated indices by modality, anatomic site and indication, including for documentation of the presence and extent of CD, disease progression, complications, and treatment response, highlighting those in clinical use or with the potential to be. As well, it details index imaging features used to quantify chronic inflammatory activity, severity, and to lesser extent fibrosis, in addition to their reference standards and any modifications. Validation in the pediatric population of indices primarily developed in adult cohorts such as the Magnetic Resonance Index of Activity (MaRIA), the Simplified Magnetic Resonance Index of Activity (MARIAs), and the MRE global score (MEGS), together with newly developed pediatric-specific indices, are discussed. Indices that may be predictive of disease course and investigational techniques with the potential to provide future imaging biomarkers, such as multiparametric MRI, are also briefly considered.

CT-TEE Image Registration for Surgical Navigation of Congenital Heart Disease Based on a Cycle Adversarial Network.

Transesophageal echocardiography (TEE) has become an essential tool in interventional cardiologist's daily toolbox which allows a continuous visualization of the movement of the visceral organ without trauma and the observation of the heartbeat in real time, due to the sensor's location at the esophagus directly behind the heart and it becomes useful for navigation during the surgery. However, TEE images provide very limited data on clear anatomically cardiac structures. Instead, computed tomography (CT) images can provide anatomical information of cardiac structures, which can be used as guidance to interpret TEE images. In this paper, we will focus on how to transfer the anatomical information from CT images to TEE images via registration, which is quite challenging but significant to physicians and clinicians due to the extreme morphological deformation and different appearance between CT and TEE images of the same person. In this paper, we proposed a learning-based method to register cardiac CT images to TEE images. In the proposed method, to reduce the deformation between two images, we introduce the Cycle Generative Adversarial Network (CycleGAN) into our method simulating TEE-like images from CT images to reduce their appearance gap. Then, we perform nongrid registration to align TEE-like images with TEE images. The experimental results on both children' and adults' CT and TEE images show that our proposed method outperforms other compared methods. It is quite noted that reducing the appearance gap between CT and TEE images can benefit physicians and clinicians to get the anatomical information of ROIs in TEE images during the cardiac surgical operation.

Risk of Prostate Cancer after a Negative Magnetic Resonance Imaging Guided Biopsy.

PURPOSE: Magnetic resonance imaging guided biopsy which reveals no cancer may impart reassurance beyond that offered by ultrasound guided biopsy. However, followup of men after a negative magnetic resonance imaging guided biopsy has been mostly by prostate specific antigen testing and reports of followup tissue confirmation are few. We investigated the incidence of clinically significant prostate cancer in such men who, because of persistent cancer suspicion, subsequently underwent a repeat magnetic resonance imaging guided biopsy. MATERIALS AND METHODS: Subjects were all men with a negative initial magnetic resonance imaging guided biopsy who underwent at least 1 further magnetic resonance imaging guided biopsy due to continued clinical suspicion of clinically significant prostate cancer (September 2009 to July 2019). Biopsies were magnetic resonance imaging-ultrasound fusion with targeted and systematic cores. Regions of interest from initial magnetic resonance imaging and any new regions of interest at followup magnetic resonance imaging guided biopsy were targeted. The primary end point was detection of clinically significant prostate cancer (Gleason Grade Group 2 or greater). RESULTS: Of 2,716 men 733 had a negative initial magnetic resonance imaging guided biopsy. Study subjects were 73/733 who underwent followup magnetic resonance imaging guided biopsy. Median (IQR) age and prostate specific antigen density were 64 years (59-67) and 0.12 ng/ml/cc (0.08-0.17), respectively. Baseline PI-RADS® scores were 3 or greater in 74%. At followup magnetic resonance imaging guided biopsy (median 2.4 years, IQR 1.3-3.6), 17/73 (23%) were diagnosed with clinically significant prostate cancer. When followup magnetic resonance imaging revealed a lesion (PI-RADS 3 or greater), clinically significant prostate cancer was found in 17/53 (32%). When followup magnetic resonance imaging was negative (PI-RADS less than 3), cancer was not found (0/20) (p <0.01). Overall 54% of men with PI-RADS 5 at followup magnetic resonance imaging guided biopsy were found to have clinically significant prostate cancer. CONCLUSIONS: Men with negative magnetic resonance imaging following an initial negative magnetic resonance imaging guided biopsy are unlikely to harbor clinically significant prostate cancer and may avoid repeat biopsy. However, when lesions are seen on followup magnetic resonance imaging, repeat magnetic resonance imaging guided biopsy is warranted.

Research of Multimodal Medical Image Fusion Based on Parameter-Adaptive Pulse-Coupled Neural Network and Convolutional Sparse Representation.

Visual effects of medical image have a great impact on clinical assistant diagnosis. At present, medical image fusion has become a powerful means of clinical application. The traditional medical image fusion methods have the problem of poor fusion results due to the loss of detailed feature information during fusion. To deal with it, this paper proposes a new multimodal medical image fusion method based on the imaging characteristics of medical images. In the proposed method, the non-subsampled shearlet transform (NSST) decomposition is first performed on the source images to obtain high-frequency and low-frequency coefficients. The high-frequency coefficients are fused by a parameter-adaptive pulse-coupled neural network (PAPCNN) model. The method is based on parameter adaptive and optimized connection strength ß adopted to promote the performance. The low-frequency coefficients are merged by the convolutional sparse representation (CSR) model. The experimental results show that the proposed method solves the problems of difficult parameter setting and poor detail preservation of sparse representation during image fusion in traditional PCNN algorithms, and it has significant advantages in visual effect and objective indices compared with the existing mainstream fusion algorithms.

Can high-frequency ultrasound combined computed tomography accurately diagnose thyroid tumor?: A protocol of systematic review and meta-analysis.

BACKGROUND: Previous clinical studies have reported that clinical value of high-frequency ultrasound combined computed tomography (HFUCT) is used for diagnosis of thyroid tumor (TT). However, no study has investigated this topic systematically. Therefore, this study will evaluate the clinical value of HFUCT for the diagnosis of TT. METHODS: We will search the databases of Cochrane Library, EMBASE, PUBMED, SCOPUS, Web of Science, OpenGrey, Cumulative Index to Nursing and Allied Health Literature, Allied and Complementary Medicine Database, and China National Knowledge Infrastructure from any time period published to the present. We will consider all case-controlled studies that assessed the clinical value of HFUCT for diagnosis of TT. Two authors will independently scan titles and abstracts to check eligible studies, followed by full-text read. We will extract data and assess study quality using Quality Assessment of Diagnostic Accuracy Studies tool. RevMan 5.3 software will be utilized for data pooling and statistical analysis. RESULTS: This study will be performed to assess the clinical value of HFUCT for the diagnosis of TT, and will provide an evidence-based synthesis for clinical application and further study. CONCLUSION: Summary of this study will provide the latest evidence to determine whether HFUCT can be used for TT diagnosis accurately. STUDY REGISTRATION: INPLASY202040022.

Is CT necessary for imaging paediatric congenital sensorineural hearing loss?

Objectives: To determine if MRI alone is adequate for pre-operative assessment of paediatric congenital sensorineural hearing loss (SNHL). While aberrant intratemporal facial nerve anatomy is usually occult on MRI, we postulate that the majority of cases have no adverse bearing on surgical outcomes.Methods: MRI and CT of the temporal bones were analysed in 240 children who underwent both on the same day for SNHL. Only children under the age of 5 years with no reported clinical syndrome or dysmorphic external ear anatomy were included.Results and discussion: 169 patients satisfied the inclusion criteria. MRI detected 32/54 cases of cochleovestibular dysplasia, with the majority of the additional CT findings comprising subtle incomplete partition type 2 (IP2) anomalies. Of the 22 cases not evident on MRI, 13 patients also had large vestibular aqueduct syndromoe (LVAS), which would have prompted evaluation with CT due to the near universal co-existence of these entities. Only one patient exhibited aberrant intratemporal facial nerve anatomy that may have conferred surgical risk and was occult on MRI.Conclusion: In a defined paediatric SNHL cohort, the addition of routine temporal bone CT to MRI offers limited additional yield but confers a significant radiation burden on a young population.