Imaging Modalities Research Articles

Prediction of Abnormal Growth of Breast Cancer Cell Using Support Vector Machine

Abstract: Breast cancer is a serious health concern that affects millions of women worldwide. Early detection of breast cancer is crucial for effective treatment and improved survival rates. Artificial intelligence (AI) has shown great promise in the field of medical imaging and has been increasingly used for breast cancer detection. Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has been developed for it. Breast cancer is one of the most common cancer types. According to the National Breast Cancer foundation, in 2020 alone, more than 276,000 new cases of invasive breast cancer and more than 48,000 non-invasive cases were diagnosed in the US. To put these figures in perspective, 64% of these cases are diagnosed early in the disease’s cycle, giving patients a 99% chance of survival. In this paper we develop a system for diagnosis, prognosis and prediction of breast cancer using AI. This will assist the doctors in diagnosis of the disease. In this research work, we systematically reviewed previous work done on detection and treatment of breast cancer using genetic sequencing or histopathological imaging with the help of deep learning and machine learning We use of AI for breast cancer detection, including studies that have used mammography, ultrasound, and magnetic resonance imaging (MRI) as imaging modalities. AI can also improve the accuracy and efficiency of breast cancer screening and diagnosis, as well as the challenges that must be addressed to ensure the successful integration of AI into clinical practice. However, further research and development are needed to optimize AI algorithms and ensure their safety and effectiveness in clinical practice. Breast cancer detection has emerged as a critical area of research, leveraging the power of Artificial Intelligence (AI) to enhance diagnostic accuracy and efficiency. Utilizing AI technologies, particularly deep learning, enables the development of robust and precise models for early breast cancer detection. These models analyze mammographic images, identifying subtle patterns indicative of malignancies that may escape human eye detection. Transfer learning, employing pre-trained neural network architectures, has demonstrated significant success in leveraging existing knowledge for improved performance. The integration of convolutional neural networks (CNNs) and image processing techniques empowers AI models to discern subtle abnormalities, aiding in the timely identification of potential breast tumors. Additionally, AI-driven diagnostic tools can streamline radiologists' workflow, providing rapid and reliable assessments, ultimately contributing to early intervention and improved patient outcomes. As these technologies continue to evolve, the synergy between AI and breast cancer detection promises to revolutionize screening methods, fostering a paradigm shift towards more accurate, efficient, and accessible diagnostic practices in the realm of breast health.

Focal incidental colorectal fluorodeoxyglucose uptake: Should it be spotlighted?

Focal incidental colorectal fluorodeoxyglucose uptake: Should it be spotlighted?

A Prospective Study of the Diagnostic Performance of Photon-Counting CT Compared With MRI in the Characterization of Renal Masses.

The aim of this study was to assess the interreader reliability and per-RCC sensitivity of high-resolution photon-counting computed tomography (PCCT) in the detection and characterization of renal masses in comparison to MRI. This prospective study included 24 adult patients (mean age, 52 ± 14 years; 14 females) who underwent PCCT (using an investigational whole-body CT scanner) and abdominal MRI within a 3-month time interval and underwent surgical resection (partial or radical nephrectomy) with histopathology (n = 70 lesions). Of the 24 patients, 17 had a germline mutation and the remainder were sporadic cases. Two radiologists (R1 and R2) assessed the PCCT and corresponding MRI studies with a 3-week washout period between reviews. Readers recorded the number of lesions in each patient and graded each targeted lesion's characteristic features, dimensions, and location. Data were analyzed using a 2-sample t test, Fisher exact test, and weighted kappa. In patients with von Hippel-Lindau mutation, R1 identified a similar number of lesions suspicious for neoplasm on both modalities (51 vs 50, P = 0.94), whereas R2 identified more suspicious lesions on PCCT scans as compared with MRI studies (80 vs 56, P = 0.12). R1 and R2 characterized more lesions as predominantly solid in MRIs (R1: 58/70 in MRI vs 52/70 in PCCT, P < 0.001; R2: 60/70 in MRI vs 55/70 in PCCT, P < 0.001). R1 and R2 performed similarly in detecting neoplastic lesions on PCCT and MRI studies (R1: 94% vs 90%, P = 0.5; R2: 73% vs 79%, P = 0.13). The interreader reliability and per-RCC sensitivity of PCCT scans acquired on an investigational whole-body PCCT were comparable to MRI scans in detecting and characterizing renal masses. PCCT scans have comparable performance to MRI studies while allowing for improved characterization of the internal composition of lesions due to material decomposition analysis. Future generations of this imaging modality may reveal additional advantages of PCCT over MRI.

Demystifying the "Dark Side of the Knee": An Update on Imaging of the Posterolateral Corner.

The posterolateral corner (PLC) of the knee is a complex anatomical-functional unit that includes ligamentous and tendinous structures that are crucial for joint stability. This review discusses the intricate anatomy, biomechanics, and imaging modalities, as well as the current challenges in diagnosing PLC injuries, with an emphasis on magnetic resonance imaging (MRI). Recognizing the normal MRI anatomy is critical in identifying abnormalities and guiding effective treatment strategies. Identification of the smaller structures of the PLC, traditionally difficult to depict on imaging, may not be necessary to diagnose a clinically significant PLC injury. Injuries to the PLC, often associated with cruciate ligament tears, should be promptly identified because failure to recognize them may result in persistent instability, secondary osteoarthritis, and cruciate graft failure.

Hi-gMISnet: generalized medical image segmentation using DWT based multilayer fusion and dual mode attention into high resolution pGAN

Objective. Automatic medical image segmentation is crucial for accurately isolating target tissue areas in the image from background tissues, facilitating precise diagnoses and procedures. While the proliferation of publicly available clinical datasets led to the development of deep learning-based medical image segmentation methods, a generalized, accurate, robust, and reliable approach across diverse imaging modalities remains elusive. Approach. This paper proposes a novel high-resolution parallel generative adversarial network (pGAN)-based generalized deep learning method for automatic segmentation of medical images from diverse imaging modalities. The proposed method showcases better performance and generalizability by incorporating novel components such as partial hybrid transfer learning, discrete wavelet transform (DWT)-based multilayer and multiresolution feature fusion in the encoder, and a dual mode attention gate in the decoder of the multi-resolution U-Net-based GAN. With multi-objective adversarial training loss functions including a unique reciprocal loss for enforcing cooperative learning in pGANs, it further enhances the robustness and accuracy of the segmentation map. Main results. Experimental evaluations conducted on nine diverse publicly available medical image segmentation datasets, including PhysioNet ICH, BUSI, CVC-ClinicDB, MoNuSeg, GLAS, ISIC-2018, DRIVE, Montgomery, and PROMISE12, demonstrate the proposed method’s superior performance. The proposed method achieves mean F1 scores of 79.53%, 88.68%, 82.50%, 93.25%, 90.40%, 94.19%, 81.65%, 98.48%, and 90.79%, respectively, on the above datasets, surpass state-of-the-art segmentation methods. Furthermore, our proposed method demonstrates robust multi-domain segmentation capabilities, exhibiting consistent and reliable performance. The assessment of the model’s proficiency in accurately identifying small details indicates that the high-resolution generalized medical image segmentation network (Hi-gMISnet) is more precise in segmenting even when the target area is very small. Significance. The proposed method provides robust and reliable segmentation performance on medical images, and thus it has the potential to be used in a clinical setting for the diagnosis of patients.

Case report: Chylopericardium secondary to dialysis catheter related jugular venous thrombosis in two dogs receiving long-term hemodialysis

Chylopericardium is a rare entity in veterinary medicine. In this report we document the development of chylopericardium in two dogs undergoing chronic hemodialysis. An 11-year-old female spayed Labrador retriever (Case 1) presented with acute coughing and lethargy 2 months following initial dialysis catheter placement and initiation of dialysis therapy for severe azotemia. Echocardiography demonstrated severe pericardial effusion and cardiac tamponade. Pericardial fluid analysis was consistent with chylous effusion. The dog underwent a subtotal pericardiectomy with thoracic duct ligation, and a PleuralPort™ was placed. The patient continued to receive outpatient hemodialysis therapy after pericardiectomy for several months until she died acutely at home. A 4-year-old male neutered Doberman (Case 2) was being treated for 2 months with outpatient hemodialysis for management of chronic kidney disease. On presentation for the 17th hemodialysis treatment, the patient had increased respiratory rate. Echocardiography demonstrated pleural and pericardial effusions, and fluid analysis in both cavities was consistent with chylous effusion. Use of tissue plasminogen activator (TPA), clot removal and replacement of the catheter was attempted; however pleural and pericardial effusion continued. The patient was euthanized after 25 hemodialysis sessions as owners elected not to pursue more procedures. In both cases, the cause of the chylopericardium was suspected to be secondary to catheter-associated thrombosis and/or stenosis based on multiple imaging modalities. Despite use of rivaroxaban and clopidogrel concurrently in each case, the chylous effusion persisted. This case report describes clinical details of a rare complication of long-term indwelling dialysis catheters in two dogs.

Assessment of Diverse Pelvic Pain in the First Trimester of Pregnancy with Ultrasound Guidance

Identifying and treating a pelvic pain during pregnancy can be challenging. Pregnant women still use ultrasound as their primary imaging modality. The current study set out to investigate the potential function of ultrasonography guidance in various pelvic pain sources during the first trimester of pregnancy. The Maternity and Children Hospital (MCH) and the Department of Radiology collaborated together to perform this cross-sectional descriptive study. 50 pregnant women, ages ranging from under 20 to over 30, who had pelvic pain throughout the first trimester (up to 12 weeks gestational age) participated in the study. All women had undergone clinical evaluations then to be referred for ultrasonography scans for the confirmation of diagnosis. SPSS software (version 25) was used to analyze the data and association using Odds ratio and multivariable logistic regression. In a study of 50 pregnant women with an assisted ultrasound. Among 22 (44%) and 28(56%) women were viable and non-viable pregnant. 60 percent of the women were primigravida, and 40 percent were multigravida. With a mean BMI of 28.7±4.21, the average age was 27.3±13.18 years. The most frequent causes of pelvic pain were abortion (22%), uterine fibroid (14%), and corpus luteal cyst (12%) in addition to Scar site pregnancy, Sub chorionic hematoma, ectopic pregnancy, and acute appendicitis were 8%,6%,6% and 1% respectively. whereas 30% of a normal pregnancy was found. The most reliable and non-invasive diagnostic technique for identifying various types of pelvic pain in pregnant women is ultrasound. It has been demonstrated that the timely treatment of women through the use of ultrasonography reduces the mortality rates linked with pregnancy problems.

Honeycomb effect elimination in differential phase fiber-bundle-based endoscopy

Fiber-bundle-based endoscopy, with its ultrathin probe and micrometer-level resolution, has become a widely adopted imaging modality for in vivo imaging. However, the fiber bundles introduce a significant honeycomb effect, primarily due to the multi-core structure and crosstalk of adjacent fiber cores, which superposes the honeycomb pattern image on the original image. To tackle this issue, we propose an iterative-free spatial pixel shifting (SPS) algorithm, designed to suppress the honeycomb effect and enhance real-time imaging performance. The process involves the creation of three additional sub-images by shifting the original image by one pixel at 0, 45, and 90 degree angles. These four sub-images are then used to compute differential maps in the x and y directions. By performing spiral integration on these differential maps, we reconstruct a honeycomb-free image with improved details. Our simulations and experimental results, conducted on a self-built fiber bundle-based endoscopy system, demonstrate the effectiveness of the SPS algorithm. SPS significantly improves the image quality of reflective objects and unlabeled transparent scattered objects, laying a solid foundation for biomedical endoscopic applications.

Single-Center Retrospective Study on the Efficacy of Contrast-Enhanced Ultrasound for Detection of Endoleak After Endovascular Aortic Repair

Introduction: Surveillance for endoleak after endovascular aortic aneurysm repair with computed tomography angiography has the associated risks of radiation exposure and nephrotoxic contrast agents. The purpose of this study was to evaluate the performance of contrast-enhanced ultrasound in the detection of endoleak post–endovascular aortic aneurysm repair. Methods: A single-center retrospective cohort study was performed evaluating patients with abdominal aortic aneurysm treated with endovascular aortic aneurysm repair between October 29, 2017 and April 21, 2021 and follow-up imaging with both computed tomography angiography and contrast-enhanced ultrasound. The sample included 35 imaging combinations in 28 patients. Positive and negative results for detection of endoleak by contrast-enhanced ultrasound were tabulated as true positive, false positive, true negative, and false negative compared to computed tomography angiography and conventional angiography. Sensitivity, specificity, positive predictive value, and negative predictive value of contrast-enhanced ultrasound were calculated. Results: Out of 35 imaging combinations, endoleak was detected in 24 cases by computed tomography angiography and in 23 cases by contrast-enhanced ultrasound. Using computed tomography angiography as the reference standard, contrast-enhanced ultrasound yielded 96% sensitivity, 100% specificity, 100% positive predictive value, and 92% negative predictive value for endoleak detection. In the 23 cases of endoleak detection by both contrast-enhanced ultrasound and computed tomography angiography, contrast-enhanced ultrasound discerned the correct endoleak type in all 23 cases, while computed tomography angiography identified the correct endoleak type in 20 cases ( P = .2333). Discussion: Endoleak detection by contrast-enhanced ultrasound appears at least equivalent to computed tomography angiography. Some of the advantages of contrast-enhanced ultrasound in the surveillance of endoleak after endovascular aortic aneurysm repair include an avoidance of radiation, elimination of nephrotoxic contrast agents, reduction in costs, real-time imaging, discerning flow directionality, and visualizing endoleaks in regions previously embolized with coils/plugs/liquid embolic agents. Limitations include operator dependence and variables that obscure the visual field including obese body habitus. With these advantages and excellent comparison data, contrast-enhanced ultrasound should be considered as a first-line imaging modality for long-term surveillance of endoleaks after endovascular aortic aneurysm repair. Conclusion: Contrast-enhanced ultrasound is a safe and viable option for long-term surveillance post–endovascular aortic aneurysm repair.

Magnetic resonance imaging should be the first-line imaging modality for investigating suspected proximal hamstring avulsion injuries.

The purpose of the study was to evaluate how the initial diagnostic tool used-specifically ultrasound (US) or magnetic resonance imaging (MRI)-for diagnosing proximal hamstring avulsion injury affects the delay before surgery and, secondarily, the outcomes of these injuries. This was a retrospective analysis of prospectively collected data (2012-2020). It targeted patients primarily treated for proximal hamstring avulsion injury. It included all patients with a preoperative US and/or MRI. Patients were divided into two groups based on the initial diagnostic tool used (US-first vs. MRI-first groups). The primary outcomes measure was the time from initial injury to surgical intervention (surgical delay). The secondary outcomes were the Parisien Hamstring Avulsion Score, as well as the activity level as measured by the University of California, Los Angeles (UCLA)Activity Scale and Tegner Activity Scale. The analysis included 392 patients with a mean age of 43.8 ± 13.6 years for the MRI-firstgroup and 47.6 ± 12.0 years for US-first group. Patients in the MRI-first group had a significantly shorter median time from injury to surgery of 20.0 days (interquartile range [IQR]: 11.0-61.0) compared to 30 days (IQR: 18-74) in the US-first group. At the final follow-up (4.2 ± 2.2 years for the MRI-first group and 5.1 ± 1.9 years for the US-first group), the MRI-first group had significantly higher mean Tegner Activity Scale and UCLA scores than the US-first group: The Tegner Activity Scale was median 5 (IQR: 3-7) for the MRI-first group versus median 4 (IQR: 2-6) for the US-first group (p < 0.05). The UCLA scores were 7.9 ± 2.4 for the MRI-first group compared to 7.3 ± 2.4 for the US-first group (p < 0.05). This difference was more pronounced when comparing the MRI-first group with the patient-false negative initial ultrasound. No difference was found regarding the Parisien Hamstring Avulsion Score. MRI as the initial diagnostic tool for proximal hamstring avulsion injury is associated with a shorter time to surgery and better postoperative outcomes in Tegner Activity Scale and UCLA scores, compared to US. Level III.

Validation of the standardization framework SSTR-RADS 1.0 for neuroendocrine tumors using the novel SSTR‑targeting peptide [18F]SiTATE.

Somatostatin receptor positron emission tomography/computed tomography (SSTR-PET/CT) using [68Ga]-labeled tracers is a widely used imaging modality for neuroendocrine tumors (NET). Recently, [18F]SiTATE, a SiFAlin tagged [Tyr3]-octreotate (TATE) PET tracer, has shown great potential due to favorable clinical characteristics. We aimed to evaluate the reproducibility of Somatostatin Receptor-Reporting and Data System 1.0 (SSTR-RADS 1.0) for structured interpretation and treatment planning of NET using [18F]SiTATE. Four readers assessed [18F]SiTATE-PET/CT of 95 patients according to the SSTR-RADS 1.0 criteria at two different time points. Each reader evaluated up to five target lesions per scan. The overall scan score and the decision on peptide receptor radionuclide therapy (PRRT) were considered. Inter- and intra-reader agreement was determined using the intraclass correlation coefficient (ICC). The ICC analysis on the inter-reader agreement using SSTR-RADS 1.0 for identical target lesions (ICC ≥ 85%), overall scan score (ICC ≥ 90%), and the decision to recommend PRRT (ICC ≥ 85%) showed excellent agreement. However, significant differences were observed in recommending PRRT among experienced readers (ER) (p = 0.020) and inexperienced readers (IR) (p = 0.004). Compartment-based analysis demonstrated good to excellent inter-reader agreement for most organs (ICC ≥ 74%), except for lymph nodes (ICC ≥ 53%). SSTR-RADS 1.0 represents a highly reproducible and consistent framework system for stratifying SSTR-targeted PET/CT scans, even using the novel SSTR-ligand [18F]SiTATE. Some inter-reader variability was observed regarding the evaluation of uptake intensity prior to PRRT as well as compartment scoring of lymph nodes, indicating that those categories require special attention during further clinical validation and might be refined in a future SSTR-RADS version 1.1. SSTR-RADS 1.0 is a consistent framework for categorizing somatostatin receptor-targeted PET/CT scans when using [18F]SiTATE. The framework serves as a valuable tool for facilitating and improving the management of patients with NET. SSTR-RADS 1.0 is a valuable tool for managing patients with NET. SSTR-RADS 1.0 categorizes patients with showing strong agreement across diverse reader expertise. As an alternative to [68Ga]-labeled PET/CT in neuroendocrine tumor imaging, SSTR-RADS 1.0 reliably classifies [18F]SiTATE-PET/CT.

How Will Artificial Intelligence Shape the Future of Decision-Making in Congenital Heart Disease?

Improvements in medical technology have significantly changed the management of congenital heart disease (CHD), offering novel tools to predict outcomes and personalize follow-up care. By using sophisticated imaging modalities, computational models and machine learning algorithms, clinicians can experiment with unprecedented insights into the complex anatomy and physiology of CHD. These tools enable early identification of high-risk patients, thus allowing timely, tailored interventions and improved outcomes. Additionally, the integration of genetic testing offers valuable prognostic information, helping in risk stratification and treatment optimisation. The birth of telemedicine platforms and remote monitoring devices facilitates customised follow-up care, enhancing patient engagement and reducing healthcare disparities. Taking into consideration challenges and ethical issues, clinicians can make the most of the full potential of artificial intelligence (AI) to further refine prognostic models, personalize care and improve long-term outcomes for patients with CHD. This narrative review aims to provide a comprehensive illustration of how AI has been implemented as a new technological method for enhancing the management of CHD.

Experimental and Monte Carlo based dosimetric investigation of a novel 3mm radiosurgery 3MV beam using the microSilicon detector.

The ZAP-X system is a novel gyroscopic radiosurgical system based on a 3MV linear accelerator and collimator cones with a diameter between 4 and 25mm. Advances in imaging modalities to detect small and early-stage pathologies allow for an early and less invasive treatment, where a smaller collimator matching the anatomical target could provide better sparing of surrounding healthy tissue. A novel 3mm collimator cone for the ZAP-X was developed. This study aims to investigate the usability of a commercial diode detector (microSilicon) for the dosimetric characterization of this small collimator cone; and to investigate the underlying small field perturbation effects. Profile measurements in five depths as well as PDD and output ratio measurements were performed with a microSilicon detector and radiochromic EBT3 films. In addition, comprehensive Monte Carlo simulations were performed to validate the measurement observations and to quantify the perturbation effects of the microSilicon detector in these extremely small field conditions. It is shown that the microSilicon detector enables an accurate dosimetric characterization of the 3mm beam. The profile parameters, such as the FWHM and 20%-80% penumbra width, agree within 0.1 to 0.2mm between film and detector measurements. The output ratios agree within the measurement uncertainty between microSilicon detector and films, whereas the comparisons of the PDD results show good agreement with the Monte Carlo simulations. The analysis of the perturbation factors of the microSilicon detector reveals a small field correction factor of approximately 3% for the 3mm circular beam and a correction factor smaller than 1.5% for field diameters above 3mm. It could be shown that the microSilicon detector is well-suitable for the characterization of the new 3mm circular beam of the ZAP-X system.

Combined Brain–Heart Imaging in Takotsubo Syndrome: Towards a Holistic Patient Assessment

Takotsubo syndrome (TTS) is a type of cardiomyopathy usually precipitated by either emotional or physical stress and potentially leading to reversible heart failure. There is emerging evidence indicating an interaction between the brain and the heart in patients with TTS. Nevertheless, these new insights are not reflected in the current clinical approach to TTS. The application of novel and existing imaging modalities for the evaluation of brain–heart interactions is an interesting approach that could potentially augment diagnostic and prognostic yield, as well as improve our pathophysiologic understanding in the context of TTS. In this opinion piece, we discuss the evidence supporting a brain–heart interaction in patients with TTS and discuss how a combined evaluation of brain–heart interactions could potentially be implemented.

Taxonomy of Acute Stroke: Imaging, Processing, and Treatment

Stroke management employs a variety of diagnostic imaging modalities, image processing and analysis methods, and treatment procedures. This work categorizes methods for stroke imaging, image processing and analysis, and treatment, and provides their taxonomies illustrated by a state-of-the-art review. Imaging plays a critical role in stroke management, and the most frequently employed modalities are computed tomography (CT) and magnetic resonance (MR). CT includes unenhanced non-contrast CT as the first-line diagnosis, CT angiography, and CT perfusion. MR is the most complete method to examine stroke patients. MR angiography is useful to evaluate the severity of artery stenosis, vascular occlusion, and collateral flow. Diffusion-weighted imaging is the gold standard for evaluating ischemia. MR perfusion-weighted imaging assesses the penumbra. The stroke image processing methods are divided into non-atlas/template-based and atlas/template-based. The non-atlas/template-based methods are subdivided into intensity and contrast transformations, local segmentation-related, anatomy-guided, global density-guided, and artificial intelligence/deep learning-based. The atlas/template-based methods are subdivided into intensity templates and atlases with three atlas types: anatomy atlases, vascular atlases, and lesion-derived atlases. The treatment procedures for arterial and venous strokes include intravenous and intraarterial thrombolysis and mechanical thrombectomy. This work captures the stateoftheart in stroke management summarized in the form of comprehensive and straightforward taxonomy diagrams. All three introduced taxonomies in diagnostic imaging, image processing and analysis, and treatment are widely illustrated and compared against other state-of-the-art classifications.

Ultrasound Elastography: Methods, Clinical Applications, and Limitations: A Review Article

Ultrasound is a highly adaptable medical imaging modality that offers several applications and a wide range of uses, both for diagnostic and therapeutic purposes. The principles of sound wave propagation and reflection enable ultrasound imaging to function as a highly secure modality. This technique facilitates the production of real-time visual representations, thereby assisting in the evaluation of various medical conditions such as cardiac, gynecologic, and abdominal diseases, among others. The ultrasound modality encompasses a diverse range of modes and mechanisms that serve to enhance the methodology of pathology and physiology assessment. Doppler imaging and US elastography, in particular, are two such techniques that contribute to this expansion. Elastography-based imaging methods have attracted significant interest in recent years for the non-invasive evaluation of tissue mechanical characteristics. These techniques utilize the changes in soft tissue elasticity in various diseases to generate both qualitative and quantitative data for diagnostic purposes. Specialized imaging techniques collect data by identifying tissue stiffness under mechanical forces such as compression or shear waves. However, in this review paper, we provide a comprehensive examination of the fundamental concepts, underlying physics, and limitations associated with ultrasound elastography. Additionally, we present a concise overview of its present-day clinical utilization and ongoing advancements across many clinical domains.

Evaluating the reliability of the lateral femoral condyle measuring methods by different modalities for patients with lateral patellar dislocation

BackgroundA variety of measurement methods and imaging modalities are in use to quantify the morphology of lateral femoral condyle (LFC), but the most reliable method remains elusive in patients with lateral patellar dislocation (LPD). The purpose of this study was to determine the intra- and inter-observer reliability of different measurement methods for evaluating the morphology of LFC on different imaging modalities in patients with LPD.MethodsSeventy-three patients with LPD were included. Four parameters for quantifying the morphology of LFC were retrospectively measured by three observers on MRI, sagittal CT image, conventional radiograph (CR), and three-dimensional CT (3D–CT). The intra-class correlation coefficient was calculated to determine the intra- and inter-observer reliability. Bland–Altman analysis was conducted to identify the bias between observers.ResultsThe lateral femoral condyle index (LFCI) showed better intra- and inter-observer reliability on MRI and 3D–CT than on CR and sagittal CT images. The mean difference in the LFCI between observers was lowest on 3D–CT (0.047), higher on MRI (0.053), and highest on sagittal CT images (0.062). The LFCI was associated with the lateral femoral condyle ratio (ρ = 0.422, P = 0.022), lateral condyle index (r = 0.413, P = 0.037), and lateral femoral condyle distance (r = 0.459, P = 0.014). The LFCI could be reliably measured by MRI and 3D–CT.ConclusionThe LFCI could be reliably measured by MRI and 3D–CT. The LFCI was associated with both the height and length of LFC and could serve as a comprehensive parameter for quantifying the morphology of LFC in patients with LPD.

Ultrasonography is an effective method for evaluating hepatosplenic fungal infections in pediatric onco-hematological patients.

This prospective study assessed the value of ultrasonography (US) in the evaluation of hepatosplenic fungal infections (HSFI). Thirty-two pediatric participants with confirmed onco-hematological diseases and HSFI were included. Lesions in the liver and/or spleen were detected by US, magnetic resonance imaging (MRI), or computed tomography (CT). Of the participants, 11 (34%) had confirmed HSFI, while 21 (66%) had highly suspected HSFI. The US, CT, MRI, and fungal blood cultures demonstrated positive results in 31, 19, 25, and 7 patients, respectively. US had a significantly higher detection rate than CT, MRI, and fungal blood cultures (p < 0.05). The "bull's eye" phenomenon was a distinctive US feature of HSFI. Follow-up examinations indicated that after a mean of 7.7 (1-15) months, liver and/or spleen lesions disappeared in five patients. The lesion was significantly smaller in 10 patients. Residual calcifications were detected in 15 patients. Two patients died. Conclusively, the US may substitute for tissue biopsy, other imaging modalities, or fungal blood culture for the confirmation of HSFI, and may guide better antifungal treatment, thus achieving better outcomes.

Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN) for cross-modal individual analysis of the whole brain

Cross-modal analysis of the same whole brain is an ideal strategy to uncover brain function and dysfunction. However, it remains challenging due to the slow speed and destructiveness of traditional whole-brain optical imaging techniques. Here we develop a new platform, termed Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN), for non-destructive, high-speed, 3D imaging of ex vivo rodent, ferret, and non-human primate brains. Using an optimally designed image acquisition scheme and an accompanying machine-learning algorithm, PATTERN extracts signals of genetically-encoded probes from photobleaching-based temporal modulation and enables reliable visualization of neural projection in the whole central nervous system with 3D isotropic resolution. Without structural and biological perturbation to the sample, PATTERN can be combined with other whole-brain imaging modalities to acquire the whole-brain image with both high resolution and morphological fidelity. Furthermore, cross-modal transcriptome analysis of an individual brain is achieved by PATTERN imaging. Together, PATTERN provides a compatible and versatile strategy for brain-wide cross-modal analysis at the individual level.

Radiological imaging and intervention in women’s health

Women’s health conditions are commonly encountered in primary care. Radiological imaging is now more available in primary care. Knowing who to refer for which investigation and interpreting results can be a daunting task for clinicians. This article considers the imaging modalities used in more detail and applies this knowledge to commonly encountered symptoms and pathologies, thereby offering guidance on the use and interpretation of imaging in primary care.