Test Images Research Articles

Ultrasound Imaging in Diagnosis and Management of Lower Limb Injuries: A Comprehensive Review.

Medical imaging tests are widely used to diagnose a broad spectrum of lower-limb injuries. Among these modalities, ultrasound (US) imaging has gained significant traction as a valuable diagnostic instrument for assessing conditions primarily affecting muscles, tendons, ligaments, and other soft tissues. However, there are important dilemmas related to the indications and possibilities of US in lower-limb injuries. Conflicting findings and approaches raise questions regarding the validity, accuracy, and usefulness of the US in that area. This narrative review attempts to summarize the current state of knowledge regarding US imaging of lower-limb injuries. The study provides a detailed discussion of the existing literature and contemporary insights on the diagnosis of lower-limb injuries using US examination, and draws attention to the role of the US in interventional procedures and monitoring of the healing process. The characteristics of normal muscles, tendons, and ligaments in US imaging are presented, along with the most commonly documented conditions affecting these tissues. Furthermore, the benefits and justifications for employing US in interventional procedures are discussed, ranging from platelet-rich plasma injections to physiotherapeutic treatments like percutaneous electrolysis. The study was further augmented with US pictures depicting various lower-limb injuries, mainly affecting young athletes. This article aims to review the role of US imaging in the diagnosis and management of common lower-limb injuries.

INTRAMUSCULAR MYXOMA OF THE VASTUS LATERALIS MUSCLE: A CASE REPORT

Introduction: Intramuscular myxoma is a rare benign soft tissue tumor which usually affects large muscle groups in patients aged between forty and sixty years. It is composed of hypocellular myxoid tissue. Incidence of intramuscular myxoma varies from 0.1 to 0.3 per 100,000 individuals. The aim of this study: to present the process of diagnosis and treatment of a patient with the rare soft tissue tumor. Case description: A 41-year-old female came to the Orthopedic Clinic with a 2-year history of a lump on the lateral side of her right thigh. Noticeable growth of the lesion and pain complaints started after skiing injury 7 months before the examination. The magnetic resonance imaging test demonstrated encapsulated intramuscular mass which measured 6 x 2 x 2 cm located in Vastus lateralis muscle. Due to an increasing pain and a significant size of the lesion, the patient was qualified for an excisional biopsy. After an excision, the lesion was found on histopathology to be an intramuscular myxoma. The patient did not complain of any neurological deficits, walking disorders. The follow-up imaging examination 3 months after surgery show no recurrence and the further observation was planned.

Nationwide prospective audit for the evaluation of appendicitis risk prediction models in adults: right iliac fossa treatment (RIFT)-Turkey.

Appendicitis is the most prevalent surgical emergency. The negative appendicectomy rate and diagnostic uncertainty are important concerns. This study aimed to assess the effectiveness of current appendicitis risk prediction models in patients with acute right iliac fossa pain. A nationwide prospective observational study was conducted, including all consecutive adult patients who presented with right iliac fossa pain. Diagnostic, clinical and negative appendicectomy rate data were recorded. The Alvarado score, Appendicitis Inflammatory Response (AIR), Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA) and Adult Appendicitis Score systems were calculated with collected data to classify patients into risk categories. Diagnostic value and categorization performance were evaluated, with use of risk category-based metrics including 'true positive rate' (percentage of appendicitis patients in the highest risk category), 'failure rate' (percentage of patients with appendicitis in the lowest risk category) and 'categorization resolution' (true positive rate/failure rate). A total of 3358 patients from 84 centres were included. Female patients were less likely to undergo surgery than men (71.5% versus 82.5% respectively; relative risk 0.866, 95% c.i. 0.834 to 0.901, P < 0.001); with a three-fold higher negative appendicectomy rate (11.3% versus 4.1% respectively; relative risk 2.744, 95% c.i. 2.047 to 3.677, P < 0.001). Ultrasonography was utilized in 56.8% and computed tomography in 75.2% of all patients. The Adult Appendicitis Score had the best diagnostic performance for the whole population; however, only RIPASA was significant in men. All scoring systems were successful in females patients, but Adult Appendicitis Score had the highest area under the receiver operating characteristic curve value. The RIPASA and the Adult Appendicitis Score had the best categorization resolution values, complemented by their exceedingly low failure rates in both male and female patients. Alvarado and AIR had extremely high failure rates in men. The negative appendicectomy rate was low overall, but women had an almost three-fold higher negative appendicectomy rate despite lower likelihood to undergo surgery. The overuse of imaging tests, best exemplified by the 75.2% frequency of patients undergoing computed tomography, may lead to increased costs. Risk-scoring systems such as RIPASA and Adult Appendicitis Score appear to be superior to Alvarado and AIR.

LEVERAGING DEEP LEARNING FOR IMPROVED CYCLONE FORCASTING

Tropical cyclones (TCs) are frequently rarest but one of the foremost dangerous weather phenomena to arise over tropical oceans, usually creating huge issues with nearly ninety storms globally annually. Early detection and monitoring of TCs are necessary for the early warning of areas in danger. Since these storms originate over the open ocean and frequently out at sea many miles of continental regions, they are detected using remote sensing. In this paper, we propose an automatic method to identify the formation of TCs through satellite images combining a deep learning architecture. The methodology is based on a two-stage deep learning framework: Mask CNN as detector stage—second wind speed filter and lastly Convolutional Neural Network (CNN) for classification. The best possible performance is obtained by hyperparameter optimization using Bayesian Optimization across the pipeline. Results show that the proposed method achieves a precision, specificity, and accuracy of 97.10%, 97.59%, and 86.55% in test images respectively KEYWORDS— Convolutional Neural Networks (CNN), Deep Learning, Cyclone Detection and Tracking, Tropical cyclone Intensity.

Automated classification of mandibular canal in relation to third molar using CBCT images

Background Dental radiology has significantly benefited from cone-beam computed tomography (CBCT) because of its compact size and low radiation exposure. Canal tracking is an important application of CBCT for determining the relationship between the inferior alveolar nerve and third molar. Usually, canal tacking is performed manually, which takes a lot of time. This study aimed to develop an artificial intelligence (AI) model to automate classification of the mandibular canal in relation to the third molar. Methods This retrospective study was conducted using 434 CBCT images. 3D slicer software was used to annotate and classify the data into lingual, buccal, and inferior categories. Two convolution neural network models, AlexNet and ResNet50, were developed to classify this relationship. The study included 262 images for training and 172 images for testing, with the model performance evaluated by sensitivity, precision, and F1 score. Results The performance of the two models was evaluated using a 3 × 3 confusion matrix, with the data categorized into 3 clases: lingual, buccal, and inferior. The mandibular canal and third molar have a close anatomical relationship, highlighting the need for precise imaging in dental and surgical settings. To accurately classify the mandibular canal in relation to the third molar, both AlexNet and ResNet50 demonstrated high accuracy, with F1 scores ranging from 0.64 to 0.92 for different classes, with accuracy of 81% and 83%, respectively, for accurately classifying the mandibular canal in relation to the third molar. Conclusion The present study developed and evaluated AI models to accurately classify and establish the relationship between the mandibular canal and third molars using CBCT images with a higher accuracy rate.

Comparison and evaluation of YOLO models for vehicle detection on bicycle paths

&lt;p&gt;Non-permitted vehicles have taken over bicycle lanes in various Latin American cities as an alternative escape from traffic. Still, they do not foresee the risk to which they expose users of smaller vehicles, such as cyclists. Technological advancement has made researchers use deep learning (DL) to solve various problems in a city's traffic. However, no research has been found focusing on any issue of vehicles allowed or prohibited to travel on a bicycle lane. Therefore, in this article, the you only look once (YOLO) algorithm was used, taking the lightest models from the YOLOv4 to the most recent version, YOLOv8, to detect 05 classes of vehicles that transit or interfere in a bicycle lane, such as bicycles (Bi), motorcycles (Mo), electric motorcycles (ME), electric scooters (SE) and motorcycle cabs (Mt). When testing with the test images, the YOLOv8m model in 50 epochs, using a batch size of 32 and SGD optimizer, was the most optimal, obtaining F1 results with 88.00%, mAP@0:50 of 94.80% and mAP@0.50:0.95 of 76.60%, also had a training time of 1:28h using a Nvidia T4 GPU from Google Colab.&lt;/p&gt;

Prevalence and management of castration-resistant prostate cancer of unknown metastatic status in the real-world setting: The AfroDiTA study

BackgroundEarly identification and management of metastases in prostate cancer (PC) patients is crucial. This study aimed to describe the nonpharmacological management and characteristics of patients with castration-resistant PC with unknown metastatic status (CRPC-MX) and estimate their prevalence in Spain. MethodsCross-sectional, multicenter, real-world study including adult (≥18 years) CRPC-MX patients from 46 Urology services. In a first phase, patients on continuous ADT for ≥6 months were screened and classified as hormone-sensitive PC (HSPC), castration-resistant PC (CRPC), and unknown hormonal status, with metastases (M1), without (M0) and unknown metastatic status (MX) using an ad hoc designed algorithm. In Phase 2, 15 months (m) after Phase 1, all patients on ADT were reviewed and reclassified again using the algorithm. ResultsAmong 6169 eligible PC patients, 294 (4.8%) were classified as CRPC-MX, which decreased to 179 of 4050 (4.4%) 15 m after study initiation. We included 103 CRPC-MX patients with a median age at diagnosis of 75.4 years (IQR: 67.8, 80.4); 26 (25.2%) lacked a histological diagnosis, and only 25 (24.5%) received treatment with curative intent, despite ECOG being ≤1 at inclusion in 83.5%. In the 15 m before inclusion, most CRPC-MX patients had <5 prostate-specific antigen (PSA) determinations (80.6%) and no imaging (63.1%). After CRPC-MX identification (15 m after inclusion), metastatic status was assessed in 55.4%, with an increased number of patients with ≥5 PSA determinations (P = 0.0357), visits per patient (P < 0.0001), patients with some imaging test (P < 0.0001), imaging tests/patient (P < 0.0001), and visits to onco-urology specialized consultation units (52.0% before and 79.2% after). ConclusionA substantial proportion of PC patients on ADT in the real-world setting are not appropriately followed up. Identification of CRPC-MX patients raised awareness among physicians and improved their adherence to guidelines, resulting in improved care for these patients.

Maternal and Neonatal Outcomes in Pregnant Women With Chronic Hypertension: A Retrospective Study of 50 Cases.

Background Chronic hypertension (CHTN) has been associated with significant maternal and neonatal complications. The goal of this research study is to assess outcomes and management strategies among pregnant women living with CHTN. Methods From December 2019 to December 2020, 50 pregnant women diagnosed with CHTN before or at 20 weeks gestation at Cure International Hospital, Kabul, Afghanistan, underwent retrospective analysis using data obtained from patient records, such as demographic details, clinical history notes, laboratory test findings, imaging results, management protocols, and maternal and neonatal outcomes. Results Of the 50 patients, 17 (34%) developed superimposed preeclampsia. Maternal complications included superimposed preeclampsia in 17 (34%), placental abruption in 14 (28%), gestational diabetes in 15 (30%), and acute kidney injury in one (2%). Neonatal complications included preterm birth (12; 24%), low birth weight (12; 24%), small for gestational age (10; 20%), and perinatal mortality (5; 10%). Management strategies revealed that 38 (75%) patients received labetalol, while 12 (25%) were treated with methyldopa. Conclusions CHTN during gestation can result in significant maternal and neonatal complications, and adherence to management guidelines is critical to improve outcomes. More studies are necessary to develop optimal treatment protocols and preventive measures.

Differentiating Definite and Probable Ménière Disease: A Comprehensive Evaluation of Audio-Vestibular Function Testing Combined with Inner Ear MRI.

To evaluate the differences between audio-vestibular function testing and inner ear gadolinium magnetic resonance imaging (MRI) in distinguishing definite Ménière disease (DMD) and probable Ménière disease (PMD), and to provide a reference for early clinical diagnosis and intervention. A total of 116 patients diagnosed with DMD (n = 80) and PMD (n = 36) were enrolled. The differences in the results of pure tone audiometry, caloric test, and tympanic injection of gadolinium for contrast-enhanced MRI between the two groups were compared and analyzed. Parameters that could differentiate between the two conditions were identified, and the sensitivity and specificity and the area under the curve (AUC) of individual and combined indices in the differential diagnosis of DMD and PMD were evaluated. The hearing threshold and hearing asymmetry rate of the DMD group were significantly higher than those of the PMD group (p < 0.001), 98.8% and 30.6%, respectively. The abnormal rates of canal paresis (CP) and severity of endolymphatic hydrops in the DMD group were higher than those in the PMD group (p < 0.05). When combined with high-frequency hearing thresholds, hearing asymmetry, hearing curve type, endolymphatic hydrops, and abnormal CP, the diagnostic accuracy of DMD was improved compared to using high-frequency alone (p < 0.05). This study showed that PMD and DMD may represent two different stages in the development of MD disease. The comprehensive assessment of audio-vestibular function testing and inner ear MRI proves beneficial for early diagnosis, potentially contributing to the preservation of inner ear function.

Femoral version and its clinical relevance in adult hip preservation surgery for developmental dysplasia of the hip.

Femoral version (FV) is more widely adopted with the definition as the angle between the long axis of the femoral neck and the tangent line of the posterior femoral condyles on the axial plane, and the normal range between 5 and 20°. FV can be measured by imaging and functional tests. Cross-sectional CT including both the hip and the knee is the typically used imaging technique, yet variation exists according to the different landmarks used. As MRI investigations are routinely performed preoperatively, and protocols can be easily adopted to include version measurement, they are frequently used as an alternative to CT and offers several advantages. Abnormal FV has adverse effects on the biomechanics and musculoskeletal health of the whole lower limb. It affects the lever arm of muscles and the forces that the hip and patellofemoral joints suffer, and can lead to disorders such as osteoarthritis and impingement. In adult hip preservation surgery for developmental dysplasia of the hip (DDH), abnormal FV is sometimes accompanied by other morphological abnormities of the hip, a more severe DDH, and can help predict postoperative range of motion (ROM), and postoperative impingement. Currently, the most frequently used surgical technique for abnormal FV is femoral derotational osteotomy. Many controversies are left to be solved, including the specific origin of FV, the indication for femoral derotational osteotomy, especially in patients with combined DDH and abnormal FV, and the explicit compensation mechanism of abnormal FV by tibial torsion.

Frontline evaluation: Atezolizumab-bevacizumab versus lenvatinib for BCLC stage B hepatocellular carcinoma exceeding the up-to-seven criteria.

This study aimed to evaluate the efficacy and safety of atezolizumab combined with bevacizumab (Atez/Bev) compared to lenvatinib (LEN) as first-line systemic therapy for patients with Barcelona Clinic Liver Cancer (BCLC) stage B hepatocellular carcinoma (HCC) exceeding the up-to-seven criteria threshold, who are typically unsuitable for transarterial chemoembolization (TACE). A retrospective analysis was conducted on 49 consecutive patients with HCC treated at Tokyo Metropolitan Komagome Hospital between May 2018 and October 2023. The patients were divided into two groups: the Atez/Bev group (21 patients) and the LEN group (28 patients). Eligibility criteria included Child-Pugh A classification, no prior systemic therapy, and ineligibility for resection, ablation, or transplantation. Treatment outcomes were assessed through periodic imaging and laboratory tests, evaluating OS, PFS, ORR, and disease control rate (DCR). Both groups demonstrated comparable baseline characteristics, with a median follow-up of 15.4 months. No significant difference was observed in OS between the Atez/Bev and LEN groups (median OS: 19.80 vs. 22.20 months, p = 0.763). The median PFS was 10.23 months for Atez/Bev and 7.20 months for LEN (p = 0.343). There were no statistically significant differences in ORR or DCR between the two groups. Common adverse events included elevated AST and ALT levels, with no significant difference in the overall rate of adverse events between the groups. Atez/Bev and LEN demonstrated comparable efficacy and safety as first-line systemic treatments for patients with BCLC stage B HCC exceeding the up-to-seven criteria. Both therapeutic options are viable for this population, though further large-scale prospective studies are required to confirm these findings.

Allogenic Vertebral Body Adherent Mesenchymal Stromal Cells Promote Muscle Recovery in Diabetic Mouse Model of Limb Ischemia

Chronic limb threatening ischemia (CLTI) carries a significant risk for amputation especially in diabetic patients with poor options for revascularization. Phase I trials have demonstrated efficacy of allogeneic mesenchymal stromal cells (MSC) in treating diabetic CLTI. Vertebral bone adherent mesenchymal stromal cells (vBA-MSC) are derived from vertebral bodies of deceased organ donors which offer the distinct advantage of providing a 1,000x greater yield compared to that of living donor bone aspiration. This study describes the effects of intramuscular injection of allogenic vBA-MSC in promoting limb perfusion and muscle recovery in a diabetic CLTI mouse model. A CLTI mouse model was created through unilateral ligation of the femoral artery in male polygenic diabetic TALLYHO mice. Treated mice were injected with vBA-MSC into the gracilis muscle of the ischemic limb 7 days post ligation. Gastrocnemius or tibialis muscle was assessed post-mortem for fibrosis by collagen staining, capillary density via immunohistochemistry, and mRNA by quantitative real time PCR. Laser Doppler perfusion imaging and plantar flexion muscle testing were performed to quantify changes in limb perfusion and muscle function. Compared to vehicle control, treated mice demonstrated indicators of muscle recovery including decreased fibrosis, increased perfusion, muscle torque, and angiogenesis. PCR analysis of muscle obtained 7- and 30-days post vBA-MSC injection showed an upregulation in expression of MyoD1 (p = 0.03) and MyH3 (p = 0.008) mRNA representing muscle regeneration, VEGF-A (p = 0.002 ; p = 0.004) signifying angiogenesis as well as IL-10 (p < 0.001), T regulatory cell marker Foxp3 (p = 0.04), and M2-biased macrophage marker Mrc1 (CD206) (p = 0.02). These findings indicate human allogeneic vBA-MSC ameliorate ischemic muscle damage and rescue muscle function. These results in a murine model will enable further studies to develop potential therapies for diabetic CLTI patients.

Study on ultrasonic lamb wave testing technology of honeycomb sandwich structures

Abstract Honeycomb sandwich composite panels have complex structures, large sizes, many types of defects, and significant sound attenuation, which lead to low efficiency and poor sensitivity of ultrasonic non-destructive testing. In the study, a non-linear ultrasonic lamb wave testing technique for honeycomb sandwich composite panels is proposed. Firstly, the anisotropic propagation characteristics and modal structure of lamb waves in honeycomb sandwich composite panels are analyzed, and the lamb wave modes with non-linear ultrasonic accumulation are excited. Secondly, the data extraction method and imaging algorithm of non-linear ultrasonic lamb wave imaging testing are proposed. Finally, an enhanced imaging algorithm is proposed to improve image quality based on the sliding window algorithm. Based on the comparative analysis of air-coupled ultrasonic testing images and metallographic tests, it can be seen that non-linear ultrasonic lamb wave testing signals can be used to characterize the damage distribution characteristics of honeycomb sandwich composite panels, display debonding and weak debonding defects, and have the advantages of being able to perform on the same side testing and high efficiency, which can be used for non-destructive testing of honeycomb sandwich composite panels.

Adenomas hipofisarios no funcionantes. Incidentaloma hipofisario

Non-functioning pituitary adenomas (NFPAs) are tumors of the pituitary gland that are usually benign and show no clinical or biochemical signs of excessive hormone production. These tumors manifest clinically when they are large enough to exert pressure on surrounding structures. Among pituitary incidentaloma, NFPAs are the most common, as they are often diagnosed accidentally during imaging tests performed for other reasons. To properly evaluate these tumors and their relationship to other structures, the use of contrast-enhanced MRI is preferred. In addition, it is necessary to perform a hormonal analysis to rule out hormonal alterations and a neuro-ophthalmological examination in those cases in which the adenomas are close to the optic chiasm or cavernous sinuses, or in patients who present vision problems. In cases where the tumors are symptomless, observation is an option. However, transsphenoidal surgery is the first-line treatment for patients with symptoms or large tumors. Other options include radiation therapy and medical treatment with dopaminergic agonists and other drugs that are being explored more recently.

Investigating the use of signal detection information in supervised learning-based image denoising with consideration of task-shift.

Recently, learning-based denoising methods that incorporate task-relevant information into the training procedure have been developed to enhance the utility of the denoised images. However, this line of research is relatively new and underdeveloped, and some fundamental issues remain unexplored. Our purpose is to yield insights into general issues related to these task-informed methods. This includes understanding the impact of denoising on objective measures of image quality (IQ) when the specified task at inference time is different from that employed for model training, a phenomenon we refer to as "task-shift." A virtual imaging test bed comprising a stylized computational model of a chest X-ray computed tomography imaging system was employed to enable a controlled and tractable study design. A canonical, fully supervised, convolutional neural network-based denoising method was purposely adopted to understand the underlying issues that may be relevant to a variety of applications and more advanced denoising or image reconstruction methods. Signal detection and signal detection-localization tasks under signal-known-statistically with background-known-statistically conditions were considered, and several distinct types of numerical observers were employed to compute estimates of the task performance. Studies were designed to reveal how a task-informed transfer-learning approach can influence the tradeoff between conventional and task-based measures of image quality within the context of the considered tasks. In addition, the impact of task-shift on these image quality measures was assessed. The results indicated that certain tradeoffs can be achieved such that the resulting AUC value was significantly improved and the degradation of physical IQ measures was statistically insignificant. It was also observed that introducing task-shift degrades the task performance as expected. The degradation was significant when a relatively simple task was considered for network training and observer performance on a more complex one was assessed at inference time. The presented results indicate that the task-informed training method can improve the observer performance while providing control over the tradeoff between traditional and task-based measures of image quality. The behavior of a task-informed model fine-tuning procedure was demonstrated, and the impact of task-shift on task-based image quality measures was investigated.

Review article about Magnetic Resonance Imaging (MRI)

Magnetic resonance imaging (MRI) is a medical imaging technique that uses a magnetic field and computer-generated radio waves to create detailed images of the organs and tissues in your body. MRI is a noninvasive way for a medical professional to examine the organs, tissues and skeletal system. It produces high-resolution images of the inside of the body that help diagnose a variety of conditions. Because MRI doesn’t use X-rays or other radiation, it’s the imaging test of choice when people will need frequent imaging for diagnosis or treatment monitoring, especially of their brain.

Low dose radioactive iodine ablation therapy (1.11GBq) for differentiated thyroid cancer in Western Turkey

ObjectiveAblation therapy is employed in low-risk differentiated thyroid cancer (DTC) cases to facilitate patient monitoring by reducing thyroglobulin (Tg) levels to measurable levels below after surgery by eliminating residual thyroid tissue. However, there is still uncertainty about the minimum activity dose required for effective ablation. Opting for low-dose [131I]-NaI for ablation offers several advantages for both patients and healthcare services. Particularly in this tumor group with a high life expectancy (approximately 90–95 % at 10 years), [131I]-NaI treatment should not pose a risk to the patient's post-treatment life and should not compromise their quality of life. However, there is a need for a well-defined identification of factors predicting successful ablation. MethodsClinical data, laboratory findings, and imaging tests of 287 patients with low-dose 1110 MBq (30 mCi) [131I]-NaI ablation therapy for DTC were retrospectively reviewed. Post-ablation imaging and laboratory findings categorized ablation success/failure. The successful ablation group was determined according to the excellent response criteria outlined in ATA criteria. Relationships between clinical, pathological findings, biochemical common variables, and treatment failure were analyzed. ResultsAn excellent response was achieved in 77% of the entire group according to ATA criteria post-ablation. Male gender and high Tg levels on the day of ablation (Tg cut-off: 10 ng/mL and 5.35 ng/mL) were associated with unsuccessful ablation. ConclusionsOur results indicate that a 1110MBq (30mCi) ablation dose is sufficient to achieve an excellent response in most low-risk DTC cases 6–12 months later. When selecting the dose for ablation, besides the histological markers mentioned in guidelines and age, we observed that stimulated Tg values and gender may be important in predicting ablation success.

Adenomas hipofisarios y adenomas funcionantes

Functioning pituitary adenomas (FPAs) are the most common pituitary lesions. They represent approximately 15% of all intracranial neoplasms, with prolactinomas accounting for 60% of FPAs. Its clinical manifestations are related to hypersecretion and/or local symptoms due to the tumor's mass effect, such as headache, visual disturbances, and/or hypopituitarism. The main clinical syndromes associated with pituitary hyperfunction include hyperprolactinemia with secondary hypogonadism, acromegaly, Cushing's syndrome, and secondary hyperthyroidism. Diagnosing FPA involves demonstrating an excess in hormone secretion through biochemical tests followed by imaging tests to localize the tumor. Magnetic resonance imaging (MRI) with contrast is the test of choice for this purpose. In regard to treatment, surgery is the first-line option for most FPAs except for prolactinomas, which usually respond well to dopamine agonists.

Protocolo diagnóstico de una lesión ocupante de espacio hipofisaria

Space-occupying pituitary lesions are a common finding in imaging tests performed for the study of diseases not related to the pituitary gland, such as computed tomography (CT) or magnetic resonance imaging (MRI). Its prevalence varies between 10%-38% in radiological studies and 15% in autopsies. They are mostly pituitary adenomas (HA), classified according to size into microadenomas (< 10mm) or macroadenomas (≥ 10mm) and are usually benign and non-functional. Its management requires a multidisciplinary approach, including anamnesis, physical examination, pituitary hormonal profile to rule out hyperfunction or hypofunction, and ophthalmological studies. High-resolution pituitary MRI is the primary tool for evaluating these lesions and their impact on surrounding structures. The differential diagnosis is broad, and includes benign tumors, malignant tumors, cystic lesions, granulomatous diseases, infiltrative diseases, and vascular malformations. The growth of the lesion can compromise vision and even produce optic atrophy. Neuro-ophthalmological evaluation is essential to evaluate the degree of involvement and the indication for surgical treatment.

Intervertebral Cervical Disc Intensity (IVCDI) Detection and Classification on MRI Scans Using Deep Learning Methods

ABSTRACTRadiologists manually interpret magnetic resonance imaging (MRI) scans for the detection of intervertebral cervical disc degeneration, which are often obtained in a primary care or emergency hospital context. The ability of computer models to work with pathological findings and aid in the first interpretation of medical imaging tests is widely acknowledged. Deep learning methods, which are commonly employed today in the diagnosis or detection of many diseases, show great promise in this area. For the detection and segmentation of intervertebral cervical disc intensity, we propose a Mask‐RCNN‐based deep learning algorithm in this study. The provided approach begins by creating an original dataset using MRI scans that were collected from Yozgat Bozok University. The senior radiologist labels the data, and three classes of intensity are chosen for the classification (low, intermediate, and high). Two alternative network backbones are used in the study, and as a consequence of the training for the Mask R‐CNN algorithm, 98.14% and 96.72% mean average precision (mAP) values are obtained with the ResNet50 and ResNet101 architectures, respectively. Utilizing the five‐fold cross‐validation approach, the study is conducted. This study also applied the Faster R‐CNN method, achieving a mAP value of 85.2%. According to the author's knowledge, no study has yet been conducted to apply deep learning algorithms to detect intervertebral cervical disc intensity in a patient population with cervical intervertebral disc degeneration. By ensuring accurate MRI image interpretation and effectively supplying supplementary diagnostic information to provide accuracy and consistency in radiological diagnosis, the proposed method is proving to be a highly useful tool for radiologists.