A man in his 60s with multiple vascular comorbidities presented with sudden, painless vision loss in one eye. Although he had a high risk for atherosclerotic events, initial evaluation for stroke was negative for acute ischemia, but found to have markedly elevated inflammatory markers. Accordingly, giant cell arteritis was investigated and Ophthalmologic findings and fulfillment of the 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology classification criteria supported the diagnosis of giant cell arteritis, despite a negative temporal artery biopsy. Management included high-dose glucocorticoids and delayed tocilizumab initiation due to the need for multiple vascular surgeries. Vision loss was irreversible, but systemic symptoms resolved and vascular interventions were successful. This case highlights the diagnostic and management complexities of biopsy-negative giant cell arteritis in patients with severe atherosclerotic vascular disease, emphasizing the importance of clinical judgment and established classification criteria when imaging and biopsy results are inconclusive.

The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

The pulmonary characteristics of Staphylococcus aureus (S. aureus) co-infection with respiratory viruses, such as SARS-CoV-2 and influenza virus, are still unclear. Case series: Two patients with methicillin-susceptible S. aureus (MSSA) infection in the lungs co-infected with either SARS-CoV-2 or influenza virus are reported. Case 1 was a 66-year-old woman who was admitted with SARS-CoV-2 infection. Her chest X-ray and computed tomography (CT) showed multiple cavity formations with infiltration shadows, and MSSA was detected from her sputum and blood, suggesting COVID-19-related bacterial pneumonia and pulmonary embolism. No catheters had been used, but she had skin eruptions and a history of SARS-CoV-2 vaccination. Ampicillin/sulbactam (ABPC/SBT) was administered, and she finally improved. Case 2 was an 87-year-old man with a history of atopic dermatitis who was admitted with moderate pneumonia, and influenza virus co-infection was found. He showed multiple cavitary shadows, and MSSA was isolated from both his sputum and blood. He was diagnosed with influenza-related bacterial pulmonary embolism. No catheters had been used, but he had a history of influenza vaccination. He was also treated by ABPC/SBT and finally improved. Conclusions: These cases suggest that MSSA showed affinity to the lungs when co-infected with either SARS-CoV-2 or influenza virus, and it presented as septic emboli without catheter use. We should consider MSSA infection when patients have SARS-CoV-2 or influenza virus co-infection, and multiple cavity formation and skin disorders are seen, even though they were vaccinated and no catheters were used.

Neurodegeneration and aging are pressing issues with significant personal, economic, ethical, and social consequences. However, the underlying biological mechanisms of these conditions remain largely unknown, making the development of effective treatments challenging. The difficulty in early detection and diagnosis of neurodegenerative diseases further compounds the issue. Recent advancements in genetics, genomics, and brain imaging technology hold great promise for improving our understanding of neurodegeneration and aging, as well as the development of personalized medicine and new drugs and therapies. Addressing these challenges will require a multi-disciplinary and collaborative approach from researchers in various fields. This Special Issue offers valuable insights and perspectives on this critical area of research, which can help advance our understanding and improve the health and well-being of our aging population.

Today, the presentation of a three-dimensional model of real-world features is very important and widely used and has attracted the attention of researchers in various fields, including surveying and spatial information systems, and those interested in the three-dimensional reconstruction of buildings. The building is the key part of the information in a three-dimensional city model, so extracting and modeling buildings from remote sensing data is an important step in building a digital model of a city. LiDAR technology due to its ability to map in all three modes of one-dimensional, two-dimensional, and three-dimensional is a suitable solution to provide hyperspectral and comprehensive images of the building in an urban environment. In this review article, a comprehensive review of the methods used in identifying buildings from the past to the present and appropriate solutions for the future is discussed.

Meigs’ syndrome is a rare triad of a benign ovarian fibroma (or fibroma‑like tumor), ascites, and pleural effusion that resolves after tumor resection. A 53‑year‑old multiparous woman presented with progressive exertional dyspnea and right‑sided pleuritic chest pain. Respiratory and cardiac evaluations were initially unrevealing. Bedside assessment identified mild right basal dullness, and point‑of‑care abdominal ultrasound demonstrated mild free fluid and a solid right adnexal mass. Chest radiography confirmed a small right pleural effusion. Without computed tomography and without diagnostic paracentesis or thoracentesis, Meigs’ syndrome was suspected. The patient underwent laparotomy with total abdominal hysterectomy and bilateral salpingo‑oophorectomy. Histopathology confirmed an ovarian fibroma. Postoperatively, symptoms resolved dramatically, and follow‑up imaging demonstrated complete resolution of the pleural effusion and ascites. This case highlights the importance of considering gynecologic etiologies in unexplained pleural effusion and dyspnea, especially when accompanied by abdominal distension or pelvic pressure.

Introduction: Ovarian torsion is a rare gynecological emergency that can result in permanent ovarian loss if not promptly recognized and managed. Cases involving multiple rotations of the ovary are highly unusual and pose a significant risk for ovarian viability. Clinical Description: A 33-year-old P2 woman presented with sudden severe lower abdominal pain. Imaging showed a complex midline adnexal mass, more towards left and mild free fluid with suspected torsion. Emergency laparotomy showed a sixfold torsion of the right ovary with a dermoid cyst. Detorsion and cystectomy were performed with preservation of the ovary. Postoperative recovery was uneventful and histopathology further confirmed a benign dermoid cyst. Discussion: Ovarian torsion with multiple rotations is extremely rare so early recognition and timely surgical intervention enable ovarian salvage even in severe cases. Moreover, Dermoid cysts are the most common predisposing factor. Conclusion: This case highlights the importance of prompt diagnosis and immediate management of ovarian torsion to prevent complications, preserve ovarian integrity and fertility.

Background: The sacroiliac joint (SIJ) plays a crucial role in transmitting axial loads and maintaining pelvic stability. Sacroiliac joint arthropathy (SIJA) accounts for 10%–30% of low back pain cases but remains underrecognized due to overlapping pain referral patterns and nonspecific imaging findings. Diagnosis relies primarily on characteristic pain distribution and provocative maneuvers, with image-guided intra-articular block serving as the diagnostic gold standard. This study aimed to characterize the clinical profile of block-confirmed SIJA, emphasizing referral pain distribution, triggering position, and provocative test responses. Methods: A cross-sectional study was conducted on 98 patients with diagnostic block–confirmed SIJA at Siloam Hospital Lippo Village, Indonesia. Demographic data, referral pain sites, sitting duration, and results of FABER, compression, and distraction tests were analyzed descriptively. Results: The mean age was 52.07 ± 14.17 years, with 72.4% females. Referral pain most frequently involved the lower back (28.6%) and thigh (28.6%), with occasional extension to the groin (8.2%) or calf (4.1%). Over half of patients (55.1%) reported sitting more than six hours daily. Pain was predominantly triggered during sit-to-stand transitions (85.7%) and while sitting (74.5%). SIJ tenderness (98.0%) and FABER positivity (75.5%) were most consistent. Conclusion: The dominant referral pain in SIJA involves the lower back and posterior thigh. Sit-to-stand transition is the most frequent triggering position, while FABER testing demonstrates the highest diagnostic yield among provocative maneuvers. These consistent patterns may serve as practical clinical indicators to improve diagnostic accuracy in suspected SIJ-related pain.

Introduction: Colorectal cancer during pregnancy is a complex and rare condition often presenting with benign gastrointestinal symptoms that overlap with normal pregnancy related changes, leading to delayed or misdiagnosis. Further, hepatic metastases may complicate recognition, especially when initially interpreted as benign lesions such as hemangiomas. So, early identification and management are crucial and remain challenging for optimizing maternal and fetal outcomes. Clinical Description: A case of 39-year-old gravida 5 para 4 at 24 weeks+1 day with chronic hypothyroidism, longstanding anemia and a one year history of epigastric + right upper quadrant pain with suspected hemorrhage from a known liver hemangioma. Further imaging suggested a malignant hepatic lesion where colonoscopy and biopsy confirmed stage IV metastatic colon adenocarcinoma with liver and adrenal metastases. Her condition deteriorated and delivered a stillborn infant at 26 weeks of 780 grams following placental abruption. She continued to decline despite supportive care and died. Conclusion: This case illustrates the diagnostic challenges of colorectal cancer in pregnancy where nonspecific symptoms and inaccurate imaging results contributed to delayed diagnosis. The aggressive nature of the disease emphasizes the importance of prompt diagnosis and integrated care approach to improve both maternal and fetal outcome.