We depict a unique case of a 39-year-old woman who presented to the emergency department with complaints of right upper quadrant pain. Work-up and a computed tomography (CT) scan revealed acute cholecystitis and the patient underwent laparoscopic cholecystectomy without complication. At this time, an incidental mass was discovered in the subcutaneous fat adjacent to the abdominal wall. The patient returned six months later with progressive, cyclic abdominal pain since her last hospital admission. Initial admission lab work was within normal limits and a urine pregnancy test was negative. Physical exam revealed tenderness around her previous cesarean section scar. Repeat CT revealed an enlarging, spiculated mass adherent to the abdominal wall. After imaging confirmation, the patient underwent complete open surgical excision for the removal of the mass. Post-surgical biopsy confirmed endometrial gland and stroma consistent with abdominal wall endometrioma. The patient was discharged with adjuvant therapy and recommended follow-up with the surgeon and her obstetrician-gynecologist. The radiological diagnosis, guidelines, and decision-making for initiating interventional treatment are discussed in this report. Our purpose in documenting this case is to present a rare diagnosis of an atypical location for an endometrioma on the abdominal wall, in a patient with prior cesarean delivery. Although this patient was treated with open excision, different interventional radiology treatments from radiofrequency ablation and focused ultrasound were discussed. In doing so, we hope to contribute to the systematic literature review on surgical excision as a treatment option for Pfannenstiel incision endometrioma.

Coronavirus disease 2019 (COVID-19) pneumonia has had catastrophic effects worldwide. Radiology, in particular computed tomography (CT) imaging, has proven to be valuable in the diagnosis, prognostication, and longitudinal assessment of those diagnosed with COVID-19 pneumonia. This article will review acute and chronic pulmonary radiologic manifestations of COVID-19 pneumonia with an emphasis on CT and also highlighting histopathology, relevant clinical details, and some notable challenges when interpreting the literature.

Rectal carcinoma with metastasis to skeletal muscle is a rare occurrence. Since 1970, only 30 cases of skeletal muscle metastasis originating from colorectal adenocarcinomas have been documented, underscoring its exceptionally low incidence. Here, we present the case of a middle-aged man who was diagnosed with rectal adenocarcinoma 3 months ago. During examination, a subcutaneous mass was discovered in the left proximal buttock. Histological analysis of a biopsy confirmed that this mass was a metastatic lesion originating from the primary rectal adenocarcinoma.

BACKGROUND: Stercoral colitis (SC) is a rare but potentially life-threatening inflammatory colitis caused by the accumulation of impacted fecal material. Despite reported associations with bowel perforation and high mortality rates, stercoral colitis remains a poorly defined and underrecognized diagnosis in the emergency department (ED).
OBJECTIVE: This review aims to summarize and synthesize existing literature on SC to guide its recognition and management in the ED.
CONCLUSIONS: SC primarily occurs in elderly or bedbound patients with chronic constipation; however, it does occur in younger patients with comorbidities at increased risk for fecal impaction. Patients may present acutely with abdominal pain and distension, but clinical presentation is often nonspecific and varied, and there are no established diagnostic criteria for SC to date. CT is therefore crucial for diagnosis, revealing key findings such as fecaloma, colonic dilatation, and fat stranding. Treatment depends on severity of illness, ranging from manual disimpaction and other conservative measures for most cases, to surgical intervention for complicated cases, such as stercoral perforation.
CONCLUSIONS: SC can be a challenging diagnosis in the ED, often requiring multidisciplinary collaboration. Timely recognition and appropriate treatment are essential to reduce morbidity and mortality associated with this condition. Further research is needed to establish diagnostic criteria and clear management algorithms.

The purpose of this systematic review was to analyze evidence based on existing studies on the ability of initial CT imaging to predict mortality in severe traumatic brain injuries (TBIs) in pediatric patients. An experienced librarian searched for all existing studies based on the inclusion and exclusion criteria. The studies were screened by two blinded reviewers. Of the 3277 studies included in the search, data on prevalence of imaging findings and mortality rate could only be extracted from 22 studies. A few of those studies had patient-specific data relating specific imaging findings to outcome, allowing the data analysis, calculation of the area under the curve (AUC) and receiver operating characteristic (ROC), and generation of a forest plot for each finding. The data were extracted to calculate the sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predicted value (NPV), AUC, and ROC for extradural hematoma (EDH), subdural hematoma (SDH), traumatic subarachnoid hemorrhage (tSAH), skull fractures, and edema. There were a total of 2219 patients, 747 females and 1461 males. Of the total, 564 patients died and 1651 survived; 293 patients had SDH, 76 had EDH, 347 had tSAH, 244 had skull fractures, and 416 had edema. The studies included had high bias and lower grade of evidence. Out of the different CT scan findings, brain edema had the highest SN, PPV, NPV, and AUC. EDH had the highest SP to predict in-hospital mortality.

Since 2020, novel coronavirus pneumonia has been spreading rapidly around the world, bringing tremendous pressure on medical diagnosis and treatment for hospitals. Medical imaging methods, such as computed tomography (CT), play a crucial role in diagnosing and treating COVID-19. A large number of CT images (with large volume) are produced during the CT-based medical diagnosis. In such a situation, the diagnostic judgement by human eyes on the thousands of CT images is inefficient and time-consuming. Recently, in order to improve diagnostic efficiency, the machine learning technology is being widely used in computer-aided diagnosis and treatment systems (i.e., CT Imaging) to help doctors perform accurate analysis and provide them with effective diagnostic decision support. In this paper, we comprehensively review these frequently used machine learning methods applied in the CT Imaging Diagnosis for the COVID-19, discuss the machine learning-based applications from the various kinds of aspects including the image acquisition and pre-processing, image segmentation, quantitative analysis and diagnosis, and disease follow-up and prognosis. Moreover, we also discuss the limitations of the up-to-date machine learning technology in the context of CT imaging computer-aided diagnosis.

Photon-counting computed tomography (CT) is a technology that has attracted increasing interest in recent years since, thanks to new-generation detectors, it holds the promise to radically change the clinical use of CT imaging. Photon-counting detectors overcome the major limitations of conventional CT detectors by providing very high spatial resolution without electronic noise, providing a higher contrast-to-noise ratio, and optimizing spectral images. Additionally, photon-counting CT can lead to reduced radiation exposure, reconstruction of higher spatial resolution images, reduction of image artifacts, optimization of the use of contrast agents, and create new opportunities for quantitative imaging. The aim of this review is to briefly explain the technical principles of photon-counting CT and, more extensively, the potential clinical applications of this technology.

COVID-19, a new respiratory infectious disease, was first reported at the end of 2019, in Wuhan, China. Now, COVID-19 is still causing major loss of human life and economic productivity in almost all countries around the world. Early detection, early isolation, and early diagnosis of COVID-19 patients and asymptomatic carriers are essential to blocking the spread of the pandemic. This paper briefly reviewed COVID-19 diagnostic assays for clinical application, including nucleic acid tests, immunological methods, and Computed Tomography (CT) imaging. Nucleic acid tests (NAT) target the virus genome and indicates the existence of the SARS-CoV-2 virus. Currently, real-time quantitative PCR (qPCR) is the most widely used NAT and, basically, is the most used diagnostic assay for COVID-19. Besides qPCR, many novel rapid and sensitive NAT assays were also developed. Serological testing (detection of serum antibodies specific to SARS-CoV-2), which belongs to the immunological methods, is also used in the diagnosis of COVID-19. The positive results of serological testing indicate the presence of antibodies specific to SARS-CoV-2 resulting from being infected with the virus. Viral antigen detection assays are also important immunological methods used mainly for rapid virus detection. However, only a few of these assays had been reported. CT imaging is still an important auxiliary diagnosis tool for COVID-19 patients, especially for symptomatic patients in the early stage, whose viral load is low and different to be identified by NAT. These diagnostic techniques are all good in some way and applying a combination of them will greatly improve the accuracy of COVID-19 diagnostics.

BACKGROUND: Pneumothorax (PTX) is defined as air in the pleural space and is classified as spontaneous or nonspontaneous (traumatic). Traumatic PTX is a common pathology identified in the emergency department. Traditional management calls for chest x-ray (CXR) diagnosis and large-bore tube thoracostomy, although recent literature supports the efficacy of lung ultrasound (US) and more conservative approaches. There is a paucity of cohesive literature on how to best manage the traumatic PTX.
UNASSIGNED: This review aimed to describe current practices and future directions of traumatic PTX management.
CONCLUSIONS: Lung US has proven to be a potentially more useful tool in the detection of PTX in the trauma bay compared with CXR, and has the potential to become the new gold standard for diagnosing traumatic PTX. Computed tomography remains the ultimate gold standard, although in the setting of trauma, its utility lies more in confirming the presence and measuring the size of a PTX. The traditional mantra calling for large-bore chest tubes as first-line approaches to traumatic PTX is challenged by recent literature demonstrating pigtail catheters as equally efficacious alternatives. In patients with small or occult PTXs, even observation may be reasonable.
CONCLUSIONS: Modern management of the traumatic PTX is shifting toward use of US for diagnosis and more conservative management practices (smaller catheters or observation). Ultimately, this shift is favorable in reducing length of stay, development of complications, and pain in the trauma patient.

OBJECTIVE: The aim of this systematic review was to identify, review, analyze, and summarize available evidence on the accuracy of linear measurements when using maxillofacial cone beam computed tomography (CBCT) specifically in the field of implant dentistry.
METHODS: The search was undertaken in April 2017 in the National Library of Medicine database (Medline) through its online site (PubMed), followed by searches in the Cochrane, EMBASE, ScienceDirect, and ProQuest Dissertation and Thesis databases. The main inclusion criterion for studies was that linear CBCT measurements were performed for quantitative assessment (e.g., height, width) of the alveolar bone at edentulous sites or measuring distances from anatomical structures related to implant dentistry. The studies should compare these values to clinical data (humans) or ex vivo and/or experimental (animal) findings from a \"gold standard.\"
RESULTS: The initial search yielded 2,516 titles. In total, 22 studies were included in the final analysis. Of those, two were clinical and 20 ex vivo investigations. The major findings of the review indicate that CBCT provides cross-sectional images that demonstrate high accuracy and reliability for bony linear measurements on cross-sectional images related to implant treatment. A wide range of error has been reported when performing linear measurements on CBCT images, with both over- and underestimation of dimensions in comparison with a gold standard. A voxel size of 0.3 to 0.4 mm is adequate to provide CBCT images of acceptable diagnostic quality for implant treatment planning.
CONCLUSIONS: CBCT can be considered as an appropriate diagnostic tool for 3D preoperative planning. Nevertheless, a 2 mm safety margin to adjacent anatomic structures should be considered when using CBCT. In clinical practice, the measurement accuracy and reliability of linear measurements on CBCT images are most likely reduced through factors such as patient motion, metallic artefacts, device-specific exposure parameters, the software used, and manual vs. automated procedures.