OBJECTIVE: To assess the diagnostic accuracy of fluorine-18 fluorodeoxyglucose positron emission tomography and computed tomography (18FDG-PET/CT) in detecting second primary malignancies (SPMs) in patients with treatment naïve head and neck squamous cell carcinoma (HNSCC).
METHODS: Medline, Embase, Cochrane Library, and Scopus searched from 1946 to December 2022.
METHODS: Studies reporting the performance of 18FDG-PET/CT in patients with treatment-naïve, index HNSCC for detection of SPMs were included. The reference standard was histopathology, clinical follow-up over the duration of study, and other imaging modalities. Multiple investigators completed depth full-text analysis. Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines were followed. Methodologic and diagnostic accuracy data were abstracted independently by multiple investigators. Risk of bias assessment was conducted using the Quality Assessment of Diagnostic Accuracy Studies tool independently. Bivariate random-effects model meta-analysis and multivariable meta-regression modeling were used.
RESULTS: Seventeen studies examining 4624 patients with a total of 475 SPMs were included in the final analysis. Eleven studies were found to be at low risk for bias, while the rest were in the high-risk category. 18FDG-PET/CT demonstrated pooled sensitivity and specificity of 0.73 (95% confidence interval [CI]: 0.49-0.88) and 0.99 (95% CI: 0.98-1.00) in detecting SPMs. Further subsite analysis revealed varied diagnostic performance across different anatomical regions, with sensitivity and specificity of esophageal SPMs being 0.47 (0.30-0.64) and 0.99 (0.98-1.00), and sensitivity and specificity of 0.86 (0.73-0.94) and 0.99 (0.98-1.00) for head and neck SPMs. Finally, this imaging modality showed sensitivity and specificity of 0.92 (0.84-0.96) and 0.99 (0.98-1.00) for lung SPMs.
CONCLUSIONS: The findings of this study suggest varied accuracy of 18FDG-PET/CT in detecting SPMs during initial workup for HNSCC, highlighting the importance of screening modalities such as esophagoscopy in high-risk patients.

The congenital Gerbode defect is defined as an abnormal communication between the left ventricle and the right atrium. This review aimed to summarize existing evidence, shed light on the clinical implications, and identify knowledge gaps. The systematic literature search was conducted in the PubMed and Google Scholar medical databases using specifically selected keywords. The inclusion of each publication was assessed according to predefined eligibility criteria based on the PICOM (Population, Phenomenon of Interest, Context, Methodology) schema. Titles and abstracts were screened independently by two authors. Available full-text versions of included publications were reviewed and relevant information was extracted. A total of 78 reports were included. The compilation of all congenital Gerbode defect cases described in the literature revealed a variety of clinical presentations comprising dyspnea, palpitations, growth retardation, and asymptomatology. A suitable multimodal diagnostic approach for newborns consists of auscultation, TTE, and optionally TEE and MRI. Because of its rarity, diversity of findings, unknown pathophysiology, and similarity to more common cardiac diseases, the diagnostic challenge remains significant. To prevent untreated long-term sequelae, early individualized treatment is recommended. Surgical defect closure is preferred to device closure for evidence reasons, although major developments are currently taking place. In conclusion, the congenital Gerbode defect provides a diagnostic challenge for pediatricians to allow early diagnosis and intervention in order to improve patients\' quality of life.

Theranostics, a method that combines targeted therapy and diagnostic imaging, has emerged as a viable route for enhancing cancer treatment, and hybrid nanoparticles (HNPs) are at the forefront of this field. Metallic, polymeric, lipid-based, and silica- based HNPs are studied for targeting and biocompatibility. Using HNPs, chemotherapeutic drugs, small interfering RNA, and therapeutic genes can be given precisely and controlled. This enhances therapeutic efficacy and reduces adverse effects. With fluorescence dyes, MRI contrast agents, and PET tracers, real-time therapy response monitoring is conceivable. A nano platform with therapeutic and diagnostic capabilities holds great promise for personalized medicine and precision oncology. The present study discusses HNPs\' biocompatibility, stability, immunogenicity, and long-term biosafety, which are crucial to the clinical translation of cancer theranostics. Further, in this in- -depth investigation, we investigated the design, synthesis, and multifunctional activities of HNPs for use in cancer theranostics.

Despite the profound impact of endometriosis worldwide, delays in diagnosis and suboptimal surveillance techniques are well-recognised issues. Case studies have reported incidental uptake of 18F-FDG PET tracer in endometriotic lesions. However, the utility of PET imaging as a non-invasive diagnostic tool for endometriosis is currently unclear. The purpose of this systematic review was to summarise the existing evidence and determine the value of available PET scanning techniques in the detection and monitoring of endometriosis. MEDLINE, EMBASE, CENTRAL, SCOPUS and Web of Science were searched from conception to 05/03/23. Eligible studies included participants with a history of known or suspected endometriosis who underwent a PET scan for any indication. All PET tracers and protocols were eligible. Outcomes included correlation of PET tracer uptake with the presence of endometriosis seen at laparoscopy or confirmed on histology, sensitivity of tracer uptake, specificity of tracer uptake, site of lesions with tracer uptake, stage of lesions with tracer uptake, SUVmax of endometriosis lesions and adverse reactions to PET imaging. The protocol for this review was registered with PROSPERO (ID: CRD42023405260). Eight studies describing 110 participants were eligible for inclusion. Six studies assessed 18F-FDG with combined PET-CT, one study assessed 18F-FDG PET alone, and the remaining study assessed PET-CT with an alternative tracer, 68Ga-DOTATATE. For 18F-FDG imaging, the correlation of PET avidity with lesions or sites of endometriosis ranged from 0-55 %. Pre-operative 68Ga-DOTATATE PET-CT detected endometriosis in 33 % of cases. All included studies were cohort studies, six were assessed to have low risk of bias, one with moderate risk and one with high risk of bias. Overall, 18F-FDG PET scanning does not appear to consistently identify endometriotic lesions, and therefore its reliability and usefulness in endometriosis diagnosis is limited. The utility of 68Ga-DOTATATE PET-CT remains uncertain. Findings are constrained by limited available evidence reporting outcomes of PET imaging for endometriosis. Other existing PET tracers with biological plausibility in the detection or monitoring of endometriosis warrant further investigation.

Internal hernias are herniations of abdominal viscera, usually small bowel, through congenital or acquired openings of the peritoneum or mesentery. Congenital hernias may involve anatomic fossae such as the epiploic foramen as well as those related to abnormal peritoneal or mesenteric defects; these include left and right paraduodenal, transomental, transmesenteric, pericecal and broad ligament hernias. Acquired hernias are due to defects in the mesentery or peritoneum, usually resulting from prior surgeries, and include those associated with Roux-en-Y surgery as well as colorectal cancer resections. Internal hernias account for 5.8% of small obstructions. Obstructed internal hernias are considered surgical emergencies due to the high risk of bowel strangulation. This review summarizes the various types of congenital and acquired internal hernias, their relevant anatomy, embryology, associated surgical history and imaging appearance. We will also discuss a location-based approach to identifying internal hernias on CT, as well as complications and relevant signs, of which abdominal imagers should be vigilant.

Diagnosing endometrial carcinoma correctly is essential for appropriate treatment, as it is a major health risk. As machine learning (ML) and artificial intelligence (AI) have grown in popularity, so has interest in their potential to improve cancer diagnosis accuracy. In the context of endometrial cancer, this study attempts to examine the efficacy as well as the accuracy of AI-assisted diagnostic approaches. Additionally, it aims to methodically evaluate the contribution of AI and ML techniques to the improvement of endometrial cancer diagnosis. Following PRISMA guidelines, we performed a thorough search of numerous databases, including Medline via Ovid, PubMed, Scopus, Web of Science, and Google Scholar. Ten years were searched, encompassing both basic and advanced research. Peer-reviewed papers and original research studies that explicitly looked at the application of AI/ML in endometrial cancer diagnosis were the main targets of the well-defined selection criteria. Using the Critical Appraisal Skills Programme (CASP) methodology, two independent researchers conducted a thorough screening process and quality assessment of included studies. The review found a notable inclination towards the effective use of AI in endometrial carcinoma diagnostics, namely in the identification and categorization of endometrial cancer. Artificial intelligence models, particularly Convolutional Neural Networks (CNNs) and deep learning algorithms have shown remarkable precision in detecting endometrial cancer. They frequently achieve or even exceed the diagnostic proficiency of human specialists. The use of artificial intelligence in medical diagnostics signifies revolutionary progress in the field of oncology. AI-assisted diagnostic tools have demonstrated the potential to improve the precision and effectiveness of cancer diagnosis, namely in cases of endometrial carcinoma. This innovation not only enhances the quality of patient care but also indicates a transition towards more individualized and efficient treatment approaches in the field of oncology. The advancement of AI technology is expected to play a crucial role in medical diagnostics, particularly in the field of cancer detection and treatment, perhaps leading to a significant transformation in the approach to these areas.

Radiation dose optimization in radiology is a critical aspect of modern healthcare, aimed at balancing the necessity of diagnostic imaging with the imperative of patient safety. This comprehensive review explores the fundamental principles, techniques, and considerations in optimizing radiation dose to safeguard patients while preserving image fidelity. Beginning with acknowledging the inherent risks associated with medical radiation exposure, the review highlights strategies such as the As Low as Reasonably Achievable (ALARA) principle, technological advancements, and quality assurance measures to minimize radiation dose without compromising diagnostic accuracy. Regulatory guidelines and the importance of patient education and informed consent are also discussed. Through a synthesis of current knowledge and emerging trends, the review underscores the pivotal role of radiation dose optimization in radiology practice. Furthermore, it emphasizes the need for ongoing research and collaboration to advance dose reduction strategies, establish standards for radiation safety, and explore personalized dose optimization approaches. By prioritizing radiation dose optimization, healthcare providers can ensure the highest standards of patient care while minimizing potential risks associated with medical radiation exposure.

OBJECTIVE: Meningioma is the most common intracranial tumor, graded on pathology using WHO criteria to predict tumor course and treatment. However, pathological grading via biopsy may not be possible in cases with poor surgical access due to tumor location. Therefore, our systematic review aims to evaluate whether diagnostic imaging features can differentiate high grade (HG) from low grade (LG) meningiomas as an alternative to pathological grading.
METHODS: Three databases were searched for primary studies that either use routine magnetic resonance imaging (MRI) or computed tomography (CT) to assess pathologically WHO-graded meningiomas. Two investigators independently screened and extracted data from included studies.
RESULTS: 24 studies met our inclusion criteria with 12 significant (p < 0.05) CT and MRI features identified for differentiating HG from LG meningiomas. Cystic changes in the tumor had the highest specificity (93.4%) and irregular tumor-brain interface had the highest positive predictive value (65.0%). Mass effect had the highest sensitivity (81.0%) and negative predictive value (90.7%) of all imaging features. Imaging feature with the highest accuracy for identifying HG disease was irregular tumor-brain interface (79.7%). Irregular tumor-brain interface and heterogenous tumor enhancement had the highest AUC values of 0.788 and 0.703, respectively.
CONCLUSIONS: Our systematic review highlight imaging features that can help differentiate HG from LG meningiomas.

UNASSIGNED: The discoid meniscus (DM) is distinguished by its thickened, disc-shaped formation, which extends over the tibial plateau. The likelihood of developing osteoarthritis escalates if a DM tear remains undiagnosed and untreated. While DM tears can be diagnosed through arthroscopy, the high cost, invasive nature and limited availability of this procedure highlight the need for a better diagnostic modality. This study aims to determine the accuracy of magnetic resonance imaging (MRI) in diagnosing DM tears.
UNASSIGNED: A systematic review was conducted to gather articles with at least 10 cases on the comparison of MRI and arthroscopy as the gold standard for DM tear diagnosis. Stata and MetaDisc were used to conduct the statistical analysis. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.
UNASSIGNED: Five diagnostic performance studies, derived from four original research papers involving 305 patients, were evaluated. Based on the pooled data, the sensitivity, specificity, diagnostic odds ratio, positive limit of detection and negative limit of detection were found to be 0.87 (95% confidence interval [CI], 0.82-0.91) and 0.84 (95% CI, 0.75-0.90), 32.88 (95% CI, 5.81-186.02), 5.22 (95% CI, 1.71-15.92) and 0.18 (95% CI, 0.09-0.38), respectively. A hierarchical summary receiver operating characteristic curve with an area under the curve of 0.92 was generated.
UNASSIGNED: This meta-analysis demonstrates that MRI has excellent sensitivity and specificity for diagnosing DM tears. Despite its lower accuracy compared to arthroscopy, MRI can be used in symptomatic patients as a viable alternative to arthroscopy due to its inherent advantages.
UNASSIGNED: Level IV.

BACKGROUND: The use of diagnostic imaging in low back pain (LBP) management is often inappropriate, despite recommendations from clinical practice guidelines. There is a limited understanding of factors that influence the imaging clinical decision-making (CDM) process.
OBJECTIVE: Explore the literature on factors influencing imaging CDM for people with LBP and consider how these findings could be used to reduce inappropriate use of imaging in LBP management.
METHODS: Scoping review.
METHODS: This review followed the Preferred Reporting Items for Systematic Review extension for scoping reviews. A digital search was conducted in Medline, the Cumulative Index of Nursing and Allied Health Literature, Scopus, and the Cochrane Central Register of Controlled Trials for eligible studies published between January 2010-2023. Data reporting influences on imaging CDM were extracted. Data were then analysed through an inductive process to group the influencing factors into categories.
RESULTS: After screening, 35 studies (5 qualitative and 30 quantitative) were included in the review, which reported factors influencing imaging CDM. Three categories were developed: clinical features (such as red flags, pain, and neurological deficit), non-modifiable factors (such as age, sex, and ethnicity) and modifiable factors (such as beliefs about consequences and clinical practice). Most studies reported non-modifiable factors.
CONCLUSIONS: The results of this scoping review challenge the perception that imaging CDM is purely based on clinical history and objective findings. There is a complex interplay between clinical features, patient and clinician characteristics, beliefs, and environment. These findings should be considered when designing strategies to address inappropriate imaging behaviour.