Improving women's health in low-income and middle-income countries. Part II: the needs of diagnostic imaging

The Functional Integrity of the Anterior Cruciate Ligament Can Be Objectively Assessed With the Use of Stress Radiographs: A Systematic Review

Background

Stress radiography is a viable imaging modality that can also be used to assess the integrity of the anterior cruciate ligament (ACL) after primary or secondary injury. Because conventional radiography is relatively easy, affordable, and available worldwide, the diagnostic efficacy of ACL standing, lateral decubitus, and supine stress radiography should be evaluated.

Purpose

To examine the existing literature regarding the application of stress radiography in evaluating the integrity of the ACL.

Study Design

Systematic review; Level of evidence, 3.

Methods

Using the PubMed and MEDLINE databases for relevant articles published between 1980 and the present, a systematic review was conducted to identify evidence related to the radiographic diagnosis or assessment of ACL tears. The literature search was conducted in September 2022.

Results

Of 495 studies, 16 (1823 patients) were included. Four studies examined standing stress radiography, and 12 investigated lateral decubitus or supine stress radiography. Significant heterogeneity in imaging technique and recorded anterior tibial translation was identified. Anterior tibial translation for ACL-injured knees ranged from 1.2 to 10.6 mm for standing stress radiographs and 2.7 to 11.2 mm for supine stress radiographs, with high sensitivities and specificities for both.

Conclusion

Stress radiography was a dependable diagnostic method for identifying ACL rupture. Further research is necessary to determine the ideal anatomic landmarks, optimal patient positioning, and appropriate applied stresses to establish a standardized protocol for both assessing ACL tears and evaluating the postoperative integrity of ACL reconstruction using stress radiography.

Machine learning methods to predict presence of residual cancer following hysterectomy

Surgical management for gynecologic malignancies often involves hysterectomy, often constituting the most common gynecologic surgery worldwide. Despite maximal surgical and medical care, gynecologic malignancies have a high rate of recurrence following surgery. Current machine learning models use advanced pathology data that is often inaccessible within low-resource settings and are specific to singular cancer types. There is currently a need for machine learning models to predict non-clinically evident residual disease using only clinically available health data. Here we developed and tested multiple machine learning models to assess the risk of residual disease post-hysterectomy based on clinical and operative parameters. Data from 3656 hysterectomy patients from the NSQIP dataset over 14 years were used to develop models with a training set of 2925 patients and a validation set of 731 patients. Our models revealed the top postoperative predictors of residual disease were the initial presence of gross abdominal disease on the diaphragm, disease located on the bowel mesentery, located on the bowel serosa, and disease located within the adjacent pelvis prior to resection. There were no statistically significant differences in performances of the top three models. Extreme gradient Boosting, Random Forest, and Logistic Regression models had comparable AUC ROC (0.90) and accuracy metrics (87–88%). Using these models, physicians can identify gynecologic cancer patients post-hysterectomy that may benefit from additional treatment. For patients at high risk for disease recurrence despite adequate surgical intervention, machine learning models may lay the basis for potential prospective trials with prophylactic/adjuvant therapy for non-clinically evident residual disease, particularly in under-resourced settings.

Circulating tight-junction proteins are potential biomarkers for blood-brain barrier function in a model of neonatal hypoxic/ischemic brain injury

Background

Neonatal encephalopathy often leads to lifelong disabilities with limited treatments currently available. The brain vasculature is an important factor in many neonatal neurological disorders but there is a lack of diagnostic tools to evaluate the brain vascular dysfunction of neonates in the clinical setting. Measurement of blood–brain barrier tight-junction (TJ) proteins have shown promise as biomarkers for brain injury in the adult. Here we tested the biomarker potential of tight-junctions in the context of neonatal brain injury.

Methods

The levels of TJ-proteins (occluding, claudin-5, and zonula occludens protein 1) in both blood plasma and cerebrospinal fluid (CSF) as well as blood–brain barrier function via ¹⁴C-sucrose (342 Da) and Evans blue extravasation were measured in a hypoxia/ischemia brain-injury model in neonatal rats.

Results

Time-dependent changes of occludin and claudin-5 levels could be measured in blood and CSF after hypoxia/ischemia with males generally having higher levels than females. The levels of claudin-5 in CSF correlated with the severity of the brain injury at 24 h post- hypoxia/ischemia. Simultaneously, we detected early increase in blood–brain barrier-permeability at 6 and 24 h after hypoxia/ischemia.

Conclusions

Levels of circulating claudin-5 and occludin are increased after hypoxic/ischemic brain injuries and blood–brain barrier-impairment and have promise as early biomarkers for cerebral vascular dysfunction and as a tool for risk assessment of neonatal brain injuries.

A phased approach to implementing the Breast Imaging Reporting and Data System (BI-RADS) in low-income and middle-income countries

BACKGROUND

Successful breast cancer detection programs rely on standardized reporting and interpreting systems, such as the Breast Imaging Reporting and Data System (BI-RADS), to improve system performance. In low-income and middle-income countries, evolving diagnostic programs have insufficient resources to either fully implement BI-RADS or to periodically evaluate the program's performance, which is a necessary component of BI-RADS. This leads to inconsistent breast ultrasound interpretation and a failure to improve performance.

METHODS

The authors applied the Breast Health Global Initiative's phased implementation strategy to implement diagnostic ultrasound and BI-RADS within the context of a limited-resource setting.

RESULTS

The authors recommended starting with triage ultrasound to distinguish suspicious masses from normal breast tissue and benign masses such as cysts because the majority of health workers performing ultrasounds at this level have minimal breast imaging experience. Transitioning to full diagnostic ultrasound with condensed or full BI-RADS should occur after performance and quality metrics have been met.

CONCLUSIONS

Transitioning through these phases across facilities likely will occur at different times, particularly in rural versus urban settings.