Can magnetic resonance imaging differentiate muscle invasion (T2) and lamina propria invasion (T1) urothelial carcinoma of the bladder? A systematic review and meta-analysis of Vesical Imaging-Reporting and Data System accuracy

Background

Vesical Imaging-Reporting and Data System (VI-RADS) was developed as a structured reporting tool to anticipate the possibility of muscle invasion. This study is aimed to investigate the diagnostic accuracy of VI-RADS for discriminating T2 from T1 bladder cancer.

Materials and methods

Scopus, Web of Science, PubMed, and Embase were searched on October 4, 2021, for studies with the following characteristics: (1) bladder cancer patient population, (2) VI-RADS as an index test, (3) retransurethral resection of bladder tumor/cystectomy as a reference, and (4) adequate VI-RADS score data for T1 and T2 lesions. The analyses were performed using the binary regression model of MIDAS in Stata.

Results

Six studies with 624 magnetic resonance imaging reports were included. The receiver operating characteristics curve for differentiation of T2 from T1 bladder cancer showed an area under the curve of 0.93 (95% confidence interval [CI], 0.91-0.95) for a VI-RADS ≥3 and 0.75 (95% CI, 0.71-0.79) for a VI-RADS ≥4. A VI-RADS ≥3 showed high sensitivity of 93% (95% CI, 85%-97%), specificity of 61% (95% CI, 30%-86%), positive likelihood ratio of 2.4 (95% CI, 1.1-5.3), and negative likelihood ratio of 0.11 (95% CI, 0.05-0.24). A total of 10.4% of T2 lesions were scored as VI-RADS 2, while 10% of T1 lesions were scored as VI-RADS 4 or 5.

Conclusions

The VI-RADS ≥3 has high accuracy and sensitivity for detecting muscle invasion in borderline populations of T1 or T2 bladder cancer. Thus, the VI-RADS could be a good non-invasive screening test for the detection of T2 urothelial lesions.

The best COVID-19 predictor is recent smell loss: a cross-sectional study

BACKGROUND

COVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19.

METHODS

This preregistered, cross-sectional study used a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified singular and cumulative predictors of COVID-19 status and post-COVID-19 olfactory recovery.

RESULTS

Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both single and cumulative feature models (ROC AUC=0.72), with additional features providing no significant model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ~50% of participants and was best predicted by time since illness onset.

CONCLUSIONS

As smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (10<OR<4), especially when viral lab tests are impractical or unavailable.