The ALBI score is readily derived from a blood test without using those factors evaluated subjectively or obtained by invasive procedures. It is an independent prognostic factor for PBC patients and provides better/similar prognostic performance compared with other prognostic scores.

BackgroundThere has been increasing interest in en bloc resection of bladder tumour (ERBT) as an oncologically non-inferior alternative to transurethral resection of bladder tumour (TURBT) with fewer complications and better histology specimens. However, there is a lack of robust randomised controlled trial (RCT) data for making recommendations. ObjectiveWe aimed to develop a consensus statement to standardise various aspects of ERBT for clinical practice and to guide future research. Design, Setting and ParticipantsWe developed the consensus statement on ERBT using a modified Delphi method.First, two systematic reviews were performed to investigate the clinical effectiveness of ERBT versus TURBT (effectiveness review), and to identify areas of uncertainty in ERBT (uncertainties review). Next, 200 health care professionals (urologists, oncologists and pathologists) with experience in ERBT were invited to complete a two-round Delphi survey. Finally, a 16-member consensus panel meeting was held to review, discuss and re-vote on the statements as appropriate. Outcome Measurements and Statistical AnalysisMeta-analyses were performed for RCT data in the effectiveness review. Consensus statements were developed from the uncertainties review. Consensus was defined as:(1) ≥70% scoring a statement 7-9 AND ≤15% scoring the statement 1-3 (consensus agree); OR (2) ≥70% scoring a statement 1-3 AND ≤15% scoring the statement 7-9 (consensus disagree). Results and LimitationsA total of 10 RCTs were identified upon systematic review. ERBT had a shorter irrigation time (mean difference -7.24 hours, 95% CI -9.29 --5.20, I 2 =85%, p<0.001) and lower rate of bladder perforation (Risk ratio [RR] 0.30, 95% CI 0.11-0.83, I 2 =1%, p=0.02) than TURBT, both with moderate certainty of evidence. There were no significant differences in recurrences at 0-12 months, 13-24 months or 25-36 months (all very low certainty of evidence). A total of 103 statements were developed and 99

BACKGROUND The current diagnosis and monitoring of bladder cancer are heavily reliant on cystoscopy, an invasive and costly procedure. Previous efforts in urine-based detection of bladder cancer focused on targeted approaches that are predicated on the tumor expressing specific aberrations. We aimed to noninvasively detect bladder cancer by the genome-wide assessment of methylomic and copy number aberrations (CNAs). We also investigated the size of tumor cell-free (cf)DNA fragments. METHODS Shallow-depth paired-end genome-wide bisulfite sequencing of urinary cfDNA was done for 46 bladder cancer patients and 39 cancer-free controls with hematuria. We assessed (a) proportional contribution from different tissues by methylation deconvolution, (b) global hypomethylation, (c) CNA, and (d) cfDNA size profile. RESULTS Methylomic and copy number approaches were synergistically combined to detect bladder cancer with a sensitivity of 93.5% (84.2% for low-grade nonmuscle-invasive disease) and a specificity of 95.8%. The prevalence of methylomic and CNAs reflected disease stage and tumor size. Sampling over multiple time points could assess residual disease and changes in tumor load. Muscle-invasive bladder cancer was associated with a higher proportion of long cfDNA, as well as longer cfDNA fragments originating from genomic regions enriched for tumor DNA. CONCLUSIONS Bladder cancer can be detected noninvasively in urinary cfDNA by methylomic and copy number analysis without previous knowledge or assumptions of specific aberrations. Such analysis could be used as a liquid biopsy to aid diagnosis and for potential longitudinal monitoring of tumor load. Further understanding of the differential size and fragmentation of cfDNA could improve the detection of bladder cancer.

Rapid and high‐resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational high‐throughput autofluorescence microscopy by pattern illumination (CHAMP). With the assistance of computational microscopy, CHAMP enables high‐throughput and label‐free imaging of thick and unprocessed tissues with large surface irregularity at an acquisition speed of 10 mm2/10 s with 1.1‐µm lateral resolution. Moreover, the CHAMP image can be transformed into a virtually stained histological image (Deep‐CHAMP) through unsupervised learning within 15 s, where significant cellular features are quantitatively extracted with high accuracy. The versatility of CHAMP is experimentally demonstrated using mouse brain/kidney and human lung tissues prepared with various clinical protocols, which enables a rapid and accurate intraoperative/postoperative pathological examination without tissue processing or staining, demonstrating its great potential as an assistive imaging platform for surgeons and pathologists to provide optimal adjuvant treatment.