Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process

Utility of circulating tumor DNA (ctDNA) for the detection of minimal residual disease (MRD) after curative-intent therapy for patients with localized pancreatic adenocarcinoma (PDAC): A single institution series and meta-analysis

695 Background: PDAC is associated with a high recurrence rate even after curative-intent surgical resection and perioperative chemotherapy. Detection of MRD in this setting can inform prognosis and may be actionable for innovative targeted therapies or additional chemotherapy to improve outcomes. While CA19-9 may detect disease before it is clinically apparent, it lacks specificity and up to 20% of patients (pts) are non-producers. ctDNA has been shown to be useful for MRD detection in other cancers but its utility in PDAC is not established. Methods: Pts with PDAC who had a commercial ctDNA assay (Natera) after completion of all curative-intent therapy (surgery and chemotherapy) in the MRD setting were included. Recurrence and survival data were correlated with the end-of-treatment (EOT) ctDNA result. Published literature and abstracts for studies examining ctDNA for MRD detection in PDAC using the same testing platform were identified. Available data were pooled to determine EOT ctDNA positivity rate, positive and negative predictive values (PPV, NPV), and lead time from a positive ctDNA to documented recurrence. Results: A total of 33 pts had EOT ctDNA samples collected at our institution. At EOT, ctDNA was + in 30.3% (n = 10). At a median follow-up time of 14.3 months, median recurrence free survival (RFS) for + vs negative ctDNA was 3.6 vs 25.1 months (HR = 15.8 [4.7-53.4], p < 0.001). Correlation of +ctDNA with recurrence showed a sensitivity of 52% (10/19), specificity of 100% (14/14), PPV of 100% (10/10) and NPV of 61% (14/23). Our institutional data were then combined with 138 pts reported in 3 prior publications/abstracts, for a total of 171 pts. Median follow-up ranged from 11.9-14.3 months and the overall EOT+ rate was 39% in the pooled cohort. The pooled sensitivity was 67% (49/73), specificity was 83% (81/98), PPV was 74% (49/66) and NPV was 77% (81/105). In each study as well as the pooled analysis, an EOT+ ctDNA was associated with significantly shorter RFS (HR = 8.1-120.5). Among 10 pts at our institution with recurrence, a + ctDNA test was detected after the recurrence 90% of the time, with a median lag-time of 4.70 months after recurrence (range -2.2 to 16.67 months). In the pooled cohort, among the 73 pts with recurrences, the ctDNA test was + before, at the time of, or after the recurrence in 23 (32%), 9 (12%) and 17 (23%) pts respectively; the ctDNA was negative despite recurrence in the remaining 24 (33%) pts. Conclusions: A tumor-informed positive ctDNA test after EOT shows high specificity and PPV for recurrence and is associated with significantly worse RFS in the MRD setting, while sensitivity of the test remains low. When positive, ctDNA assessment provides an opportunity for innovative therapies in the adjuvant setting to improve outcomes for localized PDAC

Genome-wide host methylation profiling of anal and cervical carcinoma.

HPV infection results in changes in host gene methylation which, in turn, are thought to contribute to the neoplastic progression of HPV-associated cancers. The objective of this study was to identify joint and disease-specific genome-wide methylation changes in anal and cervical cancer as well as changes in high-grade pre-neoplastic lesions. Formalin-fixed paraffin-embedded (FFPE) anal tissues (n = 143; 99% HPV+) and fresh frozen cervical tissues (n = 28; 100% HPV+) underwent microdissection, DNA extraction, HPV genotyping, bisulfite modification, DNA restoration (FFPE) and analysis by the Illumina HumanMethylation450 Array. Differentially methylated regions (DMR; t test q0.3) were compared between normal and cancer specimens in partial least squares (PLS) models and then used to classify anal or cervical intraepithelial neoplasia-3 (AIN3/CIN3). In AC, an 84-gene PLS signature (355 significant probes) differentiated normal anal mucosa (NM; n = 9) from AC (n = 121) while a 36-gene PLS signature (173 significant probes) differentiated normal cervical epithelium (n = 10) from CC (n = 9). The CC progression signature was validated using three independent publicly available datasets (n = 424 cases). The AC and CC progression PLS signatures were interchangeable in segregating normal, AIN3/CIN3 and AC and CC and were found to include 17 common overlapping hypermethylated genes. Moreover, these signatures segregated AIN3/CIN3 lesions similarly into cancer-like and normal-like categories. Distinct methylation changes occur across the genome during the progression of AC and CC with overall similar profiles and add to the evidence suggesting that HPV-driven oncogenesis may result in similar non-random methylomic events. Our findings may lead to identification of potential epigenetic drivers of HPV-associated cancers and also, of potential markers to identify higher risk pre-cancerous lesions

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process