Novel imaging techniques for intraoperative margin assessment in surgical oncology: A systematic review

Inadequate margins continue to occur frequently in patients who undergo surgical resection of a tumor, suggesting that current intraoperative methods are not sufficiently reliable in determining the margin status. This clinical demand has inspired the development of many novel imaging techniques that could help surgeons with intraoperative margin assessment. This systematic review provides an overview of novel imaging techniques for intraoperative margin assessment in surgical oncology, and reports on their technical properties, feasibility in clinical practice and diagnostic accuracy. PubMed, Embase, Web of Science and the Cochrane library were systematically searched (2013-2018) for studies reporting on imaging techniques for intraoperative margin assessment. Patient and study characteristics, technical properties, feasibility characteristics and diagnostic accuracy were extracted. This systematic review identified 134 studies that investigated and developed 16 groups of techniques for intraoperative margin assessment: fluorescence, advanced microscopy, ultrasound, specimen radiography, optical coherence tomography, magnetic resonance imaging, elastic scattering spectroscopy, bio-impedance, X-ray computed tomography, mass spectrometry, Raman spectroscopy, nuclear medicine imaging, terahertz imaging, photoacoustic imaging, hyperspectral imaging and pH measurement. Most studies were in early developmental stages (IDEAL 1 or 2a, n = 98); high-quality stage 2b and 3 studies were rare. None of the techniques was found to be clearly superior in demonstrating high feasibility as well as high diagnostic accuracy. In conclusion, the field of imaging techniques for intraoperative margin assessment is highly evolving. This review provides a unique overview of the opportunities and limitations of the currently available imaging techniques

The Tumor Milieu Promotes Functional Human Tumor-Resident Plasmacytoid Dendritic Cells in Humanized Mouse Models

Particular interest to harness the innate immune system for cancer immunotherapy is fueled by limitations of immune checkpoint blockade. Plasmacytoid dendritic cells (pDC) are detected in a variety of solid tumors and correlate with poor clinical outcome. Release of type I interferons in response to toll-like-receptor (TLR)7 and TLR9 activation is the pDC hallmark. Mouse and human pDC differ substantially in their biology concerning surface marker expression and cytokine production. Here, we employed humanized mouse models (HIS) to study pDC function. We performed a comprehensive characterization of transgenic, myeloid-enhanced mouse strains (NOG-EXL and NSG-SGM3) expressing human interleukin-3 (hIL-3) and granulocyte-macrophage colony stimulating factor (GM-CSF) using identical humanization protocols. Only in HIS-NOG-EXL mice sufficient pDC infiltration was detectable. Therefore, we selected this strain for subsequent tumor studies. We analyzed pDC frequency in peripheral blood and tumors by comparing HIS-NOG-EXL with HIS-NOG mice bearing three different ovarian and breast tumors. Despite the substantially increased pDC numbers in peripheral blood of HIS-NOG-EXL mice, we detected TLR7/8 agonist responsive and thus functional pDCs only in certain tumor models independent of the mouse strain employed. However, HIS-NOG-EXL mice showed in general a superior humanization phenotype characterized by reconstitution of different myeloid subsets, NK cells and B cells producing physiologic IgG levels. Hence, we provide first evidence that the tumor milieu but not genetically introduced cytokines defines intratumoral (i.t.) frequencies of the rare pDC subset. This study provides model systems to investigate in vivo pro- and anti-tumoral human pDC functions

Care Pathway Analysis to Inform the Earliest Stages of Technology Development:Scoping Oncological Indications in Need of Innovation

BACKGROUND: Identifying unmet needs for innovative solutions across disease contexts is challenging, but important for directing funding and research efforts and informing early-stage decisions during the innovation process. Our aim was to study the merits of care pathway analysis to scope disease contexts and guide the development of innovative devices. We used oncologic surgery as a case study, for which many intraoperative imaging techniques are under development. METHODS: Care pathway analysis is a mapping process which produces graphical maps of clinical pathways using important outcomes and subsequent consequences. We performed care pathway analyses for glioblastoma, breast, bladder, prostate, renal, pancreatic, and oral cavity cancer. Differences between a 'perfect' care pathway and the current care pathway in terms of percentage of inadequate margins, associated recurrences, quality of life, and 5-year overall survival were calculated to determine unmet needs. Data from the Netherlands cancer registry and literature was used. RESULTS: Care pathway analysis showed that highest percentages of inadequate margins were found in oral cavity cancer(72.5%), glioblastoma(48.7%), and pancreatic cancer(43.9%). Inadequate margins showed the strongest increase in recurrences in oral cavity, and bladder cancer(absolute increases of 43.5% and 41.2%, respectively). Impact on survival was largest for bladder, and oral cavity cancer with positive margins. CONCLUSIONS: Care pathway analysis provides overviews of current clinical paths in multiple indications. Disease contexts can be compared via effectiveness gaps that show the potential need for innovative solutions. This information can be used as basis for stakeholder involvement processes to prioritize care pathways in need of innovation

Validation of a Web-Based Planning Tool for Percutaneous Cryoablation of Renal Tumors

Purpose: To validate a simulation environment for virtual planning of percutaneous cryoablation of renal tumors. Materials and Methods: Prospectively collected data from 19 MR-guided procedures were used for validation of the simulation model. Volumetric overlap of the simulated ablation zone volume (Σ) and the segmented ablation zone volume (S; assessed on 1-month follow-up scan) was quantified. Validation metrics were DICE Similarity Coefficient (DSC; the ratio between twice the overlapping volume of both ablation zones divided by the sum of both ablation zone volumes), target overlap (the ratio between the overlapping volume of both ablation zones to the volume of S; low ratio means S is underestimated), and positive predictive value (the ratio between the overlapping volume of both ablation zones to the volume of Σ; low ratio means S is overestimated). Values were between 0 (no alignment) and 1 (perfect alignment), a value > 0.7 is considered good. Results: Mean volumes of S and Σ were 14.8 cm3 (± 9.9) and 26.7 cm3 (± 15.0), respectively. Mean DSC value was 0.63 (± 0.2), and ≥ 0.7 in 9 cases (47%). Mean target overlap and positive predictive value were 0.88 (± 0.11) and 0.53 (± 0.24), respectively. In 17 cases (89%), target overlap was ≥ 0.7; positive predictive value was ≥ 0.7 in 4 cases (21%) and < 0.6 in 13 cases (68%). This indicates S is overestimated in the majority of cases. Conclusion: The validation results showed a tendency of the simulation model to overestimate the ablation effect. Model adjustments are necessary to make it suitable for clinical use.Peer reviewe