Abstract Clinical outcome for patients suffering from HPV-negative head and neck squamous cell carcinoma (HNSCC) remains poor. This is mostly due to highly invasive tumors that cause loco-regional ...relapses after initial therapeutic intervention and metastatic outgrowth. The molecular pathways governing the detrimental invasive growth modes in HNSCC remain however understudied. Here, we have established HNSCC patient derived organoid (PDO) models that recapitulate 3-dimensional invasion in vitro. Single cell mRNA sequencing was applied to study the differences between non-invasive and invasive conditions, and in a collective versus single cell invading PDO model. Differential expression analysis under invasive conditions in Collagen gels reveals an overall upregulation of a YAP-centered transcriptional program, irrespective of the invasion mode. However, we find that collectively invading HNSCC PDO cells show elevated levels of YAP transcription targets when compared to single cell invasion. Also, collectively invading cells are characterized by increased nuclear translocation of YAP within the invasive strands, which coincides with Collagen-I matrix alignment at the invasive front. Using gene set enrichment analysis, we identify immune cell-like migratory pathways in the single cell invading HNSCC PDO, while collective invasion is characterized by overt upregulation of adhesion and migratory pathways. Lastly, based on clinical head and neck cancer cohorts, we demonstrate that the identified collective invasion signature provides a candidate prognostic platform for survival in HNSCC. By uncoupling collective and single cell invasive programs, we have established invasion signatures that may guide new therapeutic options.
Endoscopic resection of third-ventricle colloid cysts is technically challenging due to the limited dexterity and visualization provided by neuroendoscopic instruments. Extensive training and ...experience are required to master the learning curve. To improve the education of neurosurgical trainees in this procedure, a synthetic surgical simulator was developed and its realism, procedural content, and utility as a training instrument were evaluated.
The simulator was developed based on the neuroimaging (axial noncontrast CT and T1-weighted gadolinium-enhanced MRI) of an 8-year-old patient with a colloid cyst and hydrocephalus. Image segmentation, computer-aided design, rapid prototyping (3D printing), and silicone molding techniques were used to produce models of the skull, brain, ventricles, and colloid cyst. The cyst was filled with a viscous fluid and secured to the roof of the third ventricle. The choroid plexus and intraventricular veins were also included. Twenty-four neurosurgical trainees performed a simulated colloid cyst resection using a 30° angled endoscope, neuroendoscopic instruments, and image guidance. Using a 19-item feedback survey (5-point Likert scales), participants evaluated the simulator across 5 domains: anatomy, instrument handling, procedural content, perceived realism, and confidence and comfort level.
Participants found the simulator's anatomy to be highly realistic (mean 4.34 ± 0.63 SD) and appreciated the use of actual instruments (mean 4.38 ± 0.58). The procedural content was also rated highly (mean 4.28 ± 0.77); however, the perceived realism was rated slightly lower (mean 4.08 ± 0.63). Participants reported greater confidence in their ability to perform an endoscopic colloid cyst resection after using the simulator (mean 4.45 ± 0.68). Twenty-three participants (95.8%) indicated that they would use the simulator for additional training. Recommendations were made to develop complex case scenarios for experienced trainees (normal-sized ventricles, choroid plexus adherent to cyst wall, bleeding scenarios) and incorporate advanced instrumentation such as side-cutting aspiration devices.
A patient-specific synthetic surgical simulator for training residents and fellows in endoscopic colloid cyst resection was successfully developed. The simulator's anatomy, instrument handling, and procedural content were found to be realistic. The simulator may serve as a valuable educational tool to learn the critical steps of endoscopic colloid cyst resection, develop a detailed understanding of intraventricular anatomy, and gain proficiency with bimanual neuroendoscopic techniques.
Haralick texture features are used to quantify the spatial distribution of signal intensities within an image. In this study, the heterogeneity of proliferation (Ki-67 expression) and immune cells ...(CD45 expression) within tumors was quantified and used to classify histologic characteristics of larynx and hypopharynx carcinomas. Of 21 laryngectomy specimens, 74 whole-mount tumor slides were scored on histologic characteristics. Ki-67 and CD45 immunohistochemistry was performed, and all sections were digitized. The tumor area was annotated in QuPath. Haralick features independent of the diaminobenzidine intensity were extracted from the isolated diaminobenzidine signal to quantify intratumor heterogeneity. Haralick features from both Ki-67 and CD45 were used as input for a principal component analysis. A linear support vector machine was fitted to the first 4 principal components for classification and validated with a leave-one-patient-out cross-validation method. Significant differences in individual Haralick features were found between cohesive and noncohesive tumors for CD45 (angular second motion: P =.03, inverse difference moment: P =.009, and entropy: P =.02) and between the larynx and hypopharynx tumors for both CD45 (angular second motion: P =.03, inverse difference moment: P =.007, and entropy: P =.005) and Ki-67 (correlation: P =.003). Therefore, these features were used for classification. The linear classifier resulted in a classification accuracy of 85% for site of origin and 81% for growth pattern. A leave-one-patient-out cross-validation resulted in an error rate of 0.27 and 0.35 for both classifiers, respectively. In conclusion, we show a method to quantify intratumor heterogeneity of immunohistochemistry biomarkers using Haralick features. This study also shows the feasibility of using these features to classify tumors by histologic characteristics. The classifiers created in this study are a proof of concept because more data are needed to create robust classifiers, but the method shows potential for automated tumor classification.
Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas ...of pathology, requiring considerable expertise, time, and effort. We aimed to analyse the utility of deep learning to preclassify histology of kidney allograft biopsies into three main broad categories (ie, normal, rejection, and other diseases) as a potential biopsy triage system focusing on transplant rejection.
We performed a retrospective, multicentre, proof-of-concept study using 5844 digital whole slide images of kidney allograft biopsies from 1948 patients. Kidney allograft biopsy samples were identified by a database search in the Departments of Pathology of the Amsterdam UMC, Amsterdam, Netherlands (1130 patients) and the University Medical Center Utrecht, Utrecht, Netherlands (717 patients). 101 consecutive kidney transplant biopsies were identified in the archive of the Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany. Convolutional neural networks (CNNs) were trained to classify allograft biopsies as normal, rejection, or other diseases. Three times cross-validation (1847 patients) and deployment on an external real-world cohort (101 patients) were used for validation. Area under the receiver operating characteristic curve (AUROC) was used as the main performance metric (the primary endpoint to assess CNN performance).
Serial CNNs, first classifying kidney allograft biopsies as normal (AUROC 0·87 ten times bootstrapped CI 0·85–0·88) and disease (0·87 0·86–0·88), followed by a second CNN classifying biopsies classified as disease into rejection (0·75 0·73–0·76) and other diseases (0·75 0·72–0·77), showed similar AUROC in cross-validation and deployment on independent real-world data (first CNN normal AUROC 0·83 0·80–0·85, disease 0·83 0·73–0·91; second CNN rejection 0·61 0·51–0·70, other diseases 0·61 0·50–0·74). A single CNN classifying biopsies as normal, rejection, or other diseases showed similar performance in cross-validation (normal AUROC 0·80 0·73–0·84, rejection 0·76 0·66–0·80, other diseases 0·50 0·36–0·57) and generalised well for normal and rejection classes in the real-world data. Visualisation techniques highlighted rejection-relevant areas of biopsies in the tubulointerstitium.
This study showed that deep learning-based classification of transplant biopsies could support pathological diagnostics of kidney allograft rejection.
European Research Council; German Research Foundation; German Federal Ministries of Education and Research, Health, and Economic Affairs and Energy; Dutch Kidney Foundation; Human(e) AI Research Priority Area of the University of Amsterdam; and Max-Eder Programme of German Cancer Aid.
•We present a unique method of correlating in vivo imaging to immunohistochemistry.•3D heatmaps of biomarker presence are created from whole-mount tumor resections.•By registering the 3D heatmaps to ...imaging, we can spatially compare them.•The method provides insight into how well imaging portrays the tumor microenvironment.
In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: Ktrans (transfer constant), Ve (extravascular and extracellular space), and Vi (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm3 voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (rrm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: Ve and Ki-67 (rrm = -0.17, P < .001), Ve and HIF-1α (rrm = -0.12, P < .001), Ktrans and CD45 (rrm = 0.13, P < .001), Vi and CD45 (rrm = 0.16, P < .001), and Vi and Ki-67 (rrm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (rrm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.
Endoscopic third ventriculostomy (ETV) is an effective but technically demanding procedure with significant risk. Current simulators, including human cadavers, animal models, and virtual reality ...systems, are expensive, relatively inaccessible, and can lack realistic sensory feedback. The purpose of this study was to construct a realistic, low-cost, reusable brain simulator for ETV and evaluate its fidelity.
A brain silicone replica mimicking normal mechanical properties of a 4-month-old child with hydrocephalus was constructed, encased in the replicated skull, and immersed in water. Realistic intraventricular landmarks included the choroid plexus, veins, mammillary bodies, infundibular recess, and basilar artery. The thinned-out third ventricle floor, which dissects appropriately, is quickly replaceable. Standard neuroendoscopic equipment including irrigation is used. Bleeding scenarios are also incorporated. A total of 16 neurosurgical trainees (Postgraduate Years 1-6) and 9 pediatric and adult neurosurgeons tested the simulator. All participants filled out questionnaires (5-point Likert-type items) to rate the simulator for face and content validity.
The simulator is portable, robust, and sets up in minutes. More than 95% of participants agreed or strongly agreed that the simulator's anatomical features, tissue properties, and bleeding scenarios were a realistic representation of that seen during an ETV. Participants stated that the simulator helped develop the required hand-eye coordination and camera skills, and the training exercise was valuable.
A low-cost, reusable, silicone-based ETV simulator realistically represents the surgical procedure to trainees and neurosurgeons. It can help them develop the technical and cognitive skills for ETV including dealing with complications.
•This comprehensive systematic review and meta-analysis fulfill an unmet need by deciphering the prognostic role of Tumor Associated Macrophage (TAM) markers (CD68, CD163, CD204, CD206, iNOS, HLA-DR ...and CD11b) in HNSCC.•A low number of CD163+TAMs correlates to better overall survival, disease free survival and progression free survival.•CD163 is potentially a strong prognosticator of survival than CD68.•Limited studies have been conducted on the prognostic role of M1-like TAMs. This could potentially be attributed to the lack of a robust immunohistochemical marker for M1-like TAMs.
Head and neck squamous cell carcinoma (HNSCC) is an immunogenic cancer type, and tumor associated macrophages (TAMs) are a major component of the tumor microenvironment (TME). In this systematic review and meta-analysis, studies assessing tumor infiltration with CD68+, iNOS+, HLA-DR+, CD11b+, CD163+, CD206+, and CD204+TAMs were included, and correlation to survival hazard was studied. A low number of CD68+TAMs correlated to better overall survival (OS) in multivariate analysis (HR 1.36 95 %CI (1.07–1.72) P = .01). CD68+TAMs did not correlate to disease free survival (DFS), disease specific survival (DSS), progression free survival (PFS), or recurrence free survival (RFS). A low number of CD163+TAMs correlated to better OS in uni- and multivariate analysis (resp. HR 2.65 95 %CI (1.57–4.46) P = .01 and HR 2.42 95 %CI (1.72–3.41) P < .001). A low number of CD163+TAMs also correlated to better DFS and PFS, whereas a low number of CD204+TAMs only correlated to PFS. While IHC analysis of pan macrophage marker CD68 and M2-like marker CD163 both show prognostic utility in OS, CD163 is a stronger prognosticator, as indicated by multivariate meta-analysis. CD163+TAMs also correlate to DFS and PFS; outcomes that are more relevant to patients, thus showing promising results for future clinical implementation.
•Removal of oral cancer is safer under general than under local anesthesia.•Tumor resection under general anesthesia is associated with more clean margins.
This study analyzes the influence of the ...surgical setting, i.e. resection under local anesthesia versus resection under general anesthesia, on surgical margins in tumor resection of stage I and II oral squamous cell carcinoma (OSCC).
Retrospective study on tumor resections of stage I or II OSCC performed between 2014 and 2020. Potential predictors associated with surgical margins were identified. Multinomial logistic regression was used to analyze the effect of type of anesthesia on surgical margins, adjusted for potential predictors.
In total, 109 cases were included: 54 tumor resections were performed under local anesthesia and 55 under general anesthesia. Histopathological examination showed 19 clear surgical margins, 54 close surgical margins, and 36 positive surgical margins. Compared to resection under general anesthesia, resection under local anesthesia increased the risk of close margins (adjusted OR = 6.26; 95 %CI 1.66–23.58; p = .01) and positive margins (adjusted OR = 6.81; 95 %Cl 1.70–27.27; p = .01). Tumor resection of the floor of mouth, buccal mucosa, gingiva, retromolar trigone, hard palate, and soft palate had a higher risk of close and positive margins than tumor resection of the tongue. Tumor resection of the tongue under local anesthesia was associated with an increased risk of positive margins compared to resection under general anesthesia.
Tumor resection under local anesthesia of stage I and II OSCC increases the risk of close and positive surgical margins compared to tumor resection under general anesthesia.
•Ultrasound provides good overview of the tongue tumour's extent and deep margin.•Ultrasound-guided surgery leads to a significant increase in free margin status.•Ultrasound-guided surgery halves the ...need for local adjuvant radiotherapy.•An 8 mm margin on ex-vivo US prevents histopathological < 5 mm margins in 76%.
Surgical removal of squamous cell carcinoma of the tongue (SCCT) with tumour-free margin status (≥5 mm) is essential for loco-regional control. Inadequate margins (<5 mm) often indicate adjuvant treatment, which results in increased morbidity. Ultrasound (US)-guided SCCT resection may be a useful technique to achieve more adequate resection margins compared to conventional surgery. This study evaluates the application and accuracy of this technique.
Forty patients with SCCT were included in a consecutive US cohort. During surgery, the surgeon aimed for a 10-mm echographic resection margin, while the tumour border and resection plane were captured in one image. Ex-vivo US measurements of the resection specimen determined whether there was a need for an immediate re-resection. The margin status and the administration of adjuvant treatment were compared those of with a consecutive cohort of 96 tongue cancer patients who had undergone conventional surgery. A receiver operating characteristic analysis was done to assess the optimal margin of ex-vivo US measurements to detect histopathologically inadequate margins.
In the US cohort, the frequency of free margin status was higher than in the conventional cohort (55% vs. 16%, p < 0.001), and the frequency of positive margins status (<1 mm) was lower (5% vs. 15%, respectively, p < 0.001). Adjuvant radiotherapy was halved (10% vs. 21%), and the need for re-resection was comparable (10% vs. 9%). A cut-off value of 8 mm for ex-vivo measurements prevented histopathologically inadequate margins in 76%.
US-guided SCCT resections improve margin status and reduce the frequency of adjuvant radiotherapy.
The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological ...diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.
Companies are introducing algorithms to the market, and questions arise whether the pathology community is ready for artificial intelligence (AI) integration in routine practices. However, concerns regarding AI use in pathology are emerging. This review discusses the pros and cons of introducing AI in diagnostic pathology.
PDF
