We recapitulated and validated almost exactly the strong prognostic impact of a grading algorithm proposed recently for squamous cell carcinoma of the lung in OSCC. Our data may pave the way for a prognostically highly relevant future squamous cell carcinoma grading system broadly applicable in the aerodigestive tract.
Purpose To facilitate the transition of MALDI–MS Imaging (MALDI–MSI) from basic science to clinical application, it is necessary to analyze formalin‐fixed paraffin‐embedded (FFPE) tissues. The aim is to improve in situ tryptic digestion for MALDI–MSI of FFPE samples and determine if similar results would be reproducible if obtained from different sites. Experimental Design FFPE tissues (mouse intestine, human ovarian teratoma, tissue microarray of tumor entities sampled from three different sites) are prepared for MALDI–MSI. Samples are coated with trypsin using an automated sprayer then incubated using deliquescence to maintain a stable humid environment. After digestion, samples are sprayed with CHCA using the same spraying device and analyzed with a rapifleX MALDI Tissuetyper at 50 µm spatial resolution. Data are analyzed using flexImaging, SCiLS, and R. Results Trypsin application and digestion are identified as sources of variation and loss of spatial resolution in the MALDI–MSI of FFPE samples. Using the described workflow, it is possible to discriminate discrete histological features in different tissues and enabled different sites to generate images of similar quality when assessed by spatial segmentation and PCA. Conclusions and Clinical Relevance Spatial resolution and site‐to‐site reproducibility can be maintained by adhering to a standardized MALDI–MSI workflow.
We aimed to investigate the overall prevalence and possible factors influencing the occurrence of crossed cerebellar diaschisis after acute middle cerebral artery infarction using whole-brain CT perfusion. A total of 156 patients with unilateral hypoperfusion of the middle cerebral artery territory formed the study cohort; 352 patients without hypoperfusion served as controls. We performed blinded reading of different perfusion maps for the presence of crossed cerebellar diaschisis and determined the relative supratentorial and cerebellar perfusion reduction. Moreover, imaging patterns (location and volume of hypoperfusion) and clinical factors (age, sex, time from symptom onset) resulting in crossed cerebellar diaschisis were analysed. Crossed cerebellar diaschisis was detected in 35.3% of the patients with middle cerebral artery infarction. Crossed cerebellar diaschisis was significantly associated with hypoperfusion involving the left hemisphere, the frontal lobe and the thalamus. The degree of the relative supratentorial perfusion reduction was significantly more pronounced in crossed cerebellar diaschisis-positive patients but did not correlate with the relative cerebellar perfusion reduction. Our data suggest that (i) crossed cerebellar diaschisis is a common feature after middle cerebral artery infarction which can robustly be detected using whole-brain CT perfusion, (ii) its occurrence is influenced by location and degree of the supratentorial perfusion reduction rather than infarct volume (iii) other clinical factors (age, sex and time from symptom onset) did not affect the occurrence of crossed cerebellar diaschisis.
Here, we describe a novel approach that allows pathologists to three-dimensionally analyse malignant tissues, including the tumour-host tissue interface. Our visualization technique utilizes a combination of ultrafast chemical tissue clearing and light-sheet microscopy to obtain virtual slices and 3D reconstructions of up to multiple centimetre sized tumour resectates. For the clearing of tumours we propose a preparation technique comprising three steps: (a) Fixation and enhancement of tissue autofluorescence with formalin/5-sulfosalicylic acid. (b) Ultrafast active chemical dehydration with 2,2-dimethoxypropane and (c) refractive index matching with dibenzyl ether at up to 56 °C. After clearing, the tumour resectates are imaged. The images are computationally post-processed for contrast enhancement and artefact removal and then 3D reconstructed. Importantly, the sequence a–c is fully reversible, allowing the morphological correlation of one and the same histological structures, once visualized with our novel technique and once visualized by standard H&E- and IHC-staining. After reverting the clearing procedure followed by standard H&E processing, the hallmarks of ductal carcinoma in situ (DCIS) found in the cleared samples could be successfully correlated with the corresponding structures present in H&E and IHC staining. Since the imaging of several thousands of optical sections is a fast process, it is possible to analyse a larger part of the tumour than by mechanical slicing. As this also adds further information about the 3D structure of malignancies, we expect that our technology will become a valuable addition for histological diagnosis in clinical pathology.
Purpose Identification of proteolytic peptides from matrix‐assisted laser desorption/ionization (MALDI) imaging remains a challenge. The low fragmentation yields obtained using in situ post source decay impairs identification. Liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) is an alternative to in situ MS/MS, but leads to multiple identification candidates for a given mass. The authors propose to use LC‐MS/MS‐based biomarker discovery results to reliably identify proteolytic peptides from MALDI imaging. Experimental design The authors defined m/z values of interest for high grade squamous intraepithelial lesion (HSIL) by MALDI imaging. In parallel the authors used data from a biomarker discovery study to correlate m/z from MALDI imaging with masses of peptides identified by LC‐MS/MS in HSIL. The authors neglected candidates that were not significantly more abundant in HSIL according to the biomarker discovery investigation. Results The authors assigned identifications to three m/z of interest. The number of possible identifiers for MALDI imaging m/z peaks using LC‐MS/MS‐based biomarker discovery studies was reduced by about tenfold compared using a single LC‐MS/MS experiment. One peptide identification candidate was validated by immunohistochemistry. Conclusion and clinical relevance This concept combines LC‐MS/MS‐based quantitative proteomics with MALDI imaging and allows reliable peptide identification. Public datasets from LC‐MS/MS biomarker discovery experiments will be useful to identify MALDI imaging m/z peaks.
The detection of infratentorial infarctions can be improved by assessing WB-CTP as part of the multimodal stroke workup. However, it remains a diagnostic challenge, especially small volume infarctions in the brainstem are likely to be missed.
Many studies have demonstrated that tissue phenotyping (tissue typing) based on mass spectrometric imaging data is possible; however, comprehensive studies assessing variation and classifier transferability are largely lacking. This study evaluated the generalization of tissue classification based on Matrix Assisted Laser Desorption/Ionization (MALDI) mass spectrometric imaging (MSI) across measurements performed at different sites. Sections of a tissue microarray (TMA) consisting of different formalin-fixed and paraffin-embedded (FFPE) human tissue samples from different tumor entities (leiomyoma, seminoma, mantle cell lymphoma, melanoma, breast cancer, and squamous cell carcinoma of the lung) were prepared and measured by MALDI-MSI at different sites using a standard protocol (SOP). Technical variation was deliberately introduced on two separate measurements via a different sample preparation protocol and a MALDI Time of Flight mass spectrometer that was not tuned to optimal performance. Using standard data preprocessing, a classification accuracy of 91.4% per pixel was achieved for intrasite classifications. When applying a leave-one-site-out cross-validation strategy, accuracy per pixel over sites was 78.6% for the SOP-compliant data sets and as low as 36.1% for the mistuned instrument data set. Data preprocessing designed to remove technical variation while retaining biological information substantially increased classification accuracy for all data sets with SOP-compliant data sets improved to 94.3%. In particular, classification accuracy of the mistuned instrument data set improved to 81.3% and from 67.0% to 87.8% per pixel for the non-SOP-compliant data set. We demonstrate that MALDI-MSI-based tissue classification is possible across sites when applying histological annotation and an optimized data preprocessing pipeline to improve generalization of classifications over technical variation and increasing overall robustness.
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