Identification Of Tumor Tissue Research Articles

Retracted: Identification of Tumor Tissue of Origin with RNA-Seq Data and Using Gradient Boosting Strategy

Retracted: Identification of Tumor Tissue of Origin with RNA-Seq Data and Using Gradient Boosting Strategy

What have we learned in fluorescein-guided resection of brain metastases? An update after 79 consecutive cases.

Cerebral metastasis (CM) is the most common malignancy affecting the brain. Individualized treatment of CM still represents a challenge for neuro-oncological teams: in patient eligible for surgery, complete tumor removal is the most relevant predictor of overall survival (OS) and neurological outcome. The development of surgical microscopes harboring specific filter able to elicit the fluorescent response from sodium fluorescein (SF) has facilitated fluorescein-guided microsurgery and the identification of pathological tumor tissue, especially at the tumor margins. In this study, we analyzed the effect of SF on the visualization and resection of a large monoinstitutional cohort of CM. Surgical database of FLUOCERTUM study (Besta Institute, Milan, Italy) was retrospectively reviewed to find CM surgically removed with a fluorescein-guided technique from March 2016 to December 2022. SF was intravenously injected (5 mg/kg) immediately after induction of general anesthesia. Tumors were removed using a microsurgical technique with the YELLOW560 filter (Carl Zeiss Meditec, Oberkochen, Germany). In the most recent cases, biopsies at the tumor margins were performed to evaluate the ability of fluorescein to discriminate between fluorescent and nonfluorescent tissue at the lesion borders. Seventy-nine patients were included; most of them showed a bright, diffuse fluorescent staining that markedly enhanced tumor visibility; 11 melanomas presented a specific faint enhancement of the black pigmented central nodule with high fluorescence at tumor boundaries. Only in a minimal percentage of cases (N.=4-5.1%), fluorescein enhancement was tenuous, thus not providing a significant help during tumor resection. Altogether, in more than 90% of cases, SF was considered useful in the identification of tumoral tissue and in achieving a high rate of CM resection; thus, gross total resection was achieved in 96.2% (N.=76) of patients and in no case the detection of tumor remnants was an unexpected event. The resulted sensitivity and specificity of fluorescein in identifying tumor tissue at the tumor margin was 88.9% with a predictive positive value of 88.9%. No adverse event was registered during the postoperative course. The use of SF is a valuable method for safe fluorescence-guided tumor resection. Our data showed a positive effect of fluorescein-guided surgery on intraoperative visualization during resection of CM, suggesting a role in improving the extent of resection of these lesions.

Dexamethasone suppression for 18F-FDG PET/CT to localize ACTH-secreting pituitary tumors

Background18Fluorine-Fluoro-deoxy-glucose (18F-FDG) positron emission tomography (PET) is widely used for diagnosing various malignant tumors and evaluating metabolic activities. Although the usefulness of 18F-FDG PET has been reported in several endocrine diseases, studies on pituitary disease are extremely limited. To evaluate whether dexamethasone (DEX) suppression can improve 18F-FDG PET for the localization of adrenocorticotropic hormone-secreting adenomas in the pituitary gland in Cushing’s disease (CD).MethodsWe included 22 patients with CD who underwent PET imaging before and after DEX administration. We compared the success rates of PET before and after DEX suppression, magnetic resonance imaging (MRI), and bilateral inferior petrosal sinus sampling (BIPSS). We determined the final locations of adenomas based on intraoperative multiple-staged resection and tumor tissue identification using frozen sections. Standardized uptake value (SUV) were analyzed to confirm the change of intensity of adenomas on PET.ResultsTwenty-two patients were included (age at diagnosis: 37 [13–56] years), and most were women (90.91%). Pituitary adenomas compared to normal pituitaries showed increased maximum SUV after DEX suppression but without statistical significance (1.13 versus. 1.21, z=-0.765, P = 0.444). After DEX suppression, the mean and maximum SUV of adenomas showed a positive correlation with nadir cortisol levels in high-dose DEX suppression test (Rho = 0.554, P = 0.007 and Rho = 0.503, P = 0.017, respectively). In reference sites, mean SUV of cerebellum was significantly decreased (7.65 vs. 6.40, P = 0.006*), but those of the thalamus and gray matter was increased after DEX suppression (thalamus, 8.70 vs. 11.20, P = 0.010*; gray matter, 6.25 vs. 7.95, P = 0.010*).ConclusionDEX suppression did not improve 18F-FDG PET/CT localization in patients with CD.

Identification of tumor tissue in thin pathological samples via femtosecond laser-induced breakdown spectroscopy and machine learning

In the treatment of most newly discovered solid cancerous tumors, surgery remains the first treatment option. An important factor in the success of these operations is the precise identification of oncological safety margins to ensure the complete removal of the tumor without affecting much of the neighboring healthy tissue. Here we report on the possibility of applying femtosecond Laser-Induced Breakdown Spectroscopy (LIBS) combined with Machine Learning algorithms as an alternative discrimination technique to differentiate cancerous tissue. The emission spectra following the ablation on thin fixed liver and breast postoperative samples were recorded with high spatial resolution; adjacent stained sections served as a reference for tissue identification by classical pathological analysis. In a proof of principle test performed on liver tissue, Artificial Neural Networks and Random Forest algorithms were able to differentiate both healthy and tumor tissue with a very high Classification Accuracy of around 0.95. The ability to identify unknown tissue was performed on breast samples from different patients, also providing a high level of discrimination. Our results show that LIBS with femtosecond lasers is a technique with potential to be used in clinical applications for rapid identification of tissue type in the intraoperative surgical field.

Quelle est la meilleure méthode de délimitation du volume tumoral total des gliomes avant traitement en TEP à la [18F]-FDOPA ? Une étude contrôlée par biopsie

The definition of tumor boundaries in newly diagnosed glioma is crucial for optimal local therapies and/or non-invasive tumor characterization. The widespread use of [18F]FDOPA PET in this setting is hampered by the lack of a histologically validated standardized method. This study aimed to determine the best way to delineate the overall tumor volume in untreated gliomas regarding diagnostic performance and reliability. We retrospectively analyzed 33 biopsy sites and 33 biopsy sites and 33 contralateral virtual biopsies, from fourteen patients. Six sets of 10 minutes images were reconstructed starting at three different time points (10, 20, and 30 minutes post-injection) using two sets of features for the iterative algorithm. Four reference regions (“hemispheric,” “banana-shaped,” “striatum” and “white matter”) were drawn independently by four readers. A step-by-step selection was applied based on areas under the ROC curve (AUC) for the identification of tumor tissue, intraclass correlation coefficients (ICC) across reconstruction features, and inter-reader agreement. The best cut-off value was calculated as maximizing Youden's index. Tumor infiltration was confirmed in all biopsy samples. TargetSUVmax-to-StriatumSUVmean (TSRmean) and TargetSUVmax-to-StriatumSUVmax (TSRmax) on images performed at 20 minutes provided the best overall performances with AUCs = 0.91, inter-algorithm ICCs = 0.99 and inter-reader Fleiss’ kappas = 0.99 for both. Optimal threshold values of TSRmean20–30 = 0.90 and TSRmax20–30 = 0.68 provided sensitivities of 85% and 83%, respectively, and specificities of 86% for both. This study completes the current EANM guidelines and is a step forward in standardizing the delineation methods in untreated glioma patients. TSRmean20–30 or TSRmax20–30 provided the best combination of accuracy and reliability.

Photodynamic therapy of malignant brain gliomas

Treatment of malignant gliomas of the brain remains a serious problem on a global scale, despite intensive research into the causes and mechanisms of their progression. When using traditional surgical approaches and imaging methods tumor cell infiltrates may be overlooked, as a result of which, malignant gliomas relapse often occurs near the marginal region of the surgical cavity. A method that allows visual identification of tumor tissue and at the same time provides an opportunity to selectively destroy it is photodynamic therapy (PDT) ‒ a two-stage treatment that includes the introduction (intravenous, intraperitoneal, local or oral) of a light-sensitive chemical agent (photosensitizer (PS)) followed by its activation at a certain wavelength of light.The principle of PDT is based on the cytotoxic effects caused by PS, which selectively accumulates in malignant tumor cells and is activated by light rays of the appropriate wavelength, generating singlet oxygen and free radicals, which trigger photochemical reactions in tumor cells with subsequent destruction of protein structures. Tumor tissue has a higher affinity for PSs. PSs are divided into 1st, 2nd and 3rd generation molecules. So far, 3rd generation PSs have not yet been approved for clinical use. In vitro and in vivo experimental studies confirmed the effectiveness of PDT of brain tumors using 2nd generation PSs.The simultaneous use of surgery under the control of fluorescence and PDT enables both the visualization of tumor cells and their selective destruction. Regardless of PDT, PSs are used for the purpose of auxiliary delineation of tumor borders for maximum tumor removal during fluorescence-guided surgery.The review examines the development of PDT in a historical aspect, the contribution of domestic scientists, in particular, scientists of the Institute of Neurosurgery named after acad. A. P. Romodanov, National Academy of Medical Sciences of Ukraine to the development of the problem of PDT in neuro-oncology; preclinical studies of PDT and experimental approaches to increase the efficiency of PDT are characterized. Analysis of data from clinical trials confirms that using PDT as an adjunctive treatment of malignant gliomas administered immediately after maximal resection is safe, reduces the risk of recurrence by targeting residual tumor cells in the resection cavity, improves survival and quality of life of patients. The absence of information on the development of resistance to multiple PDT sessions suggests the possibility of repeated treatments of tumor cells not removed during surgery.

Impact of preprocessing methods on the Raman spectra of brain tissue.

Delineating cancer tissue while leaving functional tissue intact is crucial in brain tumor resection. Despite several available aids, surgeons are limited by preoperative or subjective tools. Raman spectroscopy is a label-free optical technique with promising indications for tumor tissue identification. To allow direct comparisons between measurements preprocessing of the Raman signal is required. There are many recognized methods for preprocessing Raman spectra; however, there is no universal standard. In this paper, six different preprocessing methods were tested on Raman spectra (n > 900) from fresh brain tissue samples (n = 34). The sample cohort included both primary brain tumors, such as adult-type diffuse gliomas and meningiomas, as well as metastases of breast cancer. Each tissue sample was classified according to the CNS WHO 2021 guidelines. The six methods include both direct and iterative polynomial fitting, mathematical morphology, signal derivative, commercial software, and a neural network. Data exploration was performed using principal component analysis, t-distributed stochastic neighbor embedding, and k-means clustering. For each of the six methods, the parameter combination that explained the most variance in the data, i.e., resulting in the highest Gap-statistic, was chosen and compared to the other five methods. Depending on the preprocessing method, the resulting clusters varied in number, size, and associated spectral features. The detected features were associated with hemoglobin, neuroglobin, carotenoid, water, and protoporphyrin, as well as proteins and lipids. However, the spectral features seen in the Raman spectra could not be unambiguously assigned to tissue labels, regardless of preprocessing method. We have illustrated that depending on the chosen preprocessing method, the spectral appearance of Raman features from brain tumor tissue can change. Therefore, we argue both for caution in comparing spectral features from different Raman studies, as well as the importance of transparency of methodology and implementation of the preprocessing. As discussed in this study, Raman spectroscopy for in vivo guidance in neurosurgery requires fast and adaptive preprocessing. On this basis, a pre-trained neural network appears to be a promising approach for the operating room.

Can Radiomics Provide Additional Information in [18F]FET-Negative Gliomas?

Simple SummaryAmino acid positron emission tomography (PET) complements standard magnetic resonance imaging (MRI) since it directly visualizes the increased amino acid transport into tumor cells. Amino acid PET using O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) has proven to be relevant, for example, for glioma classification, identification of tumor progression or recurrence, or for the delineation of tumor extent. Nevertheless, a relevant proportion of low-grade gliomas (30%) and few high-grade gliomas (5%) were found to show no or even decreased amino acid uptake by conventional visual analysis of PET images. Advanced image analysis with the extraction of radiomic features is known to provide more detailed information on tumor characteristics than conventional analyses. Hence, this study aimed to investigate whether radiomic features derived from dynamic [18F]FET PET data differ between [18F]FET-negative glioma and healthy background and thus provide information that cannot be extracted by visual read.The purpose of this study was to evaluate the possibility of extracting relevant information from radiomic features even in apparently [18F]FET-negative gliomas. A total of 46 patients with a newly diagnosed, histologically verified glioma that was visually classified as [18F]FET-negative were included. Tumor volumes were defined using routine T2/FLAIR MRI data and applied to extract information from dynamic [18F]FET PET data, i.e., early and late tumor-to-background (TBR5–15, TBR20–40) and time-to-peak (TTP) images. Radiomic features of healthy background were calculated from the tumor volume of interest mirrored in the contralateral hemisphere. The ability to distinguish tumors from healthy tissue was assessed using the Wilcoxon test and logistic regression. A total of 5, 15, and 69% of features derived from TBR20–40, TBR5–15, and TTP images, respectively, were significantly different. A high number of significantly different TTP features was even found in isometabolic gliomas (after exclusion of photopenic gliomas) with visually normal [18F]FET uptake in static images. However, the differences did not reach satisfactory predictability for machine-learning-based identification of tumor tissue. In conclusion, radiomic features derived from dynamic [18F]FET PET data may extract additional information even in [18F]FET-negative gliomas, which should be investigated in larger cohorts and correlated with histological and outcome features in future studies.

A new study protocol for in-vivo assessment of tumor diagnosis and microscopic tumor infiltration at the resection cavity in central nervous system tumors by a new miniature confocal endomicroscope (CONVIVO system).

Confocal laser technology has been recently suggested as a promising method to obtain near real-time intraoperative histological data. We recently demonstrated the accuracy of a newly designed confocal endomiscroscope (CONVIVO) in offering an intraoperative diagnosis during high-grade gliomas (HGGs) removal in an ex vivo study. With this work we aim to perform a standardized, prospective and blinded-to-histological section study for evaluating the potentiality of CONVIVO in offering in-vivo data regarding histological diagnosis and presence of tumor at margins during resection of central nervous system (CNS) tumors. This prospective, observational, standardized, blinded-to-histological section, clinical trial was approved by the institutional review board in Carlo Besta Neurologic Institute IRCCS Foundation in Milan and is expected to last 24 months. 75 patients will be included, with at least 53 of them being HGGs based on the statistical sample size calculation. Main objectives will be the assessing of the concordance of tumor diagnoses between CONVIVO images and frozen section at the center of all tumor subtypes and the evaluation of the accuracy of CONVIVO in the identification of tumor tissue at the margins, compared to standard histology. For this purpose, "virtual biopsies" and physical biopsies will be performed directly on patient tumor tissue and surrounding brain parenchima during tumor resection, comparing the results of CONVIVO analysis and frozen and histological sections. Despite promising preliminary data on ex vivo usefulness of CLE machines are emerging in literature, still few studies are available when looking at in vivo potentiality of CONVIVO. At this regard, this study will be the first work where a standardized, prospective, and blinded-to-histological section CONVIVO analysis will be performed in an in-vivo setting in neuro-oncological surgery. We hypothesize that this new technique may have a role in offering data regarding presence of tumor tissue, eventually giving an intraoperative diagnosis in neuro-oncological surgery, rendering more fluid the decision-making process in the operating room. Furthermore, the result of this study will provide a solid base for further expanding the clinical applications of confocal machines in neurosurgery.

Hyperspectral Evaluation of the Human Liver During Major Resection.

This study investigates the effects of PVE and vascular inflow control (VIC) on liver microperfusion and tissue oxygenation using hyperspectral imaging (HSI) technology. Mechanisms triggering future liver remnant (FLR) augmentation introduced by PVE have not been sufficiently studied in humans. Particularly, the arterial buffer response (ABR) of the liver might play a vital role. Hyperspectral datacubes (TIVITA) acquired during 58 major liver resections were qualitatively and quantitatively analyzed for tissue oxygenation (StO2%), near-infrared (NIR) perfusion, organ-hemoglobin indices (OHI), and tissue-water indices (TWI). The primary study endpoint was measurement of hyperspectral differences in liver parenchyma subject to PVE and VIC before resection. HSI revealed parenchyma specific differences in StO2% with regard to the underlying disease (P < 0.001). Preoperative PVE (n = 23, 40%) lead to arterial hyperoxygenation and hyperperfusion of corresponding liver segments (StO2: 77.23% ± 11.93%, NIR: 0.46 ± 0.20[I]) when compared with the FLR (StO2: 66.13% ± 9.96%, NIR: 0.23 ± 0.12[I]; P < 0.001). In a case of insufficient PVE and the absence of FLR augmentation hyperspectral StO2 and NIR differences were absent. The hyperspectral assessment demonstrated increased liver tissue-oxygenation and perfusion in PVE-segments (n = 23 cases) and decreased total VIC in nonembolized FLR hemilivers (n = 35 cases; P < 0.001). Intraoperative HSI analysis of tumor tissue revealed marked tumor specific differences in StO2, NIR, OHI, and TWI (P < 0.001). HSI allows intraoperative quantitative and qualitative assessment of microperfusion and StO2% of liver tissue. PVE lead to ABR-triggered tissue hyperoxygenation and cross-talk FLR augmentation. HSI furthermore facilitates intraoperative tumor tissue identification and enables image-guided liver surgery following VIC.

Intraoperative application of yellow fluorescence in resection of intramedullary spinal canal ependymoma.

BackgroundSpinal ependymoma is the most common intramedullary tumor in adults. This study was performed to evaluate whether intraoperative yellow fluorescence use enhances our ability to identify the tumor margin and residual tumor tissue in intramedullary spinal cord ependymoma resection. We also evaluated patients’ clinical conditions at a 3-month follow-up.MethodsWe retrospectively evaluated 56 patients with intramedullary ependymoma. Thirty minutes before anesthesia, the patients received intravenous sodium fluorescein injections. Tumor resection was performed under two illumination modes, traditional white light and yellow fluorescence, and the residual tumor tissue was detected. Magnetic resonance imaging was performed 3 months postoperatively to observe the tumor resection outcome and residual tumor tissue. The McCormick spinal cord function grade was evaluated preoperatively and 3 months postoperatively.ResultsThe total resection rate was 100.0% in all patients. Nine patients had no significant fluorescence imaging. After 3 months, patients with a spinal function grade of I to IV showed significant spinal function improvement. Magnetic resonance imaging showed no residual tumor tissue or recurrence.ConclusionSodium fluorescein aids in total excision of intramedullary spinal cord ependymoma and intraoperative residual tumor tissue identification. At the 3-month follow-up, the patients’ functional outcome in the fluorescein group was good.

PATH-43. RAMAN SPECTROSCOPY AS A TOOL IN NEUROSURGERY

Abstract BACKGROUND Raman Spectra have been shown to be sufficiently characteristic to their samples of origin that they can be used in a wide range of applications including distinction of intracranial tumors. While not replacing pathological analysis, the advantage of non-destructive sample analysis and extremely fast feedback make this technique an interesting tool for surgical use. METHODS We sampled intractanial tumors from more than 300 patients at the Centre Hospitalier Luxembourg over a period of three years and compared the spectra of different tumor entities, different tumor subregions and healthy surrounding tissue. We created machine-learning based classifiers that include tissue identification as well as diagnostics. RESULTS To this end, we solved several classes in the intracranial tumor classification, and developed classifiers to distinguish primary central nervous system lymphoma from glioblastoma, which is an important differential diagnosis, as well as meningioma from the surrounding healthy dura mater for identification of tumor tissue. Within glioblastoma, we resolve necrotic, vital tumor tissue and peritumoral infiltration zone.We are currently developing a multi-class classifier incorporating all tissue types measured. CONCLUSIONS Raman Spectroscopy has the potential to aid the surgeon in the surgery theater by providing a quick assessment of the tissue analyzed with regards to both tumor identity and tumor margin identification. Once a reliable classifier based on sufficient patient samples is developed, this may even be integrated into a surgical microscope or a neuronavigation system.

The role of fluorescent and hybrid tracers in radioguided surgery in urogenital malignancies.

The increasing availability of new imaging technologies and tracers has enhanced the application of nuclear molecular imaging in urogenital interventions. In this context, preoperative nuclear imaging and radioactivity-based intraoperative surgical guidance have become important tools for the identification and anatomical allocation of tumor lesions and/or suspected lymph nodes. Fluorescence guidance can provide visual identification of the preoperatively defined lesions during surgery. However, the added value of fluorescence guidance is still mostly unknown. This review provides an overview of the role of fluorescence imaging in radioguided surgery in urogenital malignancies. The sentinel node (SN) biopsy procedure using hybrid tracers (radioactive and fluorescent component) serves as a prominent example for in-depth evaluation of the complementary value of radio- and fluorescence guidance. The first large patient cohort and long-term follow-up studies show: 1) improvement in the SN identification rate compared to blue dye; 2) improved detection of cancer-positive SNs; and 3) hints towards a positive effect on (biochemical) recurrence rates compared to extended lymph node dissection. The hybrid tracer approach also highlights the necessity of a preoperative roadmap in preventing incomplete resection. Recent developments focus on receptor-targeted approaches that allow intraoperative identification of tumor tissue. Here radioguidance is still leading, but fluorescent and hybrid tracers are also finding their way into the clinic. Emerging multiwavelength approaches that allow concomitant visualization of different anatomical features within the surgical field may provide the next step towards even more refined procedures.

Sampling Based Tumor Recognition in Whole-Slide Histology Image With Deep Learning Approaches.

Histopathological identification of tumor tissue is one of the routine pathological diagnoses for pathologists. Recently, computational pathology has been successfully interpreted by a variety of deep learning-based applications. Nevertheless, the high-efficient and spatial-correlated processing of individual patches have always attracted attention in whole-slide image (WSI) analysis. In this paper, we propose a high-throughput system to detect tumor regions in colorectal cancer histology slides precisely. We train a deep convolutional neural network (CNN) model and design a Monte Carlo (MC) adaptive sampling method to estimate the most representative patches in a WSI. Two conditional random field (CRF) models are designed, namely the correction CRF and the prediction CRF are integrated for spatial dependencies of patches. We use three datasets of colorectal cancer from The Cancer Genome Atlas (TCGA) to evaluate the performance of the system. The overall diagnostic time can be reduced from 56.7 percent to 71.7 percent on the slides of a varying tumor distribution, with an increase in classification accuracy.

Identification of Tumor Tissue of Origin with RNA-Seq Data and Using Gradient Boosting Strategy.

Background Cancer of unknown primary (CUP) is a type of malignant tumor, which is histologically diagnosed as a metastatic carcinoma while the tissue-of-origin cannot be identified. CUP accounts for roughly 5% of all cancers. Traditional treatment for CUP is primarily broad-spectrum chemotherapy; however, the prognosis is relatively poor. Thus, it is of clinical importance to accurately infer the tissue-of-origin of CUP. Methods We developed a gradient boosting framework to trace tissue-of-origin of 20 types of solid tumors. Specifically, we downloaded the expression profiles of 20,501 genes for 7713 samples from The Cancer Genome Atlas (TCGA), which were used as the training data set. The RNA-seq data of 79 tumor samples from 6 cancer types with known origins were also downloaded from the Gene Expression Omnibus (GEO) for an independent data set. Results 400 genes were selected to train a gradient boosting model for identification of the primary site of the tumor. The overall 10-fold cross-validation accuracy of our method was 96.1% across 20 types of cancer, while the accuracy for the independent data set reached 83.5%. Conclusion Our gradient boosting framework was proven to be accurate in identifying tumor tissue-of-origin on both training data and independent testing data, which might be of practical usage.

Our sentinel lymph node experience in patients diagnosed with DCIS and microinvasive breast carcinoma

Aim: Along with the increased availability of radiologic imaging methods, early identification of tumor tissue, and patient surveillance programs; ductal carcinoma in situ (DCIS) and microinvasive DCIS became more commonly identified in the tru-cut biopsy specimens and resected samples of patients. Pathological examinations of the excision materials from these patients reveal invasive tumors, microinvasions or DCIS alone. Recently, it has become debatable whether to perform a sentinel lymph node biopsy (SLNB) in patients diagnosed with DCIS or microinvasive DCIS. In this present study, we evaluated the diagnosis made by examining the excision material, any presence of lymph node metastases, and the relationship of hormone profile to the presence of metastases in the patients diagnosed with DCIS or microinvasive DCIS by the examination of tru-cut biopsy specimens. Based on our study results, we discussed the requirement for SLNB in patients with a tru-cut diagnosis of DCIS or microinvasive DCIS.Materials and Methods: The study included 172 patients, who underwent surgical excision and SLNB after receiving a tru-cut biopsy diagnosis of DCIS and microinvasive DCIS in our hospital from the year 2010 to 2018.Results: Tru-cut biopsy diagnoses were DCIS and microinvasive DCIS in 69.8% (120 patients) and 30.2% (52 patients) respectively. SLNB metastases were identified in 35.8% (n=43) of the DCIS positive patients and 44.2% (n=23) in the microinvasive DCIS positive patients. The diagnosis of invasive ductal carcinoma after mastectomy was made at a rate of 90.0% (n=108) among the DCIS positive patients and 92.3% (n=48) among the microinvasive DCIS positive patients. Conclusion: SLNB metastases were found in 35.8% (n=43) and 44.2% (n=23) of the DCIS positive patients and microinvasive DCIS positive patients, respectively. We conclude that SLNB should be favorably proper to perform in the patients with tru-cut diagnoses of DCIS and microinvasive DCIS because a high rate of SLNB metastases was detected in our DCIS and microinvasive DCIS patients and a high rate of invasive ductal carcinoma diagnosis was made after examining the excision material of these patients.

A preliminary study of dual-band confocal laser endomicroscopy combined with image mosaic in the diagnosis of liver cancer

Accurate identification of tumor tissues and their margins are still challenging for conventional clinical imaging methods during liver cancer surgery. In this study, dual-band confocal laser endomicroscopy (CLE) combined with image mosaic was used to guide liver cancer surgery. In the experiments with mice bearing orthotropic liver tumor, CLE can accurately detect the tumors and identify their margins with two excitation wavelengths of 488 nm and 660 nm by clinically available dyes fluorescein sodium (FS) or indocyanine green (ICG). The mosaic CLE images enlarged the imaging field and detected the liver tumor margins more accurately. Normal liver tissues fluorescence intensity of CLE images was significantly higher than that of tumor tissues in the same tumor-bearing mice (P < 0.0001). Overall, dual-band CLE imaging demonstrates to be a promising method to identify liver tumor tissues and margins, which has the prospect of clinical application and helps to achieve intraoperative radical resection.

Topical dual-probe staining using quantum dot-labeled antibodies for identifying tumor biomarkers in fresh specimens.

PurposeRapid, intra-operative identification of tumor tissue in the margins of excised specimens has become an important focus in the pursuit of reducing re-excision rates, especially for breast conserving surgery. Dual-probe difference specimen imaging (DDSI) is an emerging approach that uses the difference in uptake/clearance kinetics between a pair of fluorescently-labeled stains, one targeted to a biomarker-of-interest and the other an untargeted isotype, to reveal receptor-specific images of the specimen. Previous studies using antibodies labeled with either enhanced Raman particles or organic fluorophores have shown promising tumor vs. normal diagnostic performance. Yet, the unique properties of quantum dot-labeled antibody complexes (QDACs), which provide spectrally-distinct fluorescence emission from a common excitation source, make them ideal candidates for this application. Herein, we evaluate the diagnostic performance of QDAC-based DDSI in excised xenografts.ProceduresExcised fresh specimens of normal tissue and human tumor xenografts with elevated expression of HER2 were stained with a HER2-targeted QDAC and an untargeted QDAC isotype. Stained specimens were imaged on a custom hyperspectral imaging system capable of spectrally separating the quantum dot signatures, and images processed using the DDSI approach. The diagnostic performance of this technique under different incubation temperatures and probe concentrations was evaluated using receiver-operator characteristic analysis.ResultsHER2-targeted QDAC-DDSI was able to distinguish HER2(+) tumors from normal tissue with reasonably high diagnostic performance; however, this performance was sensitive to temperature during the staining procedure. Area under the curve values were 0.61 when staining at room temperature but increased to over 0.81 when staining at 37 °C. Diagnostic performance was not affected by increasing stain concentration.ConclusionsThis study is the first to report dual-probe difference imaging of specimens using QDACs and hyperspectral imaging. Our results show promising diagnostic performance under certain conditions, and compel further optimization and evaluation of this intra-operative margin assessment technique.

Pancreatic Ductal Adenocarcinoma: Molecular Expression Patterns after Neoadjuvant FOLFIRINOX Treatment.

Background: Positive margin (R1) rates following pancreatic cancer resection vary between 20-75% (Tummers 2019). The clinical relevance of this is underlined by the two-fold increase in survival time after radical (R0) compared to R1 resection rates (Tummers, 2019). Distinguishing pancreatic ductal adenocarcinoma (PDAC) from peritumoral inflammation, tumor necrosis and fibrosis induced by neoadjuvant treatment is challenging. Molecular targeted imaging using fluorescence is an intra-operative technique which could aid in tumor tissue identification. Previous research has shown alterations in tumor cell molecular expression patterns following neoadjuvant chemotherapy. As neoadjuvant treatment strategies are being adopted into pancreatic cancer guidelines, determining the effect of neoadjuvant treatment regimens on PDAC molecular status is of evident importance for targeted fluorescence imaging (Boogerd, 2018).

Inline cartridge extraction for rapid brain tumor tissue identification by molecular profiling

The development of perspective diagnostic techniques in medicine requires efficient high-throughput biological sample analysis methods. Here, we present an inline cartridge extraction that facilitates the screening rate of mass spectrometry shotgun lipidomic analysis of tissue samples. We illustrate the method by its application to tumor tissue identification in neurosurgery. In perspective, this high-performance method provides new possibilities for the investigation of cancer pathogenesis and metabolic disorders.