Correlation of microscopic tumor extension with tumor microenvironment in esophageal cancer patients.

OBJECTIVE: In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE. METHODS: Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible. RESULTS: In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p < 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31 mm. CONCLUSION: Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis. TRIAL REGISTRATION NUMBER AND DATE: BO-EK-148042017 and BO-EK-177042022 on 20.06.2022, DRKS00011886, https://drks.de/search/de/trial/DRKS00011886 .

Magnetic resonance metrics for identification of cuprizone-induced demyelination in the mouse model of neurodegeneration: a review.

Neurodegenerative disorders, including Multiple Sclerosis (MS), are heterogenous disorders which affect the myelin sheath of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) provides a non-invasive method for studying, diagnosing, and monitoring disease progression. As an emerging research area, many studies have attempted to connect MR metrics to underlying pathophysiological presentations of heterogenous neurodegeneration. Most commonly, small animal models are used, including Experimental Autoimmune Encephalomyelitis (EAE), Theiler's Murine Encephalomyelitis (TMEV), and toxin models including cuprizone (CPZ), lysolecithin, and ethidium bromide (EtBr). A contrast and comparison of these models is presented, with focus on the cuprizone model, followed by a review of literature studying neurodegeneration using MRI and the cuprizone model. Conventional MRI methods including T1 Weighted (T1W) and T2 Weighted (T2W) Imaging are mentioned. Quantitative MRI methods which are sensitive to diffusion, magnetization transfer, susceptibility, relaxation, and chemical composition are discussed in relation to studying the CPZ model. Overall, additional studies are needed to improve both the sensitivity and specificity of MRI metrics for underlying pathophysiology of neurodegeneration and the relationships in attempts to clear the clinico-radiological paradox. We therefore propose a multiparametric approach for the investigation of MR metrics for underlying pathophysiology.

Optrode-Assisted Multiparametric Near-Infrared Spectroscopy for the Analysis of Liquids.

We demonstrate a sensing scheme for liquid analytes that integrates multiple optical fiber sensors in a near-infrared spectrometer. With a simple optofluidic method, a broadband radiation is encoded in a time-domain interferogram and distributed to different sensing units that interrogate the sample simultaneously; the spectral readout of each unit is extracted from its output signal by a Fourier transform routine. The proposed method allows performing a multiparametric analysis of liquid samples in a compact setup where the radiation source, measurement units, and spectral readout are all integrated in a robust telecom optical fiber. An experimental validation is provided by combining a plasmonic nanostructured fiber probe and a transmission cuvette in the setup and demonstrating the simultaneous measurement of the absorption spectrum and the refractive index of water-methanol solutions.

Multiparametric ultrasound imaging for early-stage steatosis: Comparison with magnetic resonance imaging-based proton density fat fraction.

BACKGROUND: The prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR. PURPOSE: This study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging-based proton density fat fraction (MRI-PDFF) for hepatic steatosis assessment. METHODS: We investigated early-stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI-PDFF; histology fat percentages. Seven individual US parameters were extracted using B-mode measurement, Burr distribution estimation, attenuation estimation, H-scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease-specific imaging (DSI). RESULTS: The combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p-value < 0.05) and outperforms the correlation between MRI-PDFF and histology (R = 0.89, p-value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI-PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color-highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p-value < 0.05). CONCLUSIONS: We demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI-PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans.

Simultaneous quantification of 55 psychotropic drugs and metabolites in human plasma with a fast UPLC-MS/MS method.

OBJECTIVES: Therapeutic drug monitoring is strongly recommended for psychotropic drugs, which present a strong inter- and intra-individual variability due to multiple factors like inflammatory state, smoking, diet, drug interactions due to polypharmacy, and genetic profile. The aim of this study was to develop and validate a fast, simple, and sensitive method allowing the simultaneous quantification of a large number of psychotropic drugs. METHODS: After a simple sample preparation with a one-step protein precipitation, a total of 55 compounds, including 22 antidepressants, 18 antipsychotics, 2 other psychotropic drugs (bupropion and nefopam), and their metabolites, was separated on a Waters Acquity HSS T3 ultra-performance liquid chromatography column, and subsequently detected and quantified by a triple quadrupole Quantis mass spectrometer with electrospray ionization operated in positive mode. RESULTS: Total run time was only 5.7 min. Limits of detection ranged from 0.01 to 0.18 µg/L depending on compound. Measuring ranges were from 0.195 to 1000 µg/L depending on compound, and were defined according to therapeutic ranges. Inter- and intra-assay precisions values were less than 15 %. After validation, this method was successfully applied in daily practice for therapeutic drug monitoring of polymedicated psychiatric patients. CONCLUSION: We developed and validated one of the most sensitive and complete UPLC-MS/MS methods in psychopharmacology, allowing the simultaneous determination of 55 psychotropic drugs in only 5.7 min after a simple sample preparation. This method has been successfully used in daily practice for therapeutic drug monitoring of psychiatric patients and is especially useful in polymedicated patients.

Preoperative Diagnosis of Warthin Tumors Combining Cytological, Clinical and Ultrasonographic Information within a Multidisciplinary Approach in a Lump Clinic.

(1) Background: Warthin tumors account for about 20% of all benign salivary tumors, approaching 50% if we consider only the parotid gland. Wait and see is considered a reasonable option, but the diagnosis should be certain. Diagnosis can be based on morphological and cytological data, but the sensitivity of the fine needle aspiration cytology (FNAC) is not absolute, with a high rate of non-diagnostic findings in the event of a Warthin tumor, hindering the counseling and therapeutic decisions. The aim of the study is to evaluate the reliability of FNAC and its combination with anamnestic, clinical, and ultrasonographic data in diagnosing Warthin tumors. (2) Methods: A total of 413 patients affected by masses within the major salivary gland and managed between 2017 and 2022 at our institution have been included in the present retrospective study. Each patient underwent fine needle aspiration biopsy (FNAB) with a subsequent cytological diagnosis; successively, for each patient, the clinician (otolaryngologist) and the histopathologist discussed the combination of cytological (even non-diagnostic), clinical, and ultrasonographic data in order to make a "multiparametric" diagnosis. A total of 214 cases were subsequently submitted to surgical resection and had a final histopathology report, to which the cytological and the multiparametric diagnoses can be compared. We extracted all the patients with a cytological, multiparametric, and/or histological diagnosis of Warthin tumors in order to assess the sensitivity and specificity of FNAC and of multiparametric analysis in diagnosing Warthin tumors in case of a major salivary gland mass. (3) Results: One hundred thirty-two cases had a cytological, multiparametric, and/or histological diagnosis of Warthin tumors. FNAC displays a sensitivity of 68.4% and a specificity of 98.7% in diagnosing Warthin tumors. The multiparametric evaluation allowed a considerable improvement in sensitivity (92.9% vs. 68.4%), minimizing the number of non-diagnostic results and preserving at the same time a similar value of specificity (95.5% vs. 98.7%). Notably, none of the patients with a cytological or multiparametric diagnosis of Warthin were affected by a malignant lesion in the final histopathological report. (4) Conclusions: In the case of Warthin tumors, a multiparametric evaluation encompassing anamnestic, clinical, and cytological data is effective in reducing the number of non-diagnostic reports and can safely guide the management of a tumor (e.g., antibiotic treatment of infectious complications, assign a low priority to surgery, even consider observation avoiding surgery) which is absolutely benign and can be associated with no clinically relevant issues.

Multiple flow cytometry analysis for assessing human sperm functional characteristics.

Multiparametric analysis by flow cytometry solves one of the major problems in sperm evaluation, the inability to test multiple attributes simultaneously in a single cell, which would increase the precision to predict fertility potential since several sperm parameters are tested. The association of fluorochromes and compounds conjugated to fluorochromes in multiparametric sperm analysis is well-established in microscopy techniques. However, these techniques are subjective and limit the assessment in small cell numbers, thereby harming analytic accuracy. Therefore, the current study aimed to present new possibilities for assessing the integrity and stability of the sperm plasma membrane, acrosome status, mitochondrial potential, and superoxide anion production in the mitochondrial matrix in only 2 cytometric assays using cytometers equipped with 2 and 3 lasers. For this, human semen samples collected by masturbation and selected by the swim-up technique were divided into 3 treatments: T0 (flash-frozen semen), T50 (flash-frozen semen + fresh semen, V: V), and T100 (fresh semen) for the validation of the multiparametric protocols by flow cytometry. For both protocols, sperm percentage with positive stain for all fluorophores differed significantly between treatments. The determination coefficients presented values close to 1, which validated objective, sensitive, rapid, and reproducible methodologies. Therefore, we concluded that the results reflect the status of analyzed structure, enabling a more accurate diagnosis of male infertility that has become an increasingly prevalent worldwide setback due to exposure to a variety of environmental toxicants.

Study of CD27, CD38, HLA-DR and Ki-67 immune profiles for the characterization of active tuberculosis, latent infection and end of treatment.

Background: Current blood-based diagnostic tools for TB are insufficient to properly characterize the distinct stages of TB, from the latent infection (LTBI) to its active form (aTB); nor can they assess treatment efficacy. Several immune cell biomarkers have been proposed as potential candidates for the development of improved diagnostic tools. Objective: To compare the capacity of CD27, HLA-DR, CD38 and Ki-67 markers to characterize LTBI, active TB and patients who ended treatment and resolved TB. Methods: Blood was collected from 45 patients defined according to clinical and microbiological criteria as: LTBI, aTB with less than 1 month of treatment and aTB after completing treatment. Peripheral blood mononuclear cells were stimulated with ESAT-6/CFP-10 or PPD antigens and acquired for flow cytometry after labelling with conjugated antibodies against CD3, CD4, CD8, CD27, IFN-γ, TNF-α, CD38, HLA-DR, and Ki-67. Conventional and multiparametric analyses were done with FlowJo and OMIQ, respectively. Results: The expression of CD27, CD38, HLA-DR and Ki-67 markers was analyzed in CD4+ T-cells producing IFN-γ and/or TNF-α cytokines after ESAT-6/CFP-10 or PPD stimulation. Within antigen-responsive CD4+ T-cells, CD27- and CD38+ (ESAT-6/CFP-10-specific), and HLA-DR+ and Ki-67+ (PPD- and ESAT-6/CFP-10-specific) populations were significantly increased in aTB compared to LTBI. Ki-67 demonstrated the best discriminative performance as evaluated by ROC analyses (AUC > 0.9 after PPD stimulation). Data also points to a significant change in the expression of CD38 (ESAT-6/CFP-10-specific) and Ki-67 (PPD- and ESAT-6/CFP-10-specific) after ending the anti-TB treatment regimen. Furthermore, ratio based on the CD27 median fluorescence intensity in CD4+ T-cells over Mtb-specific CD4+ T-cells showed a positive association with aTB over LTBI (ESAT-6/CFP-10-specific). Additionally, multiparametric FlowSOM analyses revealed an increase in CD27 cell clusters and a decrease in HLA-DR cell clusters within Mtb-specific populations after the end of treatment. Conclusion: Our study independently confirms that CD27-, CD38+, HLA-DR+ and Ki-67+ populations on Mtb-specific CD4+ T-cells are increased during active TB disease. Multiparametric analyses unbiasedly identify clusters based on CD27 or HLA-DR whose abundance can be related to treatment efficacy. Further studies are necessary to pinpoint the convergence between conventional and multiparametric approaches.

Comprehensive Characterization of Human Lung Large Cell Carcinoma Identifies Transcriptomic Signatures with Potential Implications in Response to Immunotherapy.

Lung cancer is the leading cause of cancer mortality worldwide, with non-small cell lung cancer (NSCLC) being the most prevalent histology. While immunotherapy with checkpoint inhibitors has shown outstanding results in NSCLC, the precise identification of responders remains a major challenge. Most studies attempting to overcome this handicap have focused on adenocarcinomas or squamous cell carcinomas. Among NSCLC subtypes, the molecular and immune characteristics of lung large cell carcinoma (LCC), which represents 10% of NSCLC cases, are not well defined. We hypothesized that specific molecular aberrations may impact the immune microenvironment in LCC and, consequently, the response to immunotherapy. To that end, it is particularly relevant to thoroughly describe the molecular genotype-immunophenotype association in LCC-to identify robust predictive biomarkers and improve potential benefits from immunotherapy. We established a cohort of 18 early-stage, clinically annotated, LCC cases. Their molecular and immune features were comprehensively characterized by genomic and immune-targeted sequencing panels along with immunohistochemistry of immune cell populations. Unbiased clustering defined two novel subgroups of LCC. Pro-immunogenic tumors accumulated certain molecular alterations, showed higher immune infiltration and upregulated genes involved in potentiating immune responses when compared to pro-tumorigenic samples, which favored tumoral progression. This classification identified a set of biomarkers that could potentially predict response to immunotherapy. These results could improve patient selection and expand potential benefits from immunotherapy.

Improving breast cancer diagnosis by incorporating raw ultrasound parameters into machine learning.

The improved diagnostic accuracy of ultrasound breast examinations remains an important goal. In this study, we propose a biophysical feature-based machine learning method for breast cancer detection to improve the performance beyond a benchmark deep learning algorithm and to furthermore provide a color overlay visual map of the probability of malignancy within a lesion. This overall framework is termed disease-specific imaging. Previously, 150 breast lesions were segmented and classified utilizing a modified fully convolutional network and a modified GoogLeNet, respectively. In this study multiparametric analysis was performed within the contoured lesions. Features were extracted from ultrasound radiofrequency, envelope, and log-compressed data based on biophysical and morphological models. The support vector machine with a Gaussian kernel constructed a nonlinear hyperplane, and we calculated the distance between the hyperplane and each feature's data point in multiparametric space. The distance can quantitatively assess a lesion and suggest the probability of malignancy that is color-coded and overlaid onto B-mode images. Training and evaluation were performed on in vivo patient data. The overall accuracy for the most common types and sizes of breast lesions in our study exceeded 98.0% for classification and 0.98 for an area under the receiver operating characteristic curve, which is more precise than the performance of radiologists and a deep learning system. Further, the correlation between the probability and Breast Imaging Reporting and Data System enables a quantitative guideline to predict breast cancer. Therefore, we anticipate that the proposed framework can help radiologists achieve more accurate and convenient breast cancer classification and detection.

Quantification of 15 Antibiotics Widely Used in the Critical Care Unit with a LC-MS/MS System: An Easy Method to Perform a Daily Therapeutic Drug Monitoring.

Potential under- or overdose of antibiotics may occur in intensive care units due to high variability in plasma concentrations. The risk is either treatment failure or toxicity. Thus, therapeutic drug monitoring of antibiotics may guide dosing adjustment, maximising antibacterial efficacy and minimising toxicity. The aim of this study was to develop and validate a method for the analysis of 15 antibiotics including beta-lactams, linezolid, fluoroquinolones, daptomycin, and clindamycin to have a complete panel in the management of infections. We proposed to develop a fast, sensitive, and quantitative method for the analysis of 15 antibiotics using ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometer (UPLC-MS/MS) technology. this method required only 100 µL of plasma and consisted of a rapid liquid-liquid deproteinisation using methanol. Calibration curves ranged from 0.078 to 500 mg/L depending on the molecules, and were defined according to a therapeutic range. Inter- and intra-assay precisions values were less than 15%. This work described the development and the full validation of a precise, sensitive and accurate assay using UPLC-MS/MS technology. After validation, this new assay was successfully applied to routine therapeutic drug monitoring.

Assessing the Quality of Milk Using a Multicomponent Analytical Platform MicroNIR/Chemometric.

In this work, an innovative screening platform based on MicroNIR and chemometrics is proposed for the on-site and contactless monitoring of the quality of milk using simultaneous multicomponent analysis. The novelty of this completely automated tool consists of a miniaturized NIR spectrometer operating in a wireless mode that allows samples to be processed in a rapid and accurate way and to obtain in a single click a comprehensive characterization of the chemical composition of milk. To optimize the platform, milk specimens with different origins and compositions were considered and prediction models were developed by chemometric analysis of the NIR spectra using Partial Least Square regression algorithms. Once calibrated, the platform was used to predict samples acquired in the market and validation was performed by comparing results of the novel platform with those obtained from the chromatographic analysis. Results demonstrated the ability of the platform to differentiate milk as a function of the distribution of fatty acids, providing a rapid and non-destructive method to assess the quality of milk and to avoid food adulteration.

Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.

Fifty years of research on the nature of backscatter from tissues has resulted in a number of promising diagnostic parameters. We recently introduced two analyses tied directly to the biophysics of ultrasound scattering: the H-scan, based on a matched filter approach to distinguishing scattering transfer functions, and the Burr distribution for quantification of speckle patterns. Together, these analyses can produce at least five parameters that are directly linked to the mathematics of ultrasound in tissue. These have been measured in vivo in 35 rat livers under normal conditions and after exposure to compounds that induce inflammation, fibrosis, and steatosis in varying combinations. A classification technique, the support vector machine, is employed to determine clusters of the five parameters that are signatures of the different liver conditions. With the multiparametric measurement approach and determination of clusters, the different types of liver pathology can be discriminated with 94.6% accuracy.

Revising CX3CR1 Expression on Murine Classical and Non-classical Monocytes.

In mice, monocytes (Mo) are conventionally described as CX3CR1low classical Mo (CMo) and CX3CR1high non-classical Mo (NCMo) based on the expression of EGFP in Cx3cr1+/EGFP mice and by analogy with human CX3CR1 expression. Although this terminology is widely used, it may not reflect the expression of CX3CR1 on Mo subsets. Using an unsupervised multiparametric analysis of blood Mo in steady state and after sterile peritonitis, we observed that CX3CR1 expression did not discriminate the CMo from the NCMo subsets. Our results highlight that despite being a reliable reporter to discriminate Mo subpopulations, EGFP level in Cx3cr1+/EGFP mice does not reflect CX3CR1 expression measured by a fluorescently-labeled CX3CL1 chemokine and a CX3CR1 specific antibody. In conclusion, authors should be cautious not to identify murine classical and non-classical Mo as CX3CR1low and CX3CR1high but rather use alternative markers such as the combination of Ly6C and CD43.

Array atomic force microscopy for real-time multiparametric analysis.

Nanoscale multipoint structure-function analysis is essential for deciphering the complexity of multiscale biological and physical systems. Atomic force microscopy (AFM) allows nanoscale structure-function imaging in various operating environments and can be integrated seamlessly with disparate probe-based sensing and manipulation technologies. Conventional AFMs only permit sequential single-point analysis; widespread adoption of array AFMs for simultaneous multipoint study is challenging owing to the intrinsic limitations of existing technological approaches. Here, we describe a prototype dispersive optics-based array AFM capable of simultaneously monitoring multiple probe-sample interactions. A single supercontinuum laser beam is utilized to spatially and spectrally map multiple cantilevers, to isolate and record beam deflection from individual cantilevers using distinct wavelength selection. This design provides a remarkably simplified yet effective solution to overcome the optical cross-talk while maintaining subnanometer sensitivity and compatibility with probe-based sensors. We demonstrate the versatility and robustness of our system on parallel multiparametric imaging at multiscale levels ranging from surface morphology to hydrophobicity and electric potential mapping in both air and liquid, mechanical wave propagation in polymeric films, and the dynamics of living cells. This multiparametric, multiscale approach provides opportunities for studying the emergent properties of atomic-scale mechanical and physicochemical interactions in a wide range of physical and biological networks.

Unbiased Phenotype Detection Using Negative Controls.

Phenotypic screens using automated microscopy allow comprehensive measurement of the effects of compounds on cells due to the number of markers that can be scored and the richness of the parameters that can be extracted. The high dimensionality of the data is both a rich source of information and a source of noise that might hide information. Many methods have been proposed to deal with this complex data in order to reduce the complexity and identify interesting phenotypes. Nevertheless, the majority of laboratories still only use one or two parameters in their analysis, likely due to the computational challenges of carrying out a more sophisticated analysis. Here, we present a novel method that allows discovering new, previously unknown phenotypes based on negative controls only. The method is compared with L1-norm regularization, a standard method to obtain a sparse matrix. The analytical pipeline is implemented in the open-source software KNIME, allowing the implementation of the method in many laboratories, even ones without advanced computing knowledge.

Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping.

RATIONALE AND OBJECTIVES: The aim of this study was to assess variability in quantitative air trapping (QAT) measurements derived from spatially aligned expiration CT scans. MATERIALS AND METHODS: Sixty-four paired CT examinations, from 16 school-age cystic fibrosis subjects examined at four separate time intervals, were used in this study. For each pair, visually inspected lobe segmentation maps were generated and expiration CT data were registered to the inspiration CT frame. Measurements of QAT, the percentage of voxels on the expiration CT scan below a set threshold were calculated for each lobe and whole-lung from the registered expiration CT and compared to the true values from the unregistered data. RESULTS: A mathematical model, which simulates the effect of variable regions of lung deformation on QAT values calculated from aligned to those from unaligned data, showed the potential for large bias. Assessment of experimental QAT measurements using Bland-Altman plots corroborated the model simulations, demonstrating biases greater than 5% when QAT was approximately 40% of lung volume. These biases were removed when calculating QAT from aligned expiration CT data using the determinant of the Jacobian matrix. We found, by Dice coefficient analysis, good agreement between aligned expiration and inspiration segmentation maps for the whole-lung and all but one lobe (Dice coefficient > 0.9), with only the lingula generating a value below 0.9 (mean and standard deviation of 0.85 ± 0.06). CONCLUSION: The subtle and predictable variability in corrected QAT observed in this study suggests that image registration is reliable in preserving the accuracy of the quantitative metrics.

Multiparametric analysis of colorectal cancer immune responses.

Colorectal cancer (CRC) is a heterogeneous disease, with a diverse and plastic immune cell infiltrate. These immune cells play an important role in regulating tumour growth - progression or elimination. Some populations of cells have a strong correlation with disease-free survival, making them useful prognostic markers. In particular, the infiltrate of CD3+ and CD8+ T cells into CRC tumours has been validated worldwide as a valuable indicator of patient prognosis. However, the heterogeneity of the immune response, both between patients with tumours of different molecular subtypes, and within the tumour itself, necessitates the use of multiparametric analysis in the investigation of tumour-specific immune responses. This review will outline the multiparametric analysis techniques that have been developed and applied to studying the role of immune cells in the tumour, with a focus on colorectal cancer. Because much of the data in this disease relates to T cell subsets and heterogeneity, we have used T cell populations as examples throughout. Flow and mass cytometry give a detailed representation of the cells within the tumour in a single-cell suspension on a per-cell basis. Imaging technologies, such as imaging mass cytometry, are used to investigate increasing numbers of markers whilst retaining the spatial and structural information of the tumour section and the infiltrating immune cells. Together, the analyses of multiple immune parameters can provide valuable information to guide clinical decision-making in CRC.

Simultaneous multiparametric PET/MRI for the assessment of therapeutic response to chemotherapy or concurrent chemoradiotherapy of cervical cancer patients: Preliminary results.

PURPOSE: To assess the response to initial treatment strategies of cervical cancer using multiparametric-PET/MRI. MATERIAL AND METHODS: PET/MR-derived morphological (tumor size), functional (DWI, DCE-MRI) and metabolic (18F-FDG PET) parameters were acquired in pre- and posttreatment examinations of 8 patients. Besides RECIST- and PERCIST-criteria, functional quantitative parameters were used to assess therapeutic response. RESULTS: RECIST- and PERCIST-response criteria demonstrated high correlations for the differentiation between therapy-responders and non-responders, which was additionally reflected by functional (DWI, DCE-MRI) quantitative imaging parameters. CONCLUSION: Multiparametric-PET/MRI bears the potential of a more comprehensive response assessment of initial treatment strategies in cervical cancer patients.