Shedding Light on Colorectal Cancer: An In Vivo Raman Spectroscopy Approach Combined with Deep Learning Analysis.

Raman spectroscopy has emerged as a powerful tool in medical, biochemical, and biological research with high specificity, sensitivity, and spatial and temporal resolution. Recent advanced Raman systems, such as portable Raman systems and fiber-optic probes, provide the potential for accurate in vivo discrimination between healthy and cancerous tissues. In our study, a portable Raman probe spectrometer was tested in immunosuppressed mice for the in vivo localization of colorectal cancer malignancies from normal tissue margins. The acquired Raman spectra were preprocessed, and principal component analysis (PCA) was performed to facilitate discrimination between malignant and normal tissues and to highlight their biochemical differences using loading plots. A transfer learning model based on a one-dimensional convolutional neural network (1D-CNN) was employed for the Raman spectra data to assess the classification accuracy of Raman spectra in live animals. The 1D-CNN model yielded an 89.9% accuracy and 91.4% precision in tissue classification. Our results contribute to the field of Raman spectroscopy in cancer diagnosis, highlighting its promising role within clinical applications.

Clustered DNA Damage Patterns after Proton Therapy Beam Irradiation Using Plasmid DNA.

Modeling ionizing radiation interaction with biological matter is a major scientific challenge, especially for protons that are nowadays widely used in cancer treatment. That presupposes a sound understanding of the mechanisms that take place from the early events of the induction of DNA damage. Herein, we present results of irradiation-induced complex DNA damage measurements using plasmid pBR322 along a typical Proton Treatment Plan at the MedAustron proton and carbon beam therapy facility (energy 137-198 MeV and Linear Energy Transfer (LET) range 1-9 keV/µm), by means of Agarose Gel Electrophoresis and DNA fragmentation using Atomic Force Microscopy (AFM). The induction rate Mbp-1 Gy-1 for each type of damage, single strand breaks (SSBs), double-strand breaks (DSBs), base lesions and non-DSB clusters was measured after irradiations in solutions with varying scavenging capacity containing 2-amino-2-(hydroxymethyl)propane-1,3-diol (Tris) and coumarin-3-carboxylic acid (C3CA) as scavengers. Our combined results reveal the determining role of LET and Reactive Oxygen Species (ROS) in DNA fragmentation. Furthermore, AFM used to measure apparent DNA lengths provided us with insights into the role of increasing LET in the induction of highly complex DNA damage.

Ipsilateral and contralateral cerebro-cerebellar white matter connections: A diffusion tensor imaging study in healthy adults.

BACKGROUND AND PURPOSE: The cerebellum has a pivotal role in regulating human behavior; yet whether this function is mediated only through contralateral cerebro-cerebellar pathways is under-investigated. Thus, we examined feed-backward and feed-forward ipsilateral and contralateral cerebro-cerebellar connections using a detereministic diffusion tensor imaging (DTI) algorithm, the robustness of which was also estimated using phantom DTI data. MATERIALS AND METHODS: Fifty-one healthy controls (22-60 years old; 15 males/36 females) were scanned in a 3T MRI scanner with a 30-direction DTI sequence. Multiple region-of-interest (ROI) method was applied for the reconstruction of the ipsilateral and contralateral (based on cerebellar seed ROI) fronto-ponto-cerebellar (FPC), parieto-ponto-cerebellar (PPC), temporo-ponto-cerebellar (TPC), occipito-ponto-cerebellar (OPC) and dentate-rubro-thalamo-cortical (DRTC) tract bilaterally using the Brainance DTI Suite. A realistic diffusion MR phantom was used to evaluate the fiber tracking methodology for 16 fibers containing crossing, kissing, splitting and bending configurations. RESULTS: Both contralateral and ipsilateral FPC, PPC, OPC and ipsilateral DRTC tracts were successfully reconstructed; the contralateral DRTC tract was not reconstructed in all subjects. Also, the TPC tract was not reproduced in several subjects mostly regarding the contralateral connection. Descriptive DTI measures (number of fibers, fractional anisotropy, radial and axial diffusivity) are presented for each tract. Regarding phantom data, Brainance DTI Suite returned a dataset of 16 fibers that almost perfectly matched the 16 ground truth fibers. CONCLUSIONS: We identified ipsilateral and contralateral connections using a clinically applicable DTI sequence, a robust deterministic algorithm and an unbiased methodology, which can be applied in daily practice in different brain pathologies.

Introduction of an effective method for the optimization of CT protocols using iterative reconstruction algorithms: comparison with patient data.

OBJECTIVE: The purpose of this study is to introduce an efficient method for the optimization of iterative reconstruction CT protocols based on phantom image analysis and the comparison of obtained results with actual patient data. MATERIALS AND METHODS: We considered chest, abdomen, and pelvis CT examinations before the installation of an iterative reconstruction algorithm (iDose4) to define the exposure parameters used in clinical routine with filtered back projection (FBP). The body area of a CT phantom was subsequently scanned with various tube voltages and tube currents-exposure time products, and acquired data were reconstructed with FBP and different levels of iDose4. The contrast-to-noise ratio (CNR) for FBP with the original exposure parameters was calculated to define the minimum acceptable CNR value for each tube voltage. Then, an optimum tube current-exposure time products for each tube voltage and level of iterative reconstruction was estimated. We also compared findings derived by the phantom with real patient data by assessing dosimetric and image quality indexes from a patient cohort scanned with exposure parameters gradually adjusted during 1 year of adoption of iDose4. RESULTS: By use of the proposed phantom method, dose reduction up to 75% was achievable, whereas for an intermediate level of iteration (level 4), the dose reduction ranged between 50% and 60%, depending on the tube voltage. For comparison, with the gradual adjustment of exposure settings, the corresponding dose reduction for the same level of iteration was about 35%. CONCLUSION: The proposed method provides rapid and efficient optimization of CT protocols and could be used as the first step in the optimization process.

Computed tomography radiation dosimetry: from the indicators to the indications.

The technological advances in computed tomography (CT) scanners and their continuously increased use have raised concern about the patient-induced risks from the CT procedures. In the present review, all available dose metrics used in CT dosimetry are described, evaluated, and compared. The various models and methodologies currently existing for the estimation of the effective dose and, by extension, the carcinogenesis probability as well as the way that this is derived from dose descriptors are also considered.

Effect of iDose4 iterative reconstruction algorithm on image quality and radiation exposure in prospective and retrospective electrocardiographically gated coronary computed tomographic angiography.

OBJECTIVES: The aims of this study were to compare a commercially available reconstruction algorithm (iDose4) with filtered back projection (FBP) in terms of image quality (IQ) for both retrospective electrocardiographically gated and prospective electrocardiographically triggered cardiac computed tomographic angiography (CCTA) protocols and to evaluate the achievable radiation dose reduction. METHODS: A total cohort of 58 patients underwent either prospective CTCA or retrospective CTCA with full or reduced tube current-time product (in milliampere-second) protocol on a 64-slice multidetector computed tomographic scanner. All images were reconstructed with FBP, whereas the reduced milliampere-second images were also reconstructed using 2 levels (levels 4 and 6) of iDose4. Subjective and objective IQ was evaluated. RESULTS: Dose reductions of 43% in the retrospective CCTA protocol and 27% in the prospective CCTA protocol were achieved without compromising IQ. In the prospective CCTA protocol, the reduced-dose images were highly scored; thus, additional reduction of exposure settings is feasible. In the retrospective acquisition, dose reduction has led to similar IQ scores between the reduced-dose iDose4 images and the full-dose FBP images. Considering different reconstructions (FBP, iDose-L4 and -L6) of the same acquisition data, increase in iDose4 level resulted in less noisy images. A slight improvement was also noticed in all IQ indices; however, this improvement was not statistically significant for both acquisition protocols. CONCLUSIONS: This study demonstrated that the application of iDose at CCTA facilitates significant radiation dose reduction by maintaining diagnostic quality. The combination of iDose4 with prospective acquisition is able to significantly reduce effective dose associated with CTCA at values of approximately 2 mSv and even lower.

A new era in computed tomographic dose optimization: the impact of iterative reconstruction on image quality and radiation dose.

The ongoing evolution of computer technology has made the use of iterative reconstruction (IR) algorithms clinically applicable. We reviewed current literature on the clinical use of IR against filtered back projection algorithms in terms of image quality and radiation dose. Iterative reconstruction algorithms provide equal or better image quality compared with filtered back projection, with dose reduction ranging from 25% to 98.6%. However, several studies have reported that the superior results of IR regarding objective evaluation are not always favorably interpreted by radiologists. Further clinical evaluation is needed to certify the optimal tradeoff between imaging quality and radiation dose, and radiologists need to become more familiar with the new appearance of computed tomographic images.

DIAGNOSTIC REFERENCE LEVELS AND COMPLEXITY INDICES IN INTERVENTIONAL RADIOLOGY.

The establishment of typical diagnostic reference levels (DRLs) values according to the complexity indices (CIs) for hepatic chemoembolisation (HC), iliac stent placement (ISP) and femoropopliteal revascularisation (FR) is reported in this study. To estimate patients' stochastic effects, effective dose was calculated through dose area product (DAP) values of this study and E/DAP conversion factors derived from the literature. Data for DAP, Reference Air Kerma (Ka,r) and fluoroscopy time (FT) were collected for 218 patients and CIs were assigned to each procedure to extract DRLs. To estimate effective dose, conversion factors and DAP values were used for seven IR procedures. DRL values for DAP were 141, 130 and 28 Gy*cm2 for HC, ISP, and FR, respectively. The corresponding DRL values for Ka,r were 634.6, 300.1 and 112.0 mGy, and for FT were 15.3, 12.4 and 17.9 min, respectively. CIs in interventional radiology are a useful tool for the optimisation of DRLs since they contribute to patient's doses.

Patient Dose Estimation in Computed Tomography-Guided Biopsy Procedures.

This study establishes typical Diagnostic Reference Levels (DRL) values and assesses patient doses in computed tomography (CT)-guided biopsy procedures. The Effective Dose (ED), Entrance Skin Dose (ESD), and Size-Specific Dose Estimate (SSDE) were calculated using the relevant literature-derived conversion factors. A retrospective analysis of 226 CT-guided biopsies across five categories (Iliac bone, liver, lung, mediastinum, and para-aortic lymph nodes) was conducted. Typical DRL values were computed as median distributions, following guidelines from the International Commission on Radiological Protection (ICRP) Publication 135. DRLs for helical mode CT acquisitions were set at 9.7 mGy for Iliac bone, 8.9 mGy for liver, 8.8 mGy for lung, 7.9 mGy for mediastinal mass, and 9 mGy for para-aortic lymph nodes biopsies. In contrast, DRLs for biopsy acquisitions were 7.3 mGy, 7.7 mGy, 5.6 mGy, 5.6 mGy, and 7.4 mGy, respectively. Median SSDE values varied from 7.6 mGy to 10 mGy for biopsy acquisitions and from 11.3 mGy to 12.6 mGy for helical scans. Median ED values ranged from 1.6 mSv to 5.7 mSv for biopsy scans and from 3.9 mSv to 9.3 mSv for helical scans. The study highlights the significance of using DRLs for optimizing CT-guided biopsy procedures, revealing notable variations in radiation exposure between helical scans covering entire anatomical regions and localized biopsy acquisitions.

Extended Analysis of Raman Spectra Using Artificial Intelligence Techniques for Colorectal Abnormality Classification.

Raman spectroscopy (RS) techniques are attracting attention in the medical field as a promising tool for real-time biochemical analyses. The integration of artificial intelligence (AI) algorithms with RS has greatly enhanced its ability to accurately classify spectral data in vivo. This combination has opened up new possibilities for precise and efficient analysis in medical applications. In this study, healthy and cancerous specimens from 22 patients who underwent open colorectal surgery were collected. By using these spectral data, we investigate an optimal preprocessing pipeline for statistical analysis using AI techniques. This exploration entails proposing preprocessing methods and algorithms to enhance classification outcomes. The research encompasses a thorough ablation study comparing machine learning and deep learning algorithms toward the advancement of the clinical applicability of RS. The results indicate substantial accuracy improvements using techniques like baseline correction, L2 normalization, filtering, and PCA, yielding an overall accuracy enhancement of 15.8%. In comparing various algorithms, machine learning models, such as XGBoost and Random Forest, demonstrate effectiveness in classifying both normal and abnormal tissues. Similarly, deep learning models, such as 1D-Resnet and particularly the 1D-CNN model, exhibit superior performance in classifying abnormal cases. This research contributes valuable insights into the integration of AI in medical diagnostics and expands the potential of RS methods for achieving accurate malignancy classification.

Nanoparticle-Mediated Radiotherapy: Unraveling Dose Enhancement and Apoptotic Responses in Cancer and Normal Cell Lines.

Cervical cancer remains a pressing global health concern, necessitating advanced therapeutic strategies. Radiotherapy, a fundamental treatment modality, has faced challenges such as targeted dose deposition and radiation exposure to healthy tissues, limiting optimal outcomes. To address these hurdles, nanomaterials, specifically gold nanoparticles (AuNPs), have emerged as a promising avenue. This study delves into the realm of cervical cancer radiotherapy through the meticulous exploration of AuNPs' impact. Utilizing ex vivo experiments involving cell lines, this research dissected intricate radiobiological interactions. Detailed scrutiny of cell survival curves, dose enhancement factors (DEFs), and apoptosis in both cancer and normal cervical cells revealed profound insights. The outcomes showcased the substantial enhancement of radiation responses in cancer cells following AuNP treatment, resulting in heightened cell death and apoptotic levels. Significantly, the most pronounced effects were observed 24 h post-irradiation, emphasizing the pivotal role of timing in AuNPs' efficacy. Importantly, AuNPs exhibited targeted precision, selectively impacting cancer cells while preserving normal cells. This study illuminates the potential of AuNPs as potent radiosensitizers in cervical cancer therapy, offering a tailored and efficient approach. Through meticulous ex vivo experimentation, this research expands our comprehension of the complex dynamics between AuNPs and cells, laying the foundation for their optimized clinical utilization.

Quantum dots hold promise for early cancer imaging and detection.

Despite all major breakthroughs in recent years of research concerning the complex events that lead to cancer expression and metastasis, we are not yet able to effectively treat cancer that has spread to vital organs. The various clinical phases originating from cancer diagnosis through treatment and prognosis require a comprehensive understanding of these events, to utilise pre-symptomatic, minimally invasive and targeted cancer management techniques. Current imaging modalities such as ultrasound, computed tomography, magnetic resonance imaging and gamma scintigraphy facilitate the pre-operative study of tumours, but they have been rendered unable to visualise cancer in early stages, due to their intrinsic limitations. The semiconductor nanocrystal quantum dots (QDs) have excellent photo-physical properties, and the QDs-based probes have achieved encouraging developments in cellular (in vitro) and in vivo molecular imaging. However, the same unique physical and chemical properties which renowned QDs attractive may be associated with their potentially catastrophic effects on living cells and tissues. There are critical issues that need to be further examined to properly assess the risks associated with the manufacturing and use of QDs in cancer management. In this review, we aim to describe the current utilisation of QDs as well as their future prospective to decipher and confront cancer.

A comprehensive method for calculating patient effective dose and other dosimetric quantities from CT DICOM images.

OBJECTIVE: The purpose of this article is to present a method for the calculation of effective dose using the DICOM header information of CT images. MATERIALS AND METHODS: Using specialized software, the DICOM data were automatically extracted into a spreadsheet containing embedded functions for calculating effective dose. These data were used to calculate the dose-length product (DLP) fraction that corresponds to each image, and the respective effective dose was obtained by multiplying the image DLP by a conversion coefficient that was automatically selected depending on the CT scanner, the tube potential, and the anatomic position to which each image corresponded. The total effective dose was calculated as the sum of effective doses of all images plus the contribution of overscan. The conversion coefficient tables were derived using dosimetry calculator software for both the International Commission on Radiological Protection (ICRP) 60 and ICRP 103 organ-weighting schemes. This method was applied for 90 chest, abdomen-pelvis, and chest-abdomen-pelvis examinations performed in three different MDCT scanners. RESULTS: The DLP values calculated with this method were in good agreement with those calculated by the CT scanners' software. The effective dose values calculated using the ICRP 103 conversion coefficient compared with those calculated using the ICRP 60 conversion coefficient were roughly equal for the chest-abdomen-pelvis examinations, smaller for the abdomen-pelvis examinations, and larger for the chest examinations. The applicability of this method for estimating organ doses was also explored. CONCLUSION: With this method, all patient dose-related quantities, such as the DLP, effective dose, and individual organ doses, can be calculated.

Quantification of Nanoscale Dose Enhancement in Gold Nanoparticle-Aided External Photon Beam Radiotherapy.

The recent progress in Nanotechnology has introduced Gold Nanoparticles (AuNPs) as promising radiosensitizing agents in radiation oncology. This work aims to estimate dose enhancement due to the presence of AuNPs inside an irradiated water region through Monte Carlo calculations. The GATE platform was used to simulate 6 MV photon histories generated from a TrueBeam® linear accelerator with and without a Flattening Filter (FF) and model AuNPs clusters. The AuNPs size, concentration and distribution pattern were examined. To investigate different clinical irradiation conditions, the effect of field size, presence of FF and placement of AuNPs in water were evaluated. The range of Dose Enhancement Factors (DEF = DoseAu/DoseWater) calculated in this study is 0.99 ± 0.01-1.26 ± 0.02 depending on photon beam quality, distance from AuNPs surface, AuNPs size and concentration and pattern of distribution. The highest DEF is reported for irradiation using un-flattened photon beams and at close distances from AuNPs. The obtained findings suggest that dose deposition could be increased in regions that represent whole cells or subcellular targets (mitochondria, cell nucleus, etc.). Nevertheless, further and consistent research is needed in order to make a step toward AuNP-aided radiotherapy in clinical practice.

Ag/Au Bimetallic Nanoparticles Trigger Different Cell Death Pathways and Affect Damage Associated Molecular Pattern Release in Human Cell Lines.

Apoptosis induction is a common therapeutic approach. However, many cancer cells are resistant to apoptotic death and alternative cell death pathways including pyroptosis and necroptosis need to be triggered. At the same time, danger signals that include HMGB1 and HSP70 can be secreted/released by damaged cancer cells that boost antitumor immunity. We studied the cytotoxic effects of AgAu NPs, Ag NPs and Au NPs with regard to the programmed cell death (apoptosis, necroptosis, pyroptosis) and the secretion/release of HSP70 and HMGB1. Cancer cell lines were incubated with 30, 40 and 50 µg/mL of AgAu NPs, Ag NPs and Au NPs. Cytotoxicity was estimated using the MTS assay, and mRNA fold change of CASP1, CASP3, BCL-2, ZPB1, HMGB1, HSP70, CXCL8, CSF1, CCL20, NLRP3, IL-1ß and IL-18 was used to investigate the associated programmed cell death. Extracellular levels of HMGB1 and IL-1ß were investigated using the ELISA technique. The nanoparticles showed a dose dependent toxicity. Pyroptosis was triggered for LNCaP and MDA-MB-231 cells, and necroptosis for MDA-MB-231 cells. HCT116 cells experience apoptotic death and show increased levels of extracellular HMGB1. Our results suggest that in a manner dependent of the cellular microenvironment, AgAu NPs trigger mixed programmed cell death in P53 deficient MDA-MB-231 cells, while they also trigger IL-1ß release in MDA-MB-231 and LNCaP cells and release of HMGB1 in HCT116 cells.

Nanomedicine approaches for treatment of hematologic and oncologic malignancies.

Cancer is a leading cause of death worldwide. Nowadays, the therapies are inadequate and spur demand for improved technologies. Rapid growth in nanotechnology and novel nanomedicine products represents an opportunity to achieve sophisticated targeting strategies and multi-functionality. Nanomedicine is increasingly used to develop new cancer diagnosis and treatment methods since this technology can modulate the biodistribution and the target site accumulation of chemotherapeutic drugs, thereby reducing their toxicity. Cancer nanotechnology and cancer immunotherapy are two parallel themes that have emerged over the last few decades while searching for a cure for cancer. Immunotherapy is revolutionizing cancer treatment, as it can achieve unprecedented responses in advanced-stage patients, including complete cures and long-term survival. A deeper understanding of the human immune system allows the establishment of combination regimens in which immunotherapy is combined with other treatment modalities (as in the case of the nanodrug Ferumoxytol). Furthermore, the combination of gene therapy approaches with nanotechnology that aims to silence or express cancer-relevant genes via one-time treatment is gradually progressing from bench to bedside. The most common example includes lipid-based nanoparticles that target VEGF-Α and KRAS pathways. This review focuses on nanoparticle-based platforms utilized in recent advances aiming to increase the efficacy of currently available cancer therapies. The insights provided and the evidence obtained in this paper indicate a bright future ahead for immuno-oncology applications of engineering nanomedicines.

Raman Spectroscopy: A Personalized Decision-Making Tool on Clinicians' Hands for In Situ Cancer Diagnosis and Surgery Guidance.

Accurate in situ diagnosis and optimal surgical removal of a malignancy constitute key elements in reducing cancer-related morbidity and mortality. In surgical oncology, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. Conventional imaging techniques have attempted to serve as adjuvant tools for in situ biopsy and surgery guidance. However, no single imaging modality has been proven sufficient in terms of specificity, sensitivity, multiplexing capacity, spatial and temporal resolution. Moreover, most techniques are unable to provide information regarding the molecular tissue composition. In this review, we highlight the potential of Raman spectroscopy as a spectroscopic technique with high detection sensitivity and spatial resolution for distinguishing healthy from malignant margins in microscopic scale and in real time. A Raman spectrum constitutes an intrinsic "molecular finger-print" of the tissue and any biochemical alteration related to inflammatory or cancerous tissue state is reflected on its Raman spectral fingerprint. Nowadays, advanced Raman systems coupled with modern instrumentation devices and machine learning methods are entering the clinical arena as adjunct tools towards personalized and optimized efficacy in surgical oncology.

FDXR Gene Expression after in Vivo Radiation Exposure of Pediatric Patients Undergoing Interventional Cardiology Procedures.

BACKGROUND: Ferredoxin reductase (FDXR) has already been reported as a promising biomarker for estimating radiation doses in radiotherapy. This study aimed to investigate the responsiveness of FDXR on pediatric population exposed to ionizing radiation (X-rays) during pediatric interventional cardiology (IC) procedures. PATIENTS AND METHODS: Peripheral blood was collected by venipuncture from 24 pediatric donors before and 24 hours after the IC procedure. To estimate the effective dose, demographic data and Air Kerma-Area Product (PKA) were recorded for each patient. The relative quantification (RQ) of the FDXR gene in irradiated patient blood samples compared to the non-irradiated blood samples was determined using qPCR analysis. The relative values of FDXR were log- transformed. RESULTS: The effective dose ranged from 0.002 mSv to 8.004 mSv. Over this radiation exposure range, the FDXR gene expression varied randomly with the effective dose. Up-regulation in FDXR expression was observed in 17 patients and down-regulation in 7 patients. CONCLUSIONS: Further studies in a larger cohort of pediatric patients along with the record of clinical data are needed to determine whether FDXR gene expression is an effective biomarker for radiation exposure estimation in pediatric imaging.

The Importance of Radiation Protection Education and Training for Medical Professionals of All Specialties.

The article is part of the series of articles on radiation protection. You can find further articles in the special section of the CVIR issue. Lately, more advanced techniques have been introduced in medical imaging expanding the diagnostic and therapeutic applications of ionizing radiation. Among the various strategies that have been proposed for the management of radiation exposure, education and training seem to have a strong impact on radiation protection and dose reduction. However, according to several studies, medical professionals appear to lack knowledge on basic radiation protection aspects. Therefore, the establishment of an accreditation and certification system in radiation protection for all medical professionals employing ionizing radiation is considered as high priority. The purpose of this review article is to highlight the importance of education and training in radiation protection, provide recommendations for an effective educational program and propose an educational program structure for the different medical specialties.

Radiation Exposure in Pediatric Interventional Procedures.

The article is part of the series of articles on radiation protection. You can find further articles in the special section of the CVIR issue. The expanding applications of interventional procedures coupled with the potential harmful effects of ionizing radiation highlight the need to assess the delivered radiation dose and establish an effective radiation protection program, particularly in the radiosensitive pediatric population. Given the complexity and heterogeneity of interventional procedures as well as the unique characteristics of children, the management of radiation dose is proving to be quite challenging. The aim of the current article is to provide an overview of the radiation exposure in pediatric patients during interventional procedures focusing on the importance of radiation protection in the pediatric population, the reported radiation doses and the techniques of minimizing radiation dose.