909 results about "Normal tissue" patented technology

The invention relates to the technical field of medical image processing and tumor treatment, and provides a tumor image boundary identification method and system fused with a fluorescence boundary, and the method comprises the steps: collecting a tumor dynamic fluorescence image sequence and breathing waveform data through a fluorescence imaging device; performing multi-scale noise suppression processing on the image sequence to generate a preprocessed image without artifacts; extracting fluorescence intensity distribution characteristics through a multi-layer characteristic weighted fusion network and generating an intensity distribution matrix; constructing a motion compensation model according to the breathing waveform data, and correcting the boundary displacement of the intensity distribution matrix; fusing the corrected fluorescence features and the tumor tissue texture features to generate an initial tumor boundary contour; iterative topological optimization is carried out on the initial boundary, and boundary discontinuity is eliminated; and mapping the optimized boundary to a space coordinate system of the laser treatment equipment, generating a boundary mapping model and updating the boundary mapping model in real time. The precision and safety of laser treatment can be improved, and damage to normal tissue is reduced.

The invention discloses a tumor radiotherapy dose calibration method, and relates to the technical field of tumor radiotherapy, and the method comprises the steps: collecting multi-modal data in real time through 4D-CT, MRI and the like, extracting dynamic features through space-time registration, calculating a risk organ dose ratio and a tumor target dose deviation rate, and constructing a comprehensive evaluation function. The method has the advantages that the multi-modal dynamic data of the tumor target area are synchronously collected in real time, the space-time joint registration algorithm and the time sequence weight factor are combined, the limitation that existing static calibration depends on fixed parameters is broken through, and the method is suitable for the multi-modal dynamic data of the tumor target area. According to the method, 95% dose coverage of a tumor target region is guaranteed, and meanwhile, organ-endangering peak value receiving amount is controlled within a certain range of a clinical tolerance threshold value, so that the risk of excessive irradiation of normal tissues is reduced, and the radiotherapy dose calibration precision is prompted based on the deviation rate of a traditional method.

The invention discloses an auxiliary film reading method and system based on artificial intelligence, and the method comprises the steps: 1, collecting a pathological WSI, an electronic medical record, detection data and equipment parameters, correcting the equipment difference through adaptive dyeing normalization, and constructing a structured data package associated with an ID-timestamp of a patient; 2, developing a dynamic branch CNN, migrating teacher model knowledge through knowledge distillation, and introducing federated learning; step 3, the edge generates a thermodynamic diagram to mark a suspicious area, and the cloud outputs a structured report; step 4, constructing a normal tissue feature space by the variational auto-encoder, detecting abnormal slices and triggering expert re-checking; a reverse automatic encoder generates a pseudo-health image to compare and position a pathological area, and dynamic weight adjustment balances the federal learning convergence speed; 5, integrating the thermodynamic diagram, the gene data and the clinical indexes by a three-dimensional platform, and supporting multi-dimensional superposition display; webGL realizes browser end rendering, and NLP automatically generates a report abstract marked with a key evidence chain and is in butt joint with an international diagnosis and treatment guide.

A computer-based adaptive decision support system for radiotherapy, including: • a patient data acquisition module configured to acquire patient-specific clinical data, including an anatomical image, a physiological signal, and genomic data; • a preprocessing and feature extraction modality compatible with normalizing, preprocessing and extracting statistical features from the acquired data; • a status estimator used to provide a dynamic representation of the patient's treatment evolution status based on radiation, biological, dosimetric characteristics; • customized action rescaler to define a series of clinically meaningful treatment adjustments depending on the patient's current condition; • a reward function engine used to calculate therapeutic outcome scores based on the probability of tumor control, the probability of complications in normal tissue, and other predetermined factors; • a reinforcement learning agent that can learn and update treatment adaptation policies based on deep reinforcement learning techniques; • a clinical decision dashboard that provides recommended treatment adjustments and personalized interaction with the physician; and • a clinical integration interface adapted for exporting the customized treatment plan to an external treatment planning or delivery system.

The invention discloses a skin targeted therapy laser control method and system based on a dual-wavelength synergistic effect, and the method comprises the steps: collecting the real-time morphological characteristics and pigment distribution data of skin tissues through a multispectral imaging unit, and recognizing the optical characteristic parameters of a target treatment region; generating a dual-wavelength combination scheme through a dynamic wavelength selection algorithm based on the optical characteristic parameters and the tissue structure characteristics of the target treatment area; according to a dual-wavelength combination scheme, generating a synergistic laser sequence with a specific pulse interval and energy ratio; the synergistic laser sequence is converted into a driving signal, and a dual-wavelength laser is controlled to output composite laser; and laser output parameters are dynamically adjusted through real-time thermal diffusion monitoring and an optical feedback mechanism. By utilizing the embodiment of the invention, accurate and selective heat dissipation of skin target tissues can be realized, surrounding normal tissues are effectively protected, the treatment safety and effectiveness are improved, and side effects are reduced.

The utility model discloses a tumor electric field treatment device and a treatment system, the tumor electric field treatment device is provided with a frame body and a pole piece module, the frame body forms a skeleton structure of the treatment device, the pole piece module is attached to the frame body, the pole piece module is provided with a plurality of electrode contacts, and each electrode contact can form an active contact or a passive contact. The active contact and the radio frequency generation module can form a loop; after the treatment device is implanted into a tumor excision part, all the electrode contacts form active contacts, and all the electrode contacts and the radio frequency generation module form a loop to distinguish normal tissues from pathological tissues; after the normal tissue and the lesion tissue are distinguished, the electrode contacts in the normal tissue area form passive contacts, and the electrode contacts in the lesion tissue area form active contacts, so that targeted treatment of the lesion tissue is realized, and side effects generated by electric field treatment are reduced.

The invention relates to the technical field of biological information, in particular to an immunoreaction evaluation method based on tumor neoantigen activity sorting. The method comprises the following steps: obtaining genome data of tumor and normal tissues through whole exon sequencing, extracting multi-dimensional features of candidate somatic mutation, and screening by combining a Gaussian mixture model and a Transform model to obtain a high-confidence mutation genome set; predicting the HLA genotype of a patient based on sequencing data, translating and mutating into a peptide fragment, predicting the binding affinity of the peptide fragment and an MHC molecule by using an XGBoost model, and calculating a new antigen activity score sequence in combination with various parameters; and finally, synthesizing a new antigen peptide fragment according to a sorting result, carrying out in-vitro co-culture to detect an IFN-gamma secretion result, and dynamically optimizing a characteristic combination coefficient through a PPO algorithm to realize intelligent iterative updating, so that the accuracy of new antigen screening and the immunoreaction prediction capability are remarkably improved.

An objective of the present disclosure is to provide anti-CD137 antigen-binding molecules which have immunocyte-activating effect, cytotoxic activity, or anti-tumor activity, and meanwhile have reduced effect on non-tumor tissues such as normal tissues and produce less side effects, and methods of using the same.Anti-CD137 antigen-binding molecules which have immunocyte-activating effect, cytotoxic activity, or anti-tumor activity, and meanwhile have reduced effect on non-tumor tissues such as normal tissues and produce less side effects, are provided by discovering and producing CD137 antigen-binding molecules whose binding activity to CD137 depends on various substances (for example, small molecule compounds) in target tissues. Methods of using the same, pharmaceutical formulations, and such are also provided.The present disclosure also provides an antigen-binding molecule whose binding activity to an antigen varies depending on a small molecule compound, a preparation method thereof, and uses thereof.

The invention relates to the field of sound velocity, opto-acoustic and ultrasonic imaging, in particular to a dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging method and a dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging system. The method comprises the following steps: acquiring an ultrasonic signal and a photoacoustic signal; reconstructing a sound velocity distribution diagram according to the ultrasonic signal; based on the sound velocity distribution diagram, reconstructing a related time delay diagram; and reconstructing an ultrasonic image and a photoacoustic image based on the related time delay graph. The problems that a traditional sound velocity correction method is limited in application range, inconvenient to operate, high in cost, low in resolution and the like are solved; the adopted sound velocity correction algorithm is high in resolution, is suitable for various transducers of linear arrays, convex arrays, ring arrays, spherical arrays and the like, and is widely applied to most parts of a human body; cancerous tissues, normal tissues, muscles, fat and the like can be accurately distinguished; the ultrasonic and photoacoustic dual-mode imaging system is simple in structure, is not influenced by illumination, is high in sound velocity resolution and signal-to-noise ratio, supports seamless correction and registration of ultrasonic and photoacoustic dual-mode imaging, and promotes clinical application and development of ultrasonic and photoacoustic dual-mode imaging.

The invention belongs to the technical field of medical treatment, and discloses a radiotherapy protection system for reducing normal tissue damage, and the system comprises a real-time imaging and monitoring module which employs high-speed CT or MRI equipment to obtain 4D images of a target region and surrounding tissues of a patient in real time in a treatment process; the dynamic protection dose distribution module is used for dynamically calculating dose distribution of each radiation according to the real-time imaging data, optimizing an irradiation path and reducing the stress of normal tissues; the intelligent feedback control module is used for detecting the accumulated dose of a target region and normal tissues in real time and dynamically adjusting an irradiation strategy; inputting the real-time image and the dose monitoring data into a treatment planning system, and updating an irradiation plan; the user interaction module provides a radiotherapy real-time display interface; patient physiological data is monitored in real time. According to the invention, through dynamic real-time monitoring, dose distribution optimization and intelligent feedback control, the limitation of the traditional radiotherapy technology on real-time performance and protection effect is broken through. The system significantly reduces damage to normal tissues, improves treatment precision and patient experience, and has wide clinical application value.

The invention discloses a tumor irreversible electroporation ablation simulation prediction system, which comprises the following modules: a simulation model geometric structure establishment module, which is used for determining related parameters of a tumor irreversible electroporation ablation operation and a catheter electrode structure, and establishing a geometric structure of a simulation model; the geometric model and numerical model setting module is used for setting a geometric model and a numerical model; respectively constructing a two-electrode plate type three-dimensional finite element multi-physical field simulation model and a three-electrode plate type three-dimensional finite element multi-physical field simulation model for irreversible electroporation ablation of tumors; the data set establishment module is used for respectively performing simulation calculation on the two numerical models constructed by the geometric model and the numerical model setting module; the model training module is used for training the respective data sets of the two numerical models obtained by the data set establishing module by using a random forest regression algorithm; and the simulation prediction module is used for predicting the tumor ablation condition and the damage condition of surrounding normal tissues. The system provided by the invention can accurately predict the tumor ablation condition and the damage condition of surrounding normal tissues.

Disclosed are RAS(ON) multi-selective inhibitor compositions and methods of treating RAS protein-related diseases or disorders using an intermittent dosing regimen. RAS(ON) multi-selective inhibitors having tight binding to cyclophilin A (CypA) result in high exposure levels, prolonged tissue retention, and / or slow clearance rates, thereby increasing the risk of inhibition of wild-type RAS in normal tissues. Accordingly, provided herein are methods for the safe and effective dosing of low KD1 RAS(ON) multi-selective inhibitors using an intermittent dosing regimen. Also provided are methods of selecting or identifying such RAS(ON) multi-selective inhibitors suitable for intermittent administration.

The invention discloses a molecular probe for in-vivo copper ion detection and a preparation method and application thereof, the chemical structural formula of the molecular probe is as follows: # imgabs0 #, the molecular probe provided by the invention can specifically respond to copper ions in a tumor subacid environment so as to cause change of an absorption spectrum, and a photoacoustic signal is started so as to detect the copper ions in the tumor subacid environment. Normal tissues and tumor tissues can be accurately distinguished, and accurate detection of the copper ions in the living tumor is realized.

The invention discloses an ultra-high dose rate radiotherapy plan optimization system based on compensator modulation, and relates to the technical field of radiotherapy. A data acquisition module is used for acquiring medical image data of a patient and receiving a clinical target; the clinical target comprises a target region prescription dose, an organ-endangering limit and a minimum dose rate threshold value required for triggering and maintaining a FLASH effect; and the FLASH biological effect evaluation module is used for calculating FLASH biological effective dose distribution corresponding to the physical dose distribution through an embedded biological effect model based on the input physical dose distribution and dose rate distribution. According to the method, the physical dose is converted into the accurate FLASH biological effective dose through the improved linear quadratic model embedded with the FLASH correction factor, the target tumor killing effect is guaranteed, normal tissue protection is enhanced with the help of the tissue differentiation correction factor, the industrial pain point that the physical dose reaches the standard but the biological effect does not reach the expectation is effectively solved, and the application prospect is wide. And the treatment plan better meets the clinical curative effect and safety core requirements.

The invention discloses a method for preparing a methylacryloyl chitosan / gelatin-based hydrogel wound dressing through 3D printing and application, and relates to a method for preparing a hydrogel wound dressing and application. The problems that existing MXene is high in photo-thermal conversion temperature, and bacteria rapidly breed again after near-infrared irradiation is closed are solved. The ZGC composite hydrogel wound dressing integrates multiple functions, can simultaneously realize hemostasis, antibiosis, anti-inflammation, vascularization promotion and cell regeneration, and is especially suitable for infectious wounds. The antibacterial performance can be achieved under the activation of near-infrared light through the dual effects of a photothermal therapy and a photodynamic therapy, and meanwhile, the antibacterial effect can be achieved in cooperation with Zn < 2 + >. The ZGC composite hydrogel wound dressing can be accurately customized and printed through a 3D printing technology according to the shape and depth of a wound, the composite dressing can achieve accurate low-temperature photo-thermal treatment, meanwhile, the continuous release of Zn < 2 + > and the physical antibacterial function of MXene are maintained, normal tissue is protected while bacteria are killed, and the healing rate of an infected wound is remarkably increased.

The invention discloses an experimental method for relation between cytokine level and tumor immune microenvironment in circulation, which comprises the following steps of: S1, collecting colorectal cancer patient data and normal data for contrast, and preferably screening a gene expression data set from a Gene Expression Omnibus (GEO) database; according to the method, a plurality of gene expression data sets from the GEO database are collected and analyzed, so that differential expression genes between colorectal cancer and normal tissues can be systematically identified, and a solid foundation is provided for subsequent research. The process not only covers batch correction, normalization and batch effect elimination of data, but also visually presents data distribution changes through principal component analysis, ensures the accuracy and reliability of analysis results, confirms that IL6 and IFN gamma are one of the most critical factors affecting the colorectal cancer immune microenvironment, and participate in formation of immune infiltration.

The invention relates to the technical field of image recognition, in particular to a magnetic resonance spectrum imaging automatic positioning method and device, equipment and a medium, and the method comprises the steps: obtaining historical imaging data of different historical brain diseases; constructing a focus recognition module based on historical iconography data; scanning a transection position, a sagittal position and a coronal position of the brain of the target patient to obtain a scanning result; based on the scanning result and a focus recognition model, performing preliminary recognition on the scanning result, and determining the focus level and area of the brain of the target patient; a mode recognition method is adopted to recognize the focus level and area, and the focus parenchyma center is accurately determined; according to the method, scanning is carried out by taking the focus parenchyma center as the single voxel center and taking the focus parenchyma center and normal tissue positions around the focus area as multiple voxels, positioning of magnetic resonance spectrum imaging is realized, a machine model training mode is adopted, the focus positioning speed can be increased, and thus the accuracy of single voxel and multi-voxel spectrum imaging positioning is improved.

The invention provides a dual-targeting carrier material, a preparation method thereof and a preparation method of oleanolic acid nanoparticles wrapped by the dual-targeting carrier material, and belongs to the technical field of medicines. The oleanolic acid targeting nanoparticles are prepared by taking a dual-targeting high-molecular copolymer as a carrier material and adopting an emulsification-solvent evaporation method, so that the oleanolic acid can be protected from being quickly degraded, and the in-vivo circulation time of the oleanolic acid can be prolonged. Meanwhile, targeted delivery of oleanolic acid is realized through a targeted group, the concentration of the drug in tumor tissues is improved, and toxic and side effects on normal tissues are reduced. An MTT method is adopted, the inhibition effect of the oleanolic acid nanoparticles on cell growth is researched, and the result shows that the oleanolic acid targeting nanoparticles have a stronger effect of inhibiting tumor cell proliferation compared with an oleanolic acid raw material medicine.

Surgical marker systems and methods for delineating a lesion margin of a subject are provided. An example system includes a handheld probe device configured to capture an optical coherence tomography (OCT) image and a processor coupled to a memory. The handheld probe device includes a handheld probe including a fiber-optic probe assembly and a marker assembly. The processor is configured to: segment, by a neural network, each pixels of the OCT into different tissue-type categories; generate one or more feature vectors based at least in part on the segmented pixels; determine, by a one-class classifier, a boundary location in the OCT image between a normal tissue and an abnormal tissue of the tissue structure; and control the marker assembly to selectively create a visible label on a tissue location of the subject, the tissue location corresponding to the boundary location.

The invention belongs to the technical field of physical thermal ablation, and relates to a physical thermal ablation energy regulation and control method based on intelligent feedback, and the method comprises the steps: collecting point-shaped temperature data, impedance data and ultrasonic data, eliminating the asynchronization and heterogeneity problems through space-time alignment, and combining with focus region segmentation, thereby achieving the energy regulation and control of the physical thermal ablation. Discrete data and continuous images are integrated into a voxelization data cube containing space coordinates, physical attributes and semantic tags, then the temperature change rate and the impedance change rate are calculated based on the voxelization data cube, and then a morphological prediction network is fused with multi-modal features to output a voxel-level ablation probability graph. The method comprises the following steps: realizing prospective prediction of an ablation range, ensuring ablation accuracy by morphological deviation through a three-layer parallel regulation and control strategy, preventing and controlling local overheating by temperature gradient, avoiding tissue carbonization by an impedance change rate, and cooperatively deciding through multi-dimensional indexes to solve the contradiction that single regulation and control cannot give consideration to accurate coverage of a focus and protection of normal tissues; and misjudgment caused by abnormity of single data is avoided.

The invention proposes a voxel-level dose distribution prediction method, and the method comprises the steps: obtaining a detection image of a target object when each tracer is independently introduced under the condition that a plurality of tracers are independently introduced into the target object; performing image standardization processing on the detection image corresponding to each tracer agent to obtain a standardized image corresponding to each tracer agent; and taking the standardized images corresponding to the various tracers as input information of a deep learning model, and determining a comprehensive three-dimensional dose prediction result of the target object under the various tracers through the deep learning model. According to the technical scheme, the accuracy of dose prediction in nuclide therapy is improved, full-link automation from image acquisition to dose planning is realized, the generated dose distribution not only meets the clinical requirement of precise coverage of a target region, but also conforms to the radiotherapy principle of normal tissue protection, and reliable technical support is provided for personalized precise radiotherapy.

The invention relates to the cross technical field of artificial intelligence and medical image processing, in particular to a medical image segmentation system and method based on a wavelet bridge diffusion model and an efficient conditional random field. A WBDM-ECRF framework is constructed and comprises a discrete wavelet transform module, a BDM-T module, a BDM-S module and an ECRF module; decomposing the image through discrete wavelet transform, extracting a low-frequency sub-band, and enhancing the contrast ratio of a focus and normal tissues; the BDM-T takes U-Net as a backbone, integrates a FlashAttention mechanism, and optimizes a variance formula to realize efficient training; the BDM-S adopts a leapfrog sampling strategy, so that the reasoning time is greatly shortened; the ECRF introduces a multivariate potential function of a structural similarity index and smooth operation through edge expansion, and accurately optimizes edge segmentation. According to the method, the dependence of marked data is reduced, the training and reasoning efficiency is improved, the problem of fuzzy edge segmentation is solved, the Dice coefficient and intersection-union ratio performance on the ISIC data set is excellent, and reliable quantitative support is provided for disease diagnosis and treatment.

The invention relates to the field of methylation sequencing, in particular to a screening method of methylation sequencing fragments. The method comprises: 1) using a healthy sample, establishing a signal baseline by constructing an n-order Markov chain model, the healthy sample containing a methylation sequencing result, and a sequencing fragment of the healthy sample originating from an rDNA region; and 2) filtering a to-be-detected sample by using the established signal baseline, the to-be-detected sample containing a methylation sequencing result, and a sequencing fragment of the to-be-detected sample being derived from an rDNA region. According to the method disclosed by the invention, background noise from normal tissues is effectively filtered, and methylation signals (especially rDNA methylation signals) related to diseases are effectively screened out.

The invention discloses a colorectal cancer radiotherapy sensitization medicine and application thereof, belongs to the field of biological medicine, and particularly relates to a colorectal cancer radiotherapy sensitization medicine which comprises active pharmaceutical ingredients and a solvent, the active pharmaceutical ingredients comprise doxorubicin and a nitrogen-containing compound, the nitrogen-containing compound comprises quinoline-6-carbohydrazide and N-benzyloxymethyl-4-nitroimidazole, and the nitrogen-containing compound comprises quinoline-6-carbohydrazide and The colorectal cancer radiotherapy sensitization medicine disclosed by the invention focuses on a key driving gene FOXP4 for colorectal cancer radiotherapy resistance, and FOXP4 protein is degraded through a ubiquitin-proteasome way, so that not only can the sensitivity of tumor cells to radiotherapy be remarkably improved and tumor growth be inhibited, but also damage to normal tissues is reduced; moreover, the problem of drug resistance easily generated by a traditional method is effectively avoided, the research and development cost is greatly reduced, clinical transformation is accelerated, and the method has a good clinical application prospect.

The present invention relates to a method and system for predicting the probability of normal tissue damage based on deep learning, belonging to the technical field of medical data processing. The method includes: obtaining the tumor dose data, basic information, and tumor diagnosis information of a patient; the tumor dose data is formulated by a doctor based on the patient's tumor diagnosis information before radiotherapy for the patient; the basic information includes at least the patient's age; based on the tumor dose data, obtaining the dose volume histogram of the patient; based on the dose volume histogram, obtaining the volume parameters and biological equivalent dose of the patient's normal tissue; inputting the volume parameters and biological equivalent dose of the patient's normal tissue, the patient's basic information, and tumor diagnosis information into a normal tissue damage probability prediction model constructed based on deep learning to obtain the damage probability of the patient's normal tissue. Compared with traditional statistical models or empirical formulas, the prediction accuracy of this method is higher, and it can more accurately evaluate the damage probability of normal tissue.

The present invention provides compositions and methods for preventing, alleviating, or treating subjects having toxic agent-induced injury. The present invention also provides compositions and methods for preventing, alleviating or treating tissue damage caused by exposure to toxic agents or restoring at least a portion of normal tissue function. In some embodiments, the methods comprise administering to the subject a therapeutically effective amount of a pharmaceutical composition comprising at least one potassium channel blocker. In some embodiments, the potassium channel blocker includes 4-aminopyridine, a derivative thereof, or a combination thereof. In some embodiments, the pharmaceutical compositions may be administered with additional therapeutic agents, such as anticonvulsions.

The invention provides application of lactic acid modified histone H3 in preparation of drugs and / or diagnostic kits for preventing and / or treating pancreatic ductal adenocarcinoma, and belongs to the technical field of disease diagnosis and / or treatment. The invention provides application of a lactic acid modified histone H3 as a target spot in preparation of a pancreatic ductal adenocarcinoma diagnostic kit or a medicine for preventing and / or treating pancreatic ductal adenocarcinoma. The site of lactic acid modification is 23-site lysine. The expression of H3K23la detected in clinical sample tissues in pancreatic ductal adenocarcinoma tumor tissues is obviously higher than that in para-carcinoma normal tissues, overexpression and non-expression of H3K23la in cells are regulated and controlled through in-vitro experiments in combination with overexpression and knock-down technologies, and results show that proliferation, invasion and migration capacities of pancreatic ductal adenocarcinoma cells are remarkably inhibited, so that the pancreatic ductal adenocarcinoma cells are remarkably inhibited. Therefore, the H3K23la can be used as a target spot for diagnosis and treatment of the pancreatic duct adenocarcinoma, and has wide application in diagnosis or treatment of the pancreatic duct adenocarcinoma.

The invention belongs to the technical field of nano-carriers, and particularly relates to a casein-based nano-carrier with slow release and pH / NIR dual response as well as a preparation method and application thereof, casein is combined with hollow copper sulfide nano-particles to load drugs, the nano-carrier with slow release and pH / NIR dual response is generated, and the drug loading rate is as high as 96.84%. Experiments show that the nano-carrier can accurately control drug release under specific pH and near-infrared light irradiation, so that the drug treatment efficiency is improved, and side effects on normal tissues are reduced.

The invention discloses a colorectal cancer prognosis model construction method based on fatty acid metabolism related genes, and belongs to the technical field of biomedicine, and the colorectal cancer prognosis model construction method comprises the following steps: S1, obtaining transcriptome data of a colorectal cancer diagnosis individual from a TCGA database; s2, performing difference analysis on fatty acid metabolism related gene expression data of the colorectal cancer tissue and the normal tissue, and screening out differentially expressed genes; s3, performing single-factor Cox regression analysis on the differentially expressed genes, and screening out genes related to colorectal cancer prognosis; according to the construction method of the colorectal cancer prognosis model based on the fatty acid metabolism related genes, provided by the invention, the tumor immunotherapy reactivity is evaluated by introducing TIDE scores, and the prior art is improved, so that the immune escape potential and the immunotherapy effect of tumor subtypes are analyzed. The prognosis of a colorectal cancer patient is effectively predicted, and a new molecular marker is provided for personalized treatment of the colorectal cancer.

Methods, devices and systems are described that enable identification of cancerous or pre-cancerous colon tissue. The described methods and systems rely on non-imaging. randomly sampled second harmonic generation (SHG) intensity measurements that are sufficient for differentiating between tumor and normal tissue. The disclosed methods and system further provide for angle-resolved SHG measurements associated with forward and backward scattered light that eliminate the need to obtain paired normal and cancer-suspicious measurements in each patient using the described techniques.