Non-invasive cancer detection with breath analyzer

Abstract

Disclosed is a breath analyzer system for detecting volatile organic compounds (VOCs) in exhaled breath, comprising: a photoacoustic detection chamber configured to receive exhaled breath and generate acoustic waves through interaction with a modulated laser source; a tunable multi-wavelength quantum cascade laser (QCL) capable of targeting specific VOCs by adjusting its wavelength; a plurality of Acoustic sensors configured to detect acoustic waves and convert them into corresponding electrical signals; a signal processing unit configured to filter noise, isolate target frequencies, and analyze signals using machine learning algorithms; and an IoT-enabled interface for real-time data transmission and remote monitoring.

Description

LR-AAR-2918 “NON-INVASIVE CANCER DETECTION WITH BREATH ANALYZER”FIELD OF INVENTION

[0001] The present invention pertains to the domain of advanced medical diagnostics and applied photonics, with particular emphasis on photoacoustic spectroscopy for detecting volatile organic compounds (VOCs) in exhaled breath enabling early cancer detection. More particularly, the disclosure leverages the interaction of laser-induced acoustic waves with specific gas-phase biomarkers, enabling precise, non-invasive diagnostics. The invention is specifically designed to facilitate early detection of diseases, particularly lung cancer, by analyzing trace molecular signatures in real-time.BACKGROUND ART

[0002] Lung cancer is a significant global health challenge, with millions of lives lost each year due to the late-stage diagnosis of the disease. The majority of lung cancer cases are diagnosed when treatment options are limited, and the prognosis is poor. This late detection occurs because traditional diagnostic methods, such as CT scans and biopsies, are typically only administered once symptoms become apparent. By that point, the disease is often in advanced stages, reducing the patient’s chance of survival. The reliance on invasive, costly, and infrastructure-dependent tools has limited the ability of healthcare systems to provide timely, widespread screening for at-risk populations.

[0003] In recent years, medical research has identified volatile organic compounds (VOCs) in exhaled breath as potential biomarkers for a variety of diseases, including lung cancer. These VOCs result from metabolic changes in cells and tissues, which can differ in healthy individuals compared to those with disease. The ability to non-invasively detect such biomarkers holds promise for shifting the paradigm of disease detection towards earlier, more accurate diagnostics. However, current methods to detect these biomarkers, such as gas chromatography and mass spectrometry, while sensitive, areCONFIDENTIALLR-AAR-2918 impractical for widespread clinical use due to their high cost, complexity, and time-consuming nature. Additionally, electrochemical sensors and other simpler technologies have faced limitations in sensitivity, especially when dealing with the very low concentrations of VOCs (in parts per billion) necessary for early-stage detection of diseases like lung cancer.

[0004] In India, the number of lung cancer cases is increasing. According to specialists from the Indian Council of Medical Research (ICMR), lung cancer cases in India are predicted to increase more than seven times by 2025 compared to the situation a decade ago. Whats worse is that roughly 45% of lung cancer patients find out they have the disease, when it has already spread to other body areas. Indians typically receive their diagnosis in their mid-50s, a decade sooner than the general population in the west. Poor outcomes result from lung cancer being discovered between stages 3 and 4 in 75% of cases. High death rates and low survival rates are observed in lung cancer in India.

[0005] The invention aims to detect Lung cancer at early stage to prevent human lives. The instrument being portable and non-invasive can be used for mass screening. Most of the detection techniques (non-invasive) available are heavy machines, expensive, time consuming, and other invasive techniques are very painful and expensive too.

[0006] In recent years, medical research has identified volatile organic compounds (VOCs) in exhaled breath as potential biomarkers for a variety of diseases, including lung cancer. These VOCs result from metabolic changes in cells and tissues, which can differ in healthy individuals compared to those with disease. The ability to non-invasively detect such biomarkers holds promise for shifting the paradigm of disease detection towards earlier, more accurate diagnostics. However, current methods to detect these biomarkers, such as gas chromatography and mass spectrometry, while sensitive, are impractical for widespread clinical use due to their high cost, complexity, andLR-AAR-2918 time-consuming nature. Additionally, electrochemical sensors and other simpler technologies have faced limitations in sensitivity, especially when dealing with the very low concentrations of VOCs (in parts per billion) necessary for early-stage detection of diseases like lung cancer.

[0007] Photoacoustic spectroscopy has emerged as a promising solution to these limitations. This technique involves the absorption of laser light by a sample, which then converts the light energy into sound waves through the photoacoustic effect. Lung cancer is a significant global health challenge, with millions of lives lost each year due to the late-stage diagnosis of the disease. The majority of lung cancer cases are diagnosed when treatment options are limited, and the prognosis is poor. This late detection occurs because traditional diagnostic methods, such as CT scans and biopsies, are typically only administered once symptoms become apparent. By that point, the disease is often in advanced stages, reducing the patient’s chance of survival. The reliance on invasive, costly, and infrastructure-dependent tools has limited the ability of healthcare systems to provide timely, widespread screening for at-risk populations.

[0008] In recent years, medical research has identified volatile organic compounds (VOCs) in exhaled breath as potential biomarkers for a variety of diseases, including lung cancer. These VOCs result from metabolic changes in cells and tissues, which can differ in healthy individuals compared to those with disease. The ability to non-invasively detect such biomarkers holds promise for shifting the paradigm of disease detection towards earlier, more accurate diagnostics. However, current methods to detect these biomarkers, such as gas chromatography and mass spectrometry, while sensitive, are impractical for widespread clinical use due to their high cost, complexity, and time-consuming nature. Additionally, electrochemical sensors and other simpler technologies have faced limitations in sensitivity, especially when dealing with the very low concentrations of VOCs (in parts per billion) necessary for early-stage detection of diseases like lung cancer. There exists aLR-AAR-2918 potential for development into portable devices for use in clinical settings or even at home. The strength of the generated sound waves correlates with the concentration of target molecules within the sample, enabling the detection of specific VOCs in human breath. Unlike traditional optical methods, which measure reflected or transmitted light, photoacoustic spectroscopy directly measures absorbed energy as sound, offering a higher level of sensitivity and specificity.[00091 Detecting Biomarkar at ppbIn order to set the minimum detection limit, various factures are involved. The narrow bandwidth of laser source, the optical power beam size, proper locking of modulated signal frequency, Digital signal processing are some major design components to understand and implement. Since most of the VOCs exist at ppb level in exhale breath, it becomes most important to achieve this milestone. Simultaneously make total system portable, rigid and reliable in harsh environments.

[0010] Despite the potential of this technology, existing systems that leverage photoacoustic spectroscopy are often bulky and confined to research laboratories. These systems are neither portable nor designed for real-time, point-of-care diagnostics, which limits their utility in routine clinical settings, especially in areas with limited healthcare infrastructure. The present invention seeks to overcome these challenges by introducing a portable, non-invasive breath analyzer based on advanced photoacoustic spectroscopy. The device is designed for the early detection of lung cancer by analyzing trace amounts of VOCs in a patient’s breath. Utilizing multi-wavelength laser sources, the system is capable of detecting multiple biomarkers simultaneously, significantly improving the accuracy and reliability of the diagnostic process. Additionally, this invention integrates advanced loT (Internet of Things) connectivity coupled with Al / ML technology, allowing forLR-AAR-2918 the continuous monitoring and analysis of patient data in real-time, which is essential for early intervention and disease management.

[0011] The key advantage of this invention lies in its ability to offer a cost-effective, scalable, and accurate solution for lung cancer screening. The portability and simplicity of the device allow it to be used in a wide range of healthcare environments, including rural areas where access to sophisticated medical infrastructure is limited. This invention opens new possibilities for widespread, routine screening and monitoring, ultimately reducing the mortality associated with lung cancer by enabling earlier detection and treatment just like ATM for payment available all the time access to citizen

[0012] In the prior art a Russian Patent specification RU2772953C1 discloses a method for rapid diagnosis of acute myocardial infarction. The method based on the registration of volatile molecular markers in exhaled air is proposed, including sampling of the patient’s exhaled air and its spectral analysis, in which concentrations of a set of volatile molecular markers are measured, including at least nitric oxide (N2O), nitrogen dioxide (NO2), ethylene (C2H4), pentane (C5H12), carbon monoxide (CO), carbon dioxide (CO2), and an assessment of the compliance of the totality of measured concentrations with the presence or absence of acute myocardial infarction. The assessment of compliance with the probability of the presence or absence of acute myocardial infarction is carried out using a machine learning method trained using the values of concentrations of volatile molecular markers previously recorded in exhaled air samples of patients with clinically confirmed acute myocardial infraction and healthy volunteers, as well as using the support vector method trained using the values of concentrations of volatile molecular markers, previously registered in exhaled air samples of patients with clinically confirmed AMI and healthy volunteers. EFFECT: invention provides an increase in the accuracy of diagnosis of acute myocardial infarction based on spectral analysis of exhaled air samples.LR-AAR-2918

[0013] In another prior art an US Patent specification US2013011872A1 discloses a method of detecting the presence of cancer cells in an animal such as a human or other mammal, comprising administering a measured volume of air to the subject wherein I6O2 and I8O2 are present and then measuring the 8180 in the subject's exhaled CO2. A Photoacoustic Spectrometer system is used for measuring the amount of laser light (Infrared) absorbed by isotopes of CO2(CieO2, C18O2) in the exhalant.

[0014] In another prior art an US Patent specification US2012183949A1 discloses method, device, or system using lung sensor for detecting a physiological condition in a vertebrate subject Devices, systems, and methods are disclosed herein for detecting one or more physiological conditions in lungs of a vertebrate subject. A method is described for administering at least one microparticle to lungs of a vertebrate subject, wherein the at least one microparticle includes one or more markers; wherein the one or more markers is configured to be released in response to one or more physiological conditions in the vertebrate subject; and detecting the one or more markers in a lung exhalant of the vertebrate subject.

[0015] In another prior art an European Patent specification EP1853163B1 discloses breath test method for total organic carbon. The total amount of volatile organic compounds (VOCs) in a breath sample is detected by oxidizing / burning the VOCs to form CO2 and H2O, and the amounts of one or both of these compounds are measured. CO2 and H2O molecules in the breath sample are removed before the VOCs are converted to CO2 and H2O. Because one VOC molecule contains multiple carbon and hydrogen atoms, the number of formed CO2 and H2O molecules will be substantially larger than the original number of VOC molecules, thereby improving the sensitivity of the detection.LR-AAR-2918

[0016] This invention seeks to overcome these challenges by introducing a portable, non-invasive breath analyzer based on advanced photoacoustic spectroscopy. The device is designed for the early detection of lung cancer by analyzing trace amounts of VOCs in a patient’s breath. Utilizing multiwavelength laser sources, the system is capable of detecting multiple biomarkers simultaneously, significantly improving the accuracy and reliability of the diagnostic process. Additionally, this invention integrates advanced loT (Internet of Things) connectivity coupled with Al / ML technology, allowing for the continuous monitoring and analysis of patient data in real-time, which is essential for early intervention and disease management.

[0017] The key advantage of this invention lies in its ability to offer a cost-effective, scalable, and accurate solution for lung cancer screening. The portability and simplicity of the device allow it to be used in a wide range of healthcare environments, including rural areas where access to sophisticated medical infrastructure is limited. This invention opens new possibilities for widespread, routine screening and monitoring, ultimately reducing the mortality associated with lung cancer by enabling earlier detection and treatment just like ATM for payment available all the time access to citizen at large.SUMMARY OF INVENTION

[0018] The primary object of the invention is to provide a non-invasive, realtime diagnostic device based on photoacoustic technology that enables the early detection of lung cancer and other respiratory diseases by analyzing volatile organic compounds (VOCs) in exhaled breath. The invention aims to overcome the limitations of existing diagnostic methods, which are invasive, costly, and not scalable for widespread use.

[0019] First Objective:

[0020] To develop a compact, portable breath analyzer that utilizes multiwavelength photoacoustic spectroscopy for the detection of trace levels ofLR-AAR-2918 VOCs. This ensures the device is sensitive enough to detect parts-per-billion (ppb) concentrations of biomarkers linked to early-stage lung cancer and other diseases.

[0021] Second Objective:

[0022] To integrate the device with loT (Internet of Things) and Al / ML technology, enabling continuous data transmission, real-time analysis, and remote monitoring. This allows healthcare providers to track patients’ diagnostic data over time, offering personalized health insights and supporting the early detection of disease progression.

[0023] Third Objective:

[0024] To make the breath analyzer cost-effective and scalable, ensuring that it can be deployed across a wide range of healthcare settings, including rural areas and low-resource environments where access to advanced medical equipment is limited. By reducing the complexity of diagnostic processes, the invention aims to democratize healthcare and provide more equitable access to life-saving technologies.

[0025] Fourth Objective:

[0026] To enhance accuracy and specificity by utilizing multi -wave length laser sources that can detect and differentiate between multiple VOC biomarkers simultaneously. This minimizes false positives and ensures a high degree of reliability in diagnosing early-stage lung cancer and other related diseases.

[0027] Fifth Objective:

[0028] To develop a device that is not only for lung cancer but adaptable to detect other diseases where VOCs serve as biomarkers. This ensures the breath analyzer can be expanded for diagnosing conditions such as chronic obstructive pulmonary disease (COPD), asthma, and other respiratory and systemic diseases, making it a versatile tool for healthcare diagnostics.

[0029] With this non-invasive technique by taking exhale from subject can be analyzed with bio-marker of Volatile Organic Compound (VOC) responsible forLR-AAR-2918 Respiratory related decease. A library created for the combination of trace VOCs can indicate the possibility of Lung cancer.

[0030] Breath Analyzer System Components

[0031] 1. Multi-Wavelength Laser SourceThe system employs quantum cascade lasers (QCLs) operating in the mid infrared region (4-12 pm), the molecular fingerprint region for VOCs. Key features include:• Room-temperature operation.• Broad tunability and spectral purity for high selectivity.1. Photoacoustic Detection ChamberThe detection chamber is gas-tight and designed to optimize laser absorption by specific VOCs in exhaled breath. It includes:• A MEMS cantilever system with gold-coated cavities.• A disposable mouthpiece for sample collection.• A CO2 sensor for initial patient health analysis.• Moisture traps to ensure sample integrity.2. Acoustic SensorsHighly sensitive microphone sensors detect acoustic waves generated by VOC absorption. The sensors are capable of capturing signals in the ppb range, ensuring reliable biomarker detection.3. Signal Processing and Data Analysis UnitThe system features onboard signal processing, including:• Lock-in amplifiers and noise filtering algorithms.• Al / ML models for biomarker classification and disease prediction.• Real-time analysis with cloud-based integration for dataset enrichment.4. loT Integration

[0032] The loT module facilitates:• Remote monitoring and patient data management.LR-AAR-2918 • Aggregation of datasets from multiple devices for Al / ML training.• Real-time notifications for healthcare providers.

[0033] The invention provides a portable breath analyzer system utilizing photoacoustic spectroscopy for non-invasive detection of cancer biomarkers. The system features multi-wavelength quantum cascade lasers, Al / ML algorithms for enhanced data analysis, and loT integration for real-time monitoring. Designed for early-stage cancer detection, the device offers high sensitivity and specificity, enabling rapid, accurate diagnostics in clinical and remote healthcare environments.

[0034] Therefore such as herein described the disclosed device incorporates advancements in multi-wavelength laser tuning, optimized for high sensitivity and specificity in identifying disease markers at parts -per-billion (ppb) concentrations. Additionally, the invention contributes to the field of point-of-care diagnostics, where portable, cost-effective, and rapid screening tools are essential for timely medical interventions in both clinical and remote healthcare settings. This breath analyzer also advances the state of the art by integrating loT-based Al / ML data management systems for continuous health monitoring, thus contributing to precision medicine and personalized healthcareBRIEF DESCRIPTION OF ACCOMPANYING DRAWINGS

[0035] Figure 1 illustrates the overall construction of the breath analyzer system in accordance with the present invention;Figure 2 illustrates molecular absorption peaks of various gases & VOCs in accordance with the present invention;Figure 3 illustrates molecular absorption peaks of VOCs found in human breath in accordance with the present invention;LR-AAR-2918 Figure 4 illustrates sensor system flow with details of all blocks in accordance with the present invention;Figure 5 illustrates individual block details of Breath Analyzer in accordance with the present invention;Figure 6 illustrates software control of QC Laser performed at Lab in accordance with the present invention;Figure 7 illustrates spectrum analysis of QC Laser at 5.2 micron for NO detection characterized at Lab in accordance with the present invention;Figure 8 illustrates tuning characteristics of Pranalytica QCL in accordance with the present invention;Figure 9 illustrates optimization of chopping frequency for maximum detection at acoustic detector in accordance with the present invention;Figure 10 illustrates photoacoustic signal analysis after introducing calibrated NO gas in the gas cell in accordance with the present inventionFigure 11 illustrates GUI developed for vacuum control unit in LabView in accordance with the present invention;Figure 12 illustrates GUI developed for gas exchange for breath inhale in accordance with the present invention;DETAILED DESCRIPTION

[0036] The present invention pertains to the domain of advanced medical diagnostics and applied photonics, with particular emphasis on photoacoustic spectroscopy for detecting volatile organic compounds (VOCs) in exhaled breath. This technology leverages the interaction of laser-induced acoustic waves with specific gas-phase biomarkers, enabling precise, non-invasive diagnostics. The invention combines the technology improvements in existing Photoacoustic technique for the use of portable instrument. The external modulation of Laser through electronics chopping, multiple source integrations, Multiple library creations, real time detection and analysis. The invention is specifically designed to facilitate early detection of diseases,LR-AAR-2918 particularly lung cancer, by analyzing trace molecular signatures in real-time. The invention also simplifies ease of operation and scope for scaling up in future. This system integrates advancements in photoacoustic spectroscopy, multi-wavelength laser sources, and loT-based data analysis to create a portable, real-time diagnostic tool with high sensitivity and specificity

[0037] Photoacoustic spectroscopy (PAS) is a technique that has shown promise in various applications, including medical diagnostics. When applied to breath analyzers for cancer detection, PAS leverages the principles of photoacoustic effect to identify and quantify biomarkers associated with cancer.I. Laser Induced acoustic waves• The generation of acoustic wave is achieved through heat energy, which is created by the absorption of infrared light, generated by laser source. When the gas molecules absorb by laser heating it moves ahead and forms pressure waves, which converts into acoustic signals. Further, it moves towards detector.II. Bio marker for precise detection• There are many Bio markers, which indicates multiple organ disease indication in a single volatile compound (VOC); but creating a library for multiple VOC’s to indicate single disease is unique.III. External modulation of Laser through electronics chopping• In order to reduce background noise, it is necessary to modulate the laser source and lock in at the receiver’s side on 2X wavelength. Most of the photoacoustic spectroscopy utilizes mechanical chopping in white light source. Some also use a wavelength filter for wavelength specific absorption. This new invention integrates electronic modulation into the laser source by TTL logic. This requires a unique design of biasing theLR-AAR-2918 source without going into breakdown region. The electronic chopping is more useful in field environment particularly where vibration / acoustic disturbance, in comparison to mechanical chopping by blades. It degrades the performance in harsh environment.IV. Multiple source integrations• There are cases where different wavelengths correspond to molecular absorption do not fall into one tunable laser. In such case, integrating two or more laser sources in a single module fits the purpose of mapping different bio markers in a single sensor systemV. Multiple library creations• The scanning of tunable laser source creates a unique spectral graph which can be utilized to create a library for each one gas molecule. These can be created at the time of validating bio markers. This is a unique technique to analyze bio marker in real world scenario.

[0038] The device incorporates advancements in multi-wavelength laser tuning, optimized for high sensitivity and specificity in identifying disease markers at parts-per-billion (ppb) concentrations. Additionally, the invention contributes to the field of point-of-care diagnostics, where portable, cost-effective, and rapid screening tools are essential for timely medical interventions in both clinical and remote healthcare settings. This breath analyzer also advances the state of the art by integrating loT-based Al / ML data management systems for continuous health monitoring, thus contributing to precision medicine and personalized healthcare.*Light Absorption*: The breath sample is exposed to a modulated light source (usually a laser).*Thermoelastic Expansion*: Specific molecules in the sample absorb the light, causing localized heating and subsequent thermoelastic expansion.LR-AAR-2918 *Acoustic Wave Generation*: The rapid expansion generates acoustic waves (sound waves) which are detected by sensitive microphones or piezoelectric sensors.*Signal Analysis*: The acoustic signals are analyzed to identify the presence and concentration of specific biomarkers.

[0039] Photoacoustic breath analyzers offer a non-invasive alternative to traditional biopsy methods. It is capable of detecting minute concentrations of biomarkers, that means is Highly Sensitivity and can give rapid results by analysising quickly which is near real-time results.System Construction:

[0040] The invention consists of several key components, each contributing to the system's overall efficiency and effectiveness in detecting biomarkers. These components are designed to work together to ensure precise, non-invasive diagnosis through breath analysis.Photoacoustic Detection Chamber:

[0041] The core of the system is the photoacoustic detection chamber, where the exhaled breath sample is introduced. This chamber is specially designed to contain the breath sample and allow for the absorption of laser light by specific VOCs present in the breath.

[0042] The detection chamber is constructed with gas-tight materials to prevent leakage of the sample and to maintain the integrity of the analysis. The chamber is equipped with multiple inlets for the introduction of breath samples and sensors for detecting the acoustic waves generated by the photoacoustic effect.

[0043] The figure 1 depicts the overall construction of the breath analyzer, showing the main components such as the breath inlet, detection chamber,LR-AAR-2918 laser source, and the data processing unit. The Laser and detectors are important components as they decide the target trace gases / volatile compound to be detected. The subsystem including Photoacoustic cell are most important components as the real time sensing occurs as per Photoacoustic technology. The last subsystem includes the high-speed electronics and display with software control.

[0044] In figure - 1, the reference numeral (1) shows the main detection components. This consists of a MEMs cantilever, a gold coated cavity, a small laser for read out the signal. The reference numeral (2) shows a Tunable laser source in the Infrared region. The tuning is achieved using either by change in biasing or change in the temperature control. The laser operates at room temperature. The reference numeral (3) is the operable electronics circuits after the signals captured from detection module. The lock-in amplifications, signal conditioning and signal processing is done vide the said electronic circuits. Further the reference numeral (4) alongwith Fig 3 and illustrates the external arrangements of collecting human breath by using a disposable mouth piece. A CO2 sensor is required to get initial information of patient health. A moisture trap is required before sending the breath in the detection cell. Pure Nitrogen is also required every time patient completed the breath exhale process. Purging of gas cell required to eliminate any trace of Human breath before collecting for next patient. Finally, there reference numeral (5) gives the details of data collected and analyze for the prediction of any disease.Multi- Wavelength Laser Source:

[0045] The fig 2 shows the molecular absorption peaks of various gases & VOCs in the atmosphere whereas, fig 3 shows most of the molecular absorption peaks of VOCs presents the human exhale. As shown in Fig 2 or 3, the system utilizes a tunable, multi-wavelength laser source, which is critical for detecting multiple VOC biomarkers simultaneously. By adjusting the wavelength of theLR-AAR-2918 laser, the system is able to target specific molecular signatures within the exhaled breath sample.

[0046] The laser light is directed into the detection chamber, where it is absorbed by the target VOCs. This absorption generates acoustic waves, which are detected and processed by the system’s acoustic sensors. The use of multiwavelength lasers allows for a broader range of diseases to be detected, as different VOCs are associated with different health conditions.

[0047] Most important component of sensor system is shown in Fig 4. More particularly it addresses detailed explanations of each blocks involved in the Breath Analyzer system, the components involves in the system and corresponding components responsible to run the subsystem.Figure 5 shows each components involving the said system as an example with corresponding speculations, This gives an idea for system design in terms of power requirements and portability.A- QCL LaserInput - 12V, 60Watt, Diameter - 4mm, Peak Power - 715mW, Avg Power - 143mWB- Gas Exchange UnitInput - 12V, 60Watt, Controls the pneumatic valves and pump motor in the gas cell unitC- Gas# cell unit(consist of pneumatic gas flow valves and pump), Pump motor - 12V, 0.5A, flow rate - 5L / min (# Gas to be tested is Nitric Oxide)D- DSPInput - 12V, 60WattLR-AAR-2918 E- Display User Interface and system controls on a laptop, displays command and status.F- Chopper controllerInput - AC mains 220VM- AC / DC switching adapters 12V, 5 AQuantum Cascade Laser (QCL)

[0048] In recent years, the development of Quantum cascade lasers (QCLs) has paved the revolution in trace gas analysis as it can easily access the entire midinfrared (mid-IR) region, covering 4-12 micro-m. This is considered to be the molecular fingerprint region; hence the fundamental and combinational vibrational bands of important trace molecules can be probed with unprecedented molecular selectivity and sensitivity.

[0049] Moreover, other salient features of QCL such as room temperature operation, high optical output power, spectral purity, compactness, mode-hop-free (MHF) broad tunability (D100 cm-1) and extremely narrow linewidth (□0.0002 cm-1) make this laser source popular in the QCL-based absorption spectroscopy (QCLAS) for trace gas monitoring in real time. In this chapter, we will discuss about the operating principle of QCL and its applications in trace molecules detection in atmospheric research and human exhaled breath.Strengths of QC Laser SensorsSub-ppb Sensing Capabilities:

[0050] By using lasers which operate in the mid-IR, QC laser sensors can achieve sub-ppb sensitivity for a number of relevant gases. The Quantum Cascade Laser which tune around 5,2 pm is controlled with software. This is very much required to scan the laser smoothly for creating library to identify disease. As shown in Fig 6, the QC laser sensor is able to outperform FTIRs, NDIRs, electrochemical sensors and VCSELS in terms of sensitivity, and isLR-AAR-2918 closer to being on par with mass spectrometry. This means if QC laser sensors can be cheaper than mass spectrometry systems, they will possess a significant market advantage. The Spectrum analysis of QC Laser at 5.2 micron for NO detection characterized at Lab to find out the wavelength peak. This is to establish the lasing wavelength and power is shown in Fig 7.Compactness:

[0051] QC laser based sensors have the ability to be miniaturized in ways that mass spectrometers, NDIRs, tunable diode laser sensors, and FTIRs do not. The QC laser sensor consists of a laser, a detector, a power supply, a cooling system, a path for the laser to travel, and some sort of communication and processing hardware. While this may seem like a lot, all these components are very small or can be miniaturized in a way that a cell phone sized QC laser sensor is possible.

[0052] If we consider other technologies, FTIRs require a more complicated interferometer setup, mass spectrometers require many very complicated parts and will never be laptop sized, and NDIRs and tunable diode laser sensors cannot provide comparable sensitivity at almost any size. Simply, no optical devices are able to be miniaturized in ways QC laser sensors can while achieving comparable sensitivity.Wide Tuning Range:

[0053] What distinguishes QC lasers from other mid-IR lasers (such as solid fixed wavelength lasers, which we do not discuss in this report) is their ability to tune, or to shift from one wavelength to another. Currently, external cavity QC lasers (or EC-QC lasers) that use mirrors to lock into specific wavelengths are able to scan across 300 wavenumbers. The ability to scan across many wavelengths gives QC lasers the ability to eliminate interference caused by other gases present in the sample, and in some cases measure for several gases using the same laser. For example, in the case of breath analysis, water vaporLR-AAR-2918 is a significant source of interference, as it has strong absorption lines across nearly the entire IR spectrum; thus, by tuning the laser in and out of the strongest absorption line for a gas like ammonia, the detector is also able to measure the levels of humidity allowing for more accurate readings of ammonia (by being able to accurately cancel the water vapor interference). Also, for single-gas spectroscopy or lasers operating in controlled environments, if QC lasers only need to scan across a few wavenumbers, they are able to do so electrically or thermally. The tuning and scanning QC laser characteristics and optimization of chopping frequency is exemplified in Fig 8 and 9 respectively. It was necessary to find out external modulation frequency to capture maximum Photoacoustic signal. The table shows in the figure 9 illustrate the optical power variation through gas cell at various stage with modulation frequency.

[0054] This image shows the scanning ability of an EC-QC Laser as indicated by the boxed area. This shows how it is able to hit several key wavelengths for multiple trace gasesImportance of trace gas sensing with the help of QCL

[0055] The trace gases are defined as the gases that exist in small concentrations in a gas mixture. Despite of their low concentration, its quantitative detection has immense importance in numerous fields such as in environmental sensing, trace amounts of explosive detection and non-invasive medical diagnostics by means of exhaled breath analysis.

[0056] The recent advancement of infrared laser absorption spectroscopy (LAS) has become the most promising tool for quantitative and selective gas detection with demonstrated detection sensitivities ranging from ppmv and ppbv, even pptv levels depending on the detection method employed. Moreover, the invention and advancement of QCL play a paramount roll in trace gas detection as it is capable of accessing entire mid-infrared molecular ‘finger-print’ region (3-15 pm) and this spectral region is considered to be the choice for high-sensitivity laser absorption spectroscopy. Since most of the important traceLR-AAR-2918 molecules, being a simple or moderately complex structure, have fundamental rovibrational transition frequencies lying in this spectral region.. Thus, the transition strengths are several orders of higher magnitude compared to near-IR region leading to high sensitivity measurement.

[0057] The simulated spectra from the HITRAN database for important trace molecules in the mid-IR electromagnetic region.Breath Research

[0058] The several studies based on exhaled breath and breath odour have been widely utilised to determine the well-being of a subject since the ancient Greeks. Rollo first reported in 1798 that the odour of decaying apple was related to those subjects suffering from Diabetes Mellitus. It was also reported that several diseases like kidney diseases, liver complications are related to ammonia smell and rotten egg odour respectively. However, in 1971, Pauling did the ground breaking discovery about the presence of hundreds of volatile organic compounds (VOCs) in human exhaled breath. The main gas matrix present in the exhaled air contains nitrogen, oxygen, carbon dioxide, argon and water vapour with high concentration. However, other trace gases like nitric oxide, ammonia, hydrogen, nitrous oxide, methane and hydrogen sulphide are also present in the exhaled breath. The main source of the molecules in exhaled air may be either endogenous or exogenous. Endogenous molecules, which are produced in response to the metabolic process in the human body, are transported through the blood stream and subsequently they are exhaled via an alveolar pulmonary membrane. The concentration of exhaled air trace molecules generally varies with patient’s diet, state of health and stress level. Therefore, exhaling excessive amount of some compounds might be the cause of some diseases. In this way, exhaled breath analysis has become one of most promising methodologies for clinical diagnostics for early detection of pathogenic changes at the molecular level. In below mentioned table, few non limiting bio-markers concerning particular diseases have been mentioned. The overview of biomarkers that are instrumental in the early detection of lungLR-AAR-2918 cancer. These biomarkers show significant changes even in the initial stages, providing an opportunity for timely diagnosis and intervention.

[0059] The recent advancement of QCL-based detection schemes become the most viable alternatives for exhaled breath analysis. The traditional gas analysis systems such as mass spectroscopy (MS), Proton transfer reaction-MS and gas chromatography impede the real-time online exhaled breath analysis due to their size, high cost for handling, complicated maintenance and complex sample pre-treatment process. Alternatively, other gas detection systems with a low cost, such as pellistors, semiconductor and electrochemical sensors do not provide the sensitivity and selectivity in comparison with QCL coupled gas detection tools. The important thing to be required during exhaled breath traceLR-AAR-2918 constituents detection by QCL is the selection of analyte -specific absorption line. The targeted absorption line should be chosen in such a way that other interfering matrix compounds, present in exhaled air with higher concentration, do not overlap with the selected absorption line. However, several researchers have employed the detection of isotope species in exhaled breath for clinical diagnostic purposes. For example, many 13C-labelled substrates are often utilized for the clinical diagnostic procedure during pharmacokinetics and other studies regarding the evaluation of specific enzyme activities. Table 2.4 demonstrates the few applications of QCL for breath bio markers detection.

[0060] The Figure 4 shows Sensor system flow with details of all blocks, illustrating how the system can target specific VOCs by adjusting the laser wavelength to match the absorption characteristics of different biomarkers. (Courtesy NATURE PHOTONICS DOI: 10. 1038 / NPHOTON.2012.143)Acoustic Sensors:

[0061] The system includes highly sensitive microphone sensors that capture the acoustic waves generated by the absorbed laser light. These sensors are optimized for detecting extremely low concentrations of VOCs, in the range of parts per billion (ppb) .

[0062] The sensors convert the acoustic signals into electrical signals, which are then processed by the system’s onboard analysis unit. The precision of these sensors ensures that even trace amounts of biomarkers can be detected, making the system suitable for early-stage disease detection.Signal Processing and Data Analysis Unit:

[0063] Once the acoustic signals are captured, they are processed by a built-in signal processing unit. This unit uses advanced algorithms to filter noise and isolate the specific acoustic signatures of the VOCs present in the sample.LR-AAR-2918

[0064] The processed signals are then analyzed using advanced machine learning models integrated into the system’s software, which compares the results against a database of known biomarkers for diseases such as lung cancer as shown in Fig 10. This analysis enables the system to provide a realtime diagnosis with high specificity. The Photoacoustic signal analysis after introducing calibrated NO gas in the gas cell. Further, 100 ppm Nitric oxide detection was performed as shown in figure 10.loT Integration and Remote Monitoring:

[0065] A key feature of the invention is its loT (Internet of Things) integration, which allows for continuous monitoring and data transmission to cloud-based servers. This feature enables healthcare providers to remotely monitor patient data and track changes in VOC levels over time.

[0066] The loT system also allows for the aggregation of data from multiple devices, facilitating large-scale health monitoring programs and enabling predictive analytics to identify trends in disease progression. The real-time transmission of data ensures that healthcare providers can intervene at the earliest possible stage. The graphical user interface (GUI) for vacuum control unit and for gas exchange for breath inhale is shown in Fig 11 and 12 respectively. In the gas cell it is required to control the gas flow for the calibration, A software in LAB View is developed to optimize the same. This helps in controlling gas flow of subject every time we require to use for Lung aligments, Figure 11 shows the picture of Graphical Users Interface (GUI) of the same. A similar GUI is also developed and implemented in Figure 12, for gas exchange.Working of the System:

[0067] The operation of the system can be described in several key steps:Breath Sample Collection:LR-AAR-2918

[0068] The patient exhales into a specially designed breath inlet, which directs the breath sample into the photoacoustic detection chamber. The system ensures that the sample remains uncontaminated and is immediately subjected to laser analysis. The breath sample is directed into the photoacoustic detection chamber via a CO2 sensor and moisture traps.Laser Excitation and Photoacoustic Effect:

[0069] Once the breath sample enters the detection chamber, the multiwavelength laser source is activated. The laser light is absorbed by the VOCs present in the breath at their molecular absorption peak, causing these molecules to generate acoustic waves through the photo-acoustic effect.The strength and frequency of these acoustic waves are directly proportional to the concentration of the VOCs being analyzed.• Acetone and benzene (lung cancer) .• Formaldehyde (breast cancer).• Ammonia (renal cancer).Acoustic Signal Detection and Processing:

[0070] The acoustic sensors capture the waves generated in the detection chamber and convert them into electrical signals. These signals undergo several layers of signal processing, where noise is filtered out, and the target frequencies associated with disease-specific VOCs are isolated. Al / ML algorithms classify the biomarkers based on their spectral signatures.

[0071] The processed data is then analyzed against a database of known biomarkers, allowing the system to detect the presence of specific diseases, such as lung cancer.Real-Time Diagnosis and Remote Monitoring:

[0072] Once the analysis is complete, the system provides a real-time diagnosis based on the presence and concentration of the VOCs. The system comparesLR-AAR-2918 the detected biomarkers with a pre-trained library to provide a real-time diagnosis and the results are displayed on an easy-to-read interface, allowing healthcare providers to make immediate decisions about further testing or treatment.

[0073] Simultaneously, the data is transmitted to a secure cloud server via the loT system, where it can be accessed by healthcare providers remotely for longterm monitoring and management of the patient’s health

[0074] The figure 3 provides an overview of the signal processing workflow, from acoustic signal capture to noise filtering, and the final analysis comparing the results to a database of known VOC biomarkers. In the above figure, the reference numeral (6) denotes the basing and modulation of Laser source. The reference numeral (7) are the main detection units, which comprises of Date acquisition, Signal conditioning and the reference numeral (8) is the display, which is generally a screen / projector or PC.EXAMPLES:Example 1 : Early Detection of Lung Cancer

[0075] A 55-year-old patient with a history of smoking exhaled into the device. The system identified elevated levels of acetone and benzene, with a 95% match to the lung cancer biomarker profile in the library. The Al model provided a preliminary diagnosis, prompting further clinical evaluation.Example 2: AI-Driven Dataset Expansion

[0076] Data from 1,000 patients was aggregated to train the ML model, resulting in improved diagnostic accuracy for breast cancer by identifying unique VOC patterns in formaldehyde concentrations.LR-AAR-2918 Example 3: Remote Monitoring

[0077] A patient undergoing chemotherapy for lung cancer used the device daily. Changes in VOC levels were tracked remotely via loT, enabling timely adjustments to the treatment plan.INVENTIVE STEP:

[0078] Breath analyzers using PAS can detect volatile organic compounds (VOCs) that are indicative of certain cancers. For example:*Lung Cancer*: Certain VOCs, such as alkanes and benzene derivatives, are elevated in the breath of lung cancer patients.*Breast Cancer*: Specific aldehydes and ketones can be indicative of breast cancer.ADVANTAGES OF THE INVENTION• Enhanced early detection of cancer through non-invasive methods.• Integration of Al / ML for dataset enrichment and improved diagnostic accuracy.• Real-time analysis and remote monitoring through loT.• High sensitivity and specificity for VOC detection using QCLs.• Portable and cost-effective design suitable for clinical and remote settings.

[0079] While the present invention has been described with reference to a specific preferred embodiment, it will be apparent that various modifications and changes could be made to this embodiment without departing from the scope of the invention as hereinafter claimed. The above-mentioned description is provided to serve the purpose of clarifying the aspects of the invention, and it will be apparent to one skilled in the art that they do not serve to limit the scope of the invention. All modifications and improvements have beenLR-AAR-2918 incorporated here in for the sake of conciseness and readability but are properly within the scope of the present invention.

Claims

LR-AAR-2918 CLAIMS:- 1. A breath analyzer system for detecting volatile organic compounds (VOCs) in exhaled breath, comprising:a photoacoustic detection chamber configured to receive exhaled breath and generate acoustic waves through interaction with a modulated laser source; a tunable multi-wavelength quantum cascade laser (QCL) capable of targeting specific VOCs by adjusting its wavelength;a plurality of Acoustic sensors configured to detect acoustic waves and convert them into corresponding electrical signals;a signal processing unit configured to filter noise, isolate target frequencies, and analyze signals using machine learning algorithms; andan loT-enabled interface for real-time data transmission and remote monitoring.

2. The breath analyzer system as claimed in claim 1, wherein the said detection chamber includes:a disposable mouthpiece configured for sample collection;a CO2 sensor for baseline health monitoring; anda moisture trap to remove water vapor.

3. The breath analyzer system as claimed in claim 1, wherein the said laser source is electronically modulated to reduce background noise.

4. The breath analyzer system as claimed in claim 1, wherein the said signal processing unit is integrated with a database of known biomarkers for real-time disease diagnosis.

5. The breath analyzer system as claimed in claim 1, wherein the said loT interface allows aggregation of data from multiple devices for predictive analytics.

6. The breath analyzer system as claimed in claim 1, further comprising nitrogen gas purging to eliminate residual samples between tests.

7. The breath analyzer system as claimed in claim 1, wherein the said acoustic sensors are optimized for detecting VOCs at parts-per-billion concentrations.

8. The breath analyzer system as claimed in claim 1, wherein the said laser source’s tuning range covers multiple VOCs associated with different diseases.

9. The breath analyzer system as claimed in claim 1, wherein the said detection components include a MEMs cantilever, a gold coated cavity, a small laser operable at room temperature for read out the signal; wherein said laser sourceLR- AAR- 29 18 is configured to be tunable in the Infrared region and thee tunability is achieved using either by change in biasing or change in the temperature control.

10. The breath analyzer system as claimed in claim 1, wherein the said electronics circuits after the signals being captured from detection module perform lock-in amplifications, signal conditioning and signal processing.

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