Early-stage Detection Research Articles

Abstract IA017: A liquid biopsy fingerprint of disease via nanoengineering

Abstract Serum biomarkers are often insufficiently sensitive or specific to facilitate cancer screening or diagnostic testing. In many cancers, including high-grade serous carcinoma (HGSC), biomarkers fail to detect early-stage cancer detection or to substantially impact mortality rates. We developed a perception-based sensing method that captures a biomarker-agnostic ‘disease fingerprint’ of HGSC using serum. Instead of measuring individual biomarkers, the method collects large data sets of molecular binding interactions to a diverse array of moderately-selective sensors, which were used to train machine learning algorithms. In an initial study using serum from 264 patients, we built a prediction model of nanosensor responses that reliably identified HGSC substantially better than CA125. We believe that the improvement of such a method, using larger nanosensor arrays, more sophisticated AI algorithms, and larger patient cohorts, could improve the detection of HGSC and facilitate biomarker discovery efforts. Citation Format: Daniel A. Heller, Mijin Kim, Lakshmi Ramanathan, Kara Long Roche. A liquid biopsy fingerprint of disease via nanoengineering [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr IA017.

Label-Free Optical Technologies to Enhance Noninvasive Endoscopic Imaging of Early-Stage Cancers.

White light endoscopic imaging allows for the examination of internal human organs and is essential in the detection and treatment of early-stage cancers. To facilitate diagnosis of precancerous changes and early-stage cancers, label-free optical technologies that provide enhanced malignancy-specific contrast and depth information have been extensively researched. The rapid development of technology in the past two decades has enabled integration of these optical technologies into clinical endoscopy. In recent years, the significant advantages of using these adjunct optical devices have been shown, suggesting readiness for clinical translation. In this review, we provide an overview of the working principles and miniaturization considerations and summarize the clinical and preclinical demonstrations of several such techniques for early-stage cancer detection. We also offer an outlook for the integration of multiple technologies and the use of computer-aided diagnosis in clinical endoscopy.

Frequency sweep study on the generation of dual-mode second harmonics (DMSH) on an isotropic nonlinear elastic cylindrical rod by T(0,1) mode

Nonlinear ultrasonic (NLU) guided wave (GW) measurements are more sensitive to microscale defects than linear measurements. This nonlinear phenomenon is helpful for early-stage damage detection in material for nondestructive evaluation (NDE) and structural health monitoring (SHM) applications. The amplitude of the higher harmonics generated in the material serves as the basis for the NLU measurement. Recent studies have reported the presence of dual-mode second harmonic (DMSH) on an isotropic nonlinear elastic plate and cylindrical structures. The fundamental non-dispersive mode shear horizontal SH0 and torsional T(0,1) modes can generate simultaneously propagating dual-mode second harmonic(DMSH) on plate and cylindrical guided media respectively. For the case of cylinders, at phase matching condition two dominant second harmonic fundamental longitudinal (l(0,1)) and orthogonal torsional (t(0,1)┴) mode are generated with significant amplitude. The particle vibration of the t(0,1)┴ mode was present in both orthogonal directions compared to conventional T(0,1) mode and hence called orthogonal torsional mode. The present work aims to study the behaviour of DMSH at different frequencies through a frequency sweep study on a weakly nonlinear elastic cylinder of circular cross-section via numerical simulations and validated experimentally for some selected cases. The wave propagation of the T(0,1) mode at several selected frequencies from 300 kHz to 2.2 MHz is chosen to explore the second harmonic mode for better understanding. At frequencies below 1.25 MHz, l(0,1) mode is faster than t(0,1)┴ mode; above 1.25 MHz, it was the other way around. The behaviour of harmonics was observed to be in accordance with the group and phase velocities at the corresponding frequencies in the dispersion curves. The evidence for the presence of DMSH was validated experimentally for some selected frequency cases at different propagation distances. The significance of DMSH is explored via numerical simulations and found that t(0,1)┴ mode is sensitive towards material degradation, while all other generated wave modes were not affected. Research shows that enough energy is available in the generated DMSH to be noticed experimentally and in numerical simulations. This improved understanding of the generation of DMSH across different frequencies would be helpful in new advanced NLU-based NDE and SHM applications.

Next-generation endoscopic probe for detection of esophageal dysplasia using combined OCT and angle-resolved low-coherence interferometry.

Angle-resolved low-coherence interferometry (a/LCI) is an optical technique that enables depth-specific measurements of nuclear morphology, with applications to detecting epithelial cancers in various organs. Previous a/LCI setups have been limited by costly fiber-optic components and large footprints. Here, we present a novel a/LCI instrument incorporating a channel for optical coherence tomography (OCT) to provide real-time image guidance. We showcase the system's capabilities by acquiring imaging data from in vivo Barrett's esophagus patients. The main innovation in this geometry lies in implementing a pathlength-matched single-mode fiber array, offering substantial cost savings while preserving signal fidelity. A further innovation is the introduction of a specialized side-viewing probe tailored for esophageal imaging, featuring miniature optics housed in a custom 3D-printed enclosure attached to the tip of the endoscope. The integration of OCT guidance enhances the precision of tissue targeting by providing real-time morphology imaging. This novel device represents a significant advancement in clinical translation of an enhanced screening approach for esophageal precancer, paving the way for more effective early-stage detection and intervention strategies.

QbD-driven development and characterization of superparamagnetic iron oxide nanoparticles (SPIONS) of a bone-targeting peptide for early detection of osteoporosis

Osteoporosis is a metabolic disorder that leads to deterioration of bones. The major challenges confronting osteoporosis therapy include early-stage detection and regular disease monitoring. The present studies employed D-aspartic acid octapeptide (-D-Asp-)8 as bone-targeting peptide for evaluating osteoporosis manifestation, and superparamagnetic iron oxide nanoparticles (SPIONs) as nanocarriers for MRI-aided diagnosis. Thermal decomposition technique was employed to synthesize SPIONs, followed by surface-functionalization with hydrophilic ligands. Failure mode effect analysis and factor screening studies were performed to identify concentrations of SPIONs and ligand as critical material attributes, and systematic optimization was subsequently conducted employing face-centered cubic design. The optimum formulation was delineated using desirability function, and design space demarcated with 178.70 nm as hydrodynamic particle size, –24.40 mV as zeta potential, and 99.89 % as hydrophilic iron content as critical quality attributes. XRD patterns ratified lattice structure and SQUID studies corroborated superparamagnetic properties of hydrophilic SPIONs. Bioconjugation of (-D-Asp-)8 with SPIONs (1:1) was confirmed using UV spectroscopy, FTIR and NMR studies. Cell line studies indicated successful targeting of SPIONs to MG-63 human osteoblasts, ratifying enormous bone-targeting and safety potential of peptide-tethered SPIONs as MRI probes. In vivo MRI imaging studies in rats showcased promising contrast ability and safety of peptide-conjugated SPIONs.

Association between surgical quality and long-term survival in lung cancer

ObjectivesThere are significant variations in both perioperative and long-term outcomes after lung cancer resection. While perioperative outcomes are often used as comparative measures of quality, they are unreliable, and their association with long-term outcomes remain unclear. In this context, we evaluated whether historical perioperative mortality after lung cancer resection is associated with 5-year survival. Patients and MethodsThe National Cancer Database (NCDB) was queried to identify patients diagnosed with non-small cell lung cancer (NSCLC) in 2010–2016 who underwent surgical resection (n = 234200). Hospital-level reliability-adjusted 90-day mortality rate quartiles for 2010–2013 was used as the independent variable to analyze 5-year survival for patients diagnosed in 2014–2016 (n = 85396). ResultsThere were 85,396 patients in the 2014–2016 cohort across 1,086 hospitals. Overall observed 90-day mortality rate was 3.2% (SD 17.6%) with 2.6% (SD 16.0%) for the historically best performing quartile vs. 3.9% (SD 19.4%) for the worst performing quartile (p < 0.0001). Patients who underwent resection at hospitals with the best historical mortality rate had significantly better 5-year survival across all stages compared to those treated at hospitals in the worst performing quartile in multivariate Cox regression analysis (all stages – HR 1.21 [95% CI 1.15–1.26]; stage I – HR 1.19 [95% CI 1.12–1.25]; stage II – HR 1.20 [95% CI 1.09–1.32]; stage III – HR 1.36 [95% CI 1.20–1.54]) and Kaplan-Meier survival estimates (all stages – p < 0.0001, stage I – p < 0.0001; stage II – p = 0.0004; stage III – p < 0.0001). ConclusionWith expanded lung cancer screening criteria and likely increase in early-stage detection, profiling performance is paramount to ensuring mortality benefits. We found that episodes surrounding surgical resection may be used to profile long-term outcomes that likely reflect quality across a broader context of care. Evaluating lung cancer care quality using perioperative outcomes may be useful in profiling provider performance and guiding value-based payment policies.

Evaluation of the diagnostic assays detecting red sea bream iridovirus infection at different severity levels

Red sea bream iridovirus (RSIV) is a highly contagious viral infection that affects various fish species and poses a significant threat to the global aquaculture industry. Thus, accurate and timely diagnosis is paramount for sustainable management of fish health. This study rigorously evaluated the diagnostic efficacy of various polymerase chain reaction (PCR) assays, focusing on those recommended by the World Organization for Animal Health (WOAH) and the assays newly proposed by WOAH's Aquatic Animals Health Standards Commission. Specifically, this study assessed conventional PCR, nested PCR, modified 1-F/1-R, and real-time PCR assays using a 95% limit of detection (LoD95%), as well as diagnostic sensitivity (DSe) and specificity (DSp) tests across different RSIV severity grades (G0−G4). In previous studies, the LoD95% for the 1-F/1-R and 4-F/4-R conventional assays were 225.81 and 328.7 copies/reaction, respectively. The modified 1-F/1-R exhibited a lower LoD95% of 51.32 copies/reaction. Notably, the nested PCR had an LoD95% of 11.23 copies/reaction, and the real-time PCR assay had an LoD95% of 12.02 copies/reaction. The DSe varied across RSIV severity grades, especially in the lower G0−G2 grades. The nested PCR and modified 1-F/1-R assays displayed the highest DSe, making them particularly useful for early-stage screening and detection of asymptomatic carriers. In addition, the PCR assays did not cross-react with any other aquatic pathogens except RSIV. Our findings significantly advanced the diagnostic capabilities of RSIVD by suggesting that nested PCR and modified 1-F/1-R assays are particularly promising for early detection. We propose their inclusion in future WOAH guidelines for a more comprehensive diagnostic framework.

Molecularly Imprinted Polymers: Shaping the Future of Early-Stage Bone Loss Detection-A Review.

Osteoporosis is the deterioration of bone mineral density (BMD) because of an imbalance between bone resorption and formation, which might happen due to lots of factors like age, hormonal imbalance, and several others. While this occurrence is prevalent in both genders, it is more common in women, especially postmenopausal women. It is an asymptomatic disease that is underlying until the first incidence of a fracture. The bone is weakened, making it more susceptible to fracture. Even a low trauma can result in a fracture, making osteoporosis an even more alarming disease. These fractures can sometimes be fatal or can make the patient bedridden. Osteoporosis is an understudied disease, and there are certain limitations in diagnosing and early-stage detection of this condition. The standard method of dual X-ray absorptiometry can be used to some extent and can be detected in standard radiographs after the deterioration of a significant amount of bone mass. Clinically assessing osteoporosis using biomarkers can still be challenging, as clinical tests can be expensive and cannot be accessed by most of the general population. In addition, manufacturing antibodies specific to these biomarkers can be a challenging, time-consuming, and expensive method. As an alternative to these antibodies, molecularly imprinted polymers (MIPs) can be used in the detection of these biomarkers. This Review provides a comprehensive exploration of bone formation, resorption, and remodeling processes, linking them to the pathophysiology of osteoporosis. It details biomarker-based detection and diagnosis methods, with a focus on MIPs for sensing CTX-1, NTX-1, and other biomarkers. The discussion compares traditional clinical practices with MIP-based sensors, revealing comparable sensitivity with identified limitations. Additionally, the Review contrasts antibody-functionalized sensors with MIPs. Finally, our Review concludes by highlighting the potential of MIPs in future early-stage osteoporosis detection.

Digital mammogram based robust feature extraction and selection for effective breast cancer classification in earlier stage

Breast cancer poses a significant health risk for women, demanding early detection to mitigate its mortality impact. Leveraging the power of Deep Learning (DL) in medical imaging, this paper introduces a hybrid model that integrates YOLOv7 and Half UNet for feature extraction. YOLOv7 identifies and localizes potential cancerous regions, while Half UNet focuses on extracting pertinent features with its encoder-decoder structure. The fusion of these discriminative features, coupled with feature selection via Coati Optimization, ensures a comprehensive and optimized dataset. The selected features then feed into the CatBoost classification algorithm, refining parameters iteratively for precise predictions and minimizing the loss function. Evaluation metrics, including precision, recall, specificity, and accuracy, demonstrate the model’s superior performance. Notably, the proposed model surpasses existing methods in early-stage breast cancer detection. Beyond numerical metrics, its significance lies in the potential to positively impact patient outcomes and increase survival rates. By amalgamating cutting-edge DL techniques, the model excels in identifying intricate patterns crucial for early cancer detection. The efficient fusion of YOLOv7 and Half UNet, coupled with feature optimization through Coati Optimization, sets this model apart. This research contributes to the evolving landscape of medical imaging and DL applications, emphasizing the potential for enhanced breast cancer diagnosis and improved patient prognoses.

Breast cancer screening and early diagnosis in China: a systematic review and meta-analysis on 10.72 million women

BackgroundThe incidence of breast cancer among Chinese women has gradually increased in recent years. This study aims to analyze the situation of breast cancer screening programs in China and compare the cancer detection rates (CDRs), early-stage cancer detection rates (ECDRs), and the proportions of early-stage cancer among different programs.MethodsWe conducted a systematic review and meta-analysis of studies in multiple literature databases. Studies that were published between January 1, 2010 and June 30, 2023 were retrieved. A random effects model was employed to pool the single group rate, and subgroup analyses were carried out based on screening model, time, process, age, population, and follow-up method.ResultsA total of 35 studies, including 47 databases, satisfied the inclusion criteria. Compared with opportunistic screening, the CDR (1.32‰, 95% CI: 1.10‰–1.56‰) and the ECDR (0.82‰, 95% CI: 0.66‰–0.99‰) were lower for population screening, but the proportion of early-stage breast cancer (80.17%, 95% CI: 71.40%–87.83%) was higher. In subgroup analysis, the CDR of population screening was higher in the urban group (2.28‰, 95% CI: 1.70‰–2.94‰), in the breast ultrasonography (BUS) in parallel with mammography (MAM) group (3.29‰, 95% CI: 2.48‰–4.21‰), and in the second screening follow-up group (2.47‰, 95% CI: 1.64‰–3.47‰), and the proportion of early-stage breast cancer was 85.70% (95% CI: 68.73%–97.29%), 88.18% (95% CI: 84.53%–91.46%), and 90.05% (95% CI: 84.07%–94.95%), respectively.ConclusionThere were significant differences between opportunistic and population screening programs. The results of these population screening studies were influenced by the screening process, age, population, and follow-up method. In the future, China should carry out more high-quality and systematic population-based screening programs to improve screening coverage and service.

Abstract IA011: The epigenetic-based liquid biopsy odyssey of bedside pancreatic cancer diagnostics

Abstract Pancreatic cancer (PC), often diagnosed at an advanced stage, urgently requires innovative early detection methods to improve patient outcomes. Presently, there is no approved screening method for pancreas cancer and its high-risk individuals (HRIs), as existing techniques rely on costly and invasive imaging modalities, which face challenges in detecting interval cancers. This study presents an innovative approach that utilizes liquid biopsy technology combined with blood-based DNA methylation biomarkers—ADAMTS1, BNC1, and LRFN5. These biomarkers demonstrate a remarkable 94% diagnostic accuracy for early-stage PC detection, providing a transformative strategy in precision medicine. In line with precision medicine principles, the potential application of this liquid biopsy-based DNA methylation panel for monitoring HRIs offers a promising path toward personalized surveillance. The creation of an affordable bedside test with exceptional diagnostic accuracy has the potential to revolutionize early detection strategies for PCs. Identifying early curable stage PC through this liquid biopsy technique aligns perfectly with precision medicine, promising increased patient survival. If successfully integrated into routine healthcare, early detection could significantly advance the fight against pancreatic cancer, paving the way for more effective and patient-centric diagnostic approaches. Citation Format: Nita Ahuja. The epigenetic-based liquid biopsy odyssey of bedside pancreatic cancer diagnostics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA011.

An Expeditious Algorithm for Identification and Classification of Rotor Faults in Salient Pole Synchronous Generators

Providing secure electricity depends on the reliable operation of the synchronous generators in power plants. Inter-turn short circuit (ITSC) and dynamic eccentricity (DE) faults are among the most prevalent fault types in wound field synchronous generators (WFSGs). Among the various signals used to detect faults such as current, voltage, and vibration, the stray magnetic field provides higher sensitivity for early-stage ITSC and DE detection. The introduced detection methods rely on comparison of various signals frequency spectrum's from fault and healthy generators. However, obtaining a frequency spectrum of a healthy synchronous generator that has been operating for decades in a power plant is almost impossible. A unique pattern is introduced using fast Fourier transform that can be implemented on a low-end microcontroller and ideal for IoT solutions. The efficacy of the proposed pattern is examined by finite element modeling and validated on a 100 kVA WFSG setup in the laboratory and field test in a power plant with a power rating of 22 MVA.

A Systematic Review on: Polycystic Ovary Syndrome Using Machine Learning

Abstract: Polycystic Ovary Syndrome (PCOS) is a medical condition which causes hormonal disorder in women in their childbearing years. The hormonal imbalance leads to a delayed or even absent menstrual cycle. Women with PCOS majorly suffer from excessive weight gain, facial hair growth, acne, hair loss, skin darkening and irregular periods leading to infertility in rare cases. Early detection and diagnosis of PCOS are crucial for timely intervention and management. The existing methodologies and treatments are insufficient for early-stage detection and prediction. Machine learning can play a significant role in automating PCOS detection based on medical data and patient information. To deal with this problem, we propose a system which can help in early detection and prediction of PCOS treatment from an optimal and minimal set of parameters. In this study, we present an online application that enables women to conveniently estimate their likelihood of having the condition while remaining in the comfort of their own homes until assistance becomes accessible. Using feature selection approaches, we select only the non-invasive, readily measurable characteristics at home, resulting in a minimal but optimal set of clinical data for the same prediction. We employ the random-forest classifier, which has demonstrated encouraging outcomes when used in conjunction with machine learning techniques to diagnose PCOS. The Kaggle dataset, which consists of data points with clinical variables such as weight increase, LHS levels, hair loss, acne, BMI, and follicles in the left and right ovary, is used in this work.

Electrochemically Synthesized MIP Sensors: Applications in Healthcare Diagnostics.

Early-stage detection and diagnosis of diseases is essential to the prompt commencement of treatment regimens, curbing the spread of the disease, and improving human health. Thus, the accurate detection of disease biomarkers through the development of robust, sensitive, and selective diagnostic tools has remained cutting-edge scientific research for decades. Due to their merits of being selective, stable, simple, and having a low preparation cost, molecularly imprinted polymers (MIPs) are increasingly becoming artificial substitutes for natural receptors in the design of state-of-the-art sensing devices. While there are different MIP preparation approaches, electrochemical synthesis presents a unique and outstanding method for chemical sensing applications, allowing the direct formation of the polymer on the transducer as well as simplicity in tuning the film properties, thus accelerating the trend in the design of commercial MIP-based sensors. This review evaluates recent achievements in the applications of electrosynthesized MIP sensors for clinical analysis of disease biomarkers, identifying major trends and highlighting interesting perspectives on the realization of commercial MIP-endowed testing devices for rapid determination of prevailing diseases.

Use of micronuclei DNA from erythrocytes in early-stage colorectal cancer detection.

25 Background: Current development in stool- and cell-free DNA (cfDNA)-based technologies have demonstrated promising potentials in colorectal cancer (CRC) diagnosis. However, early detection of CRC and advanced adenoma (AA) remains challenging. Micronuclei (MN) are extranuclear bodies containing chromatin segments resulting from errors in DNA repair. Elevated levels of MN+ erythrocytes have been studied in genotoxicity testing and cancer diagnosis. We have developed a method (WO2021/228246 A1) for purifying and sequencing micronuclei DNA (mnDNA) in erythrocytes from peripheral blood. Here, we compared mnDNA between healthy donors (HDs) and CRC patients and explored its application for early cancer diagnosis. Methods: Peripheral blood (1ml) was obtained from a training cohort of 987 individuals, a validation cohort of 246, and an independent test cohort of 193. mnDNA was isolated and sequenced from erythrocytes. Genome-wide analysis identified distinctive mnDNA features between HD and CRC. Predictive models using these features were developed to differentiate CRC and AA from HDs. A clinical trial comparing mnDNA with an approved multitarget stool DNA test (sDNA-FIT) was also conducted on 60 individuals (42 HDs, 6 AAs, and 12 CRCs). Results: Genome-wide analysis of mnDNA revealed substantial differences in distribution patterns between HDs and CRC patients. The predictive model built on mnDNA features achieved an AUC of 92.98% (95%CI: 87.85-98.12%), with an 88.64% sensitivity and 92.75% specificity in the independent test cohort. The model identified early-stage (stage I-II) CRC and AA with sensitivities of 83.33% or 69.56%, respectively. Comparing mnDNA to sDNA-FIT showed superior overall sensitivity (83.33% vs. 61.11%), AA sensitivity (83.33% vs. 16.66%), with comparable specificity (85.71% vs. 88.10%). Conclusions: Our results demonstrate that mnDNA from a small amount of peripheral blood enable accurate detection of AA and early-stage CRC. As a type of cytoplasmic DNA, mnDNA can provide a valuable tool for early cancer detection, offering different underlying mechanisms compared to current methods. A larger clinical study (NCT05875584) is ongoing and will further validate the application of mnDNA in early cancer detection.

Detection of early-stage gastrointestinal cancers by micronuclei DNA from erythrocytes.

382 Background: Gastrointestinal (GI) cancers account for over a third of cancer deaths. However, their early detection remains a challenge. Micronuclei (MN) are extranuclear bodies containing damaged chromosome segments indicative of genomic instability. Increased MN frequency in hematopoietic cells is observed in patients with solid tumors. We have developed a method (WO2021/228246 A1) for purifying and characterizing micronuclei DNA (mnDNA) in erythrocytes from peripheral blood. Here, we evaluated the potential of mnDNA for early-stage GI cancer detection, including colorectal (CC) and gastric (GC) cancers. Methods: Peripheral blood (1 ml) was collected from healthy donors (HD) and cancer patients mnDNA isolation and purification from erythrocytes. Participants were randomly divided into training, validation and independent test cohorts in a 7:2:1 ratio, maintaining similar cancer types, CC/GC/HD ratio, gender and age distribution. Distinct mnDNA features between cancer patients and HDs were identified using sequencing data. Logistic regression algorithms were applied using these features for cancer detection. Results: The study enrolled 1046 participants, including 419 HDs, 366 CC and 261 GC cases. Of these, over half were diagnosed with early-stage diseases; TNM stage I accounted for 38.7%, stage II for 22.8%, stage III for 30.5% and stage IV for 8.0%. The cancer detection model with mnDNA features yielded an overall accuracy of 84.8%, with a sensitivity of 84.1% and specificity of 85.7%. For individual caner types, sensitivity was 89.2% for CC and 76.9% for GC. For early-stage (stage I-II) CC and GC, the model demonstrated sensitivities of 88.9% and 76.5%, respectively, at 85.7% specificity. Conclusions: Unlike cell-free DNA, mnDNA are chromosomal fragments in the cytoplasm. The abundance of erythrocytes in peripheral blood provides an easily accessible source for mnDNA enrichment. This pilot study illustrates the potential of mnDNA as a tool for early GI cancer detection, contributing to large-scale efforts towards developing an effective GI cancer screening test.

Voltage measurement-based recursive adaptive method for internal short circuit fault diagnosis in lithium-ion battery packs

Internal short circuit (ISC) has been identified as a major cause of thermal runaway in lithium-ion (Li-ion) battery systems, making the investigation of ISC fault diagnosis a focal research topic in electric vehicles and battery energy storage systems. Recently, several studies have applied multivariate analysis techniques to analyze abnormal behavior in cell voltage measurements and achieved an accurate diagnosis of ISC faults. However, model parameter variations under different operating conditions and state of charge (SOC), which results in unacceptable false alarm rates, is yet to be fully considered. To effectively address this problem, this study introduces a recursive approach on the basis of principal component analysis (PCA) to update the monitoring model and adapt to parameter changes. Moreover, an adaptive threshold with fusion factors is devised to reduce fault false alarm rates. In particular, this study employs sliding window techniques to amplify weak fault features to tackle the challenge of early-stage detection difficulty for ISC faults and provides an optimal window width determination algorithm based on fault-free data. Experimental results on a real Li-ion battery pack test platform under various operating conditions and SOC levels demonstrate that the proposed method maintains extremely high fault detection rates for ISC faults of different intensities. Furthermore, it is established that the adaptive updating of the model in the absence of faults greatly reduces false alarm rates.

Abstract A016: Novel positron emission tomography imaging targeting cell surface glycans for pancreatic cancer: 18F-labeled rBC2LCN lectin

Abstract Introduction: Advancement in early detection modalities will greatly improve the overall prognoses of pancreatic ductal adenocarcinoma (PDAC). As a molecular imaging technique, [18F]FDG-PET imaging has provided new insight in PDAC diagnosis; however, the utility of FDG for early-stage PDAC detection remains undefined. Therefore, PET radiotracers conjugated to malignancy-specific targeting agents (e.g., antibodies targeting cancer-associated/specific antigens) have been developed to improve specificity toward cancer cells but persist in the developmental stage. One underexplored cancer cell surface-specific target is the glycocalyx. We have previously demonstrated that fucosylated glycans (H type-3 antigens) are expressed in pancreatic cancers and a recombinant lectin, rBC2LCN, binds to these glycans specifically (Shimomura O et al: Mol Cancer Ther 2018). Here, we developed a novel, lectin-based PET probe targeting cell surface glycan for pancreatic cancer. Material and Methods: The rBC2LCN (16kDa) lectin was labeled with N-succinimidyl-4-[18F]fluorobenzoate ([18F]SFB), prepared according to literature (Maeding P, et al: Appl Radiat Isot 2005) in phosphate buffer (pH 8.5). Obtained [18F]FB-rBC2LCN was then purified using gel filtration column (PD-10, GE, Uppsala, Sweden). A PDAC cell line, Capan-1, was used as a model which expresses H type-3 antigens. The biodistribution of the [18F]FB-rBC2LCN was evaluated in athymic nude mice bearing subcutaneous Capan-1 tumors. Static, small-animal PET imaging studies (G4, SOFIE, Dulles, VA) were performed to further evaluate in vivo tumor targeting and specificity. Results: The decay-corrected radiochemical mean yield of [18F]FB-rBC2LCN was 3.6%±0.3% (mean±SD), based on [18F]SFB, and radiochemical purity was above 95%. Cell binding and uptake revealed that [18F]FB-rBC2LCN binds to Capan-1 cells. Mice received 0.32±0.16 MBq (corresponding to 59±21 mg) of product, injected intravenously. Biodistribution studies demonstrated that Capan-1 tumor uptake (6.5±2.0 %ID/g) was high as early as 60 min after injection of [18F]FB-rBC2LCN and the uptake increased over time (9.6±2.2 and 11±3.9 at 150 and 240 min after injection, respectively). Tumor-to-muscle ratio increased with time up to 19±1.8 at 360 min after injection, indicating image contrast. Although kidneys (72±23 %ID/g), liver (7.1±1.7 %ID/g) and lungs (7.4±2.9 %ID/g) showed high uptake at 60 min after injection, the uptake of those organs decreased over time. The blood activity concentration of the tracer was also high at 60 min after injection (12±4.4 %ID/g) and decreased over time. Bone uptake was very low (below 1.8 %ID/g throughout the study), indicating that defluorinating metabolism was negligible. High-contrast PET imaging of tumors was achieved as early as 60 min after injection and the contrast became clearer over 240 min, consistent with the biodistribution result. Conclusions: Our 18F-labeled rBC2LCN lectin warrants further clinical development to improve the accuracy and sensitivity of early-stage PDAC detection. Citation Format: Yukihito Kuroda, Tatsuya Oda, Osamu Shimomura, Bryan J. Mathis, Hiroaki Tateno, Kentaro Hatano. Novel positron emission tomography imaging targeting cell surface glycans for pancreatic cancer: 18F-labeled rBC2LCN lectin [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A016.

Diagnosis, treatment, and prognosis of stage IB non-small cell lung cancer with visceral pleural invasion.

With the increasing implementation of early lung cancer screening and the increasing emphasis on physical examinations, the early-stage lung cancer detection rate continues to rise. Visceral pleural invasion (VPI), which denotes the tumor's breach of the elastic layer or reaching the surface of the visceral pleura, stands as a pivotal factor that impacts the prognosis of patients with non-small cell lung cancer (NSCLC) and directly influences the pathological staging of early-stage cases. According to the latest 9th edition of the TNM staging system for NSCLC, even when the tumor diameter is less than 3 cm, the final T stage remains T2a if VPI is present. There is considerable controversy within the guidelines regarding treatment options for stage IB NSCLC, especially among patients exhibiting VPI. Moreover, the precise determination of VPI is important in guiding treatment selection and prognostic evaluation in individuals with NSCLC. This article aims to provide a comprehensive review of the current status and advancements in studies pertaining to stage IB NSCLC accompanied by VPI.

Analysis of polarization features of human breast cancer tissue by Mueller matrix visualization.

Breast cancer ranks second in the world in terms of the number of women diagnosed. Effective methods for its early-stage detection are critical for facilitating timely intervention and lowering the mortality rate. Polarimetry provides much useful information on the structural properties of breast cancer tissue samples and is a valuable diagnostic tool. The present study classifies human breast tissue samples as healthy or cancerous utilizing a surface-illuminated backscatter polarization imaging technique. The viability of the proposed approach is demonstrated using 95 breast tissue samples, including 35 healthy samples, 20 benign cancer samples, 20 grade-2 malignant samples, and 20 grade-3 malignant samples. The observation results reveal that element in the Mueller matrix of the healthy samples has a deeper color and greater intensity than that in the breast cancer samples. Conversely, element shows a lighter color and reduced intensity. Finally, element has a darker color in the healthy samples than in the cancer samples. The analysis of variance test results and frequency distribution histograms confirm that elements , , and provide an effective means of detecting and classifying human breast tissue samples. Overall, the results indicate that surface-illuminated backscatter polarization imaging has significant potential as an assistive tool for breast cancer diagnosis and classification.