Identification Of Lesions Research Articles

BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy (BONBID-HIE): I. MRI and Lesion Labeling

Hypoxic ischemic encephalopathy (HIE) is a brain injury that occurs in 1 ~ 5/1000 term neonates. Accurate identification and segmentation of HIE-related lesions in neonatal brain magnetic resonance images (MRIs) is the first step toward identifying high-risk patients, understanding neurological symptoms, evaluating treatment effects, and predicting outcomes. We release the first public dataset containing neonatal brain diffusion MRI and expert annotation of lesions from 133 patients diagnosed with HIE. HIE-related lesions in brain MRI are often diffuse (i.e., multi-focal), and small (over half the patients in our data having lesions occupying <1% of the brain volume (including ventricles)). Segmentation for HIE MRI data is remarkably different from, and arguably more challenging than, other segmentation tasks such as brain tumors with focal and relatively large lesions. We hope that this dataset can help fuel the development of MRI lesion segmentation methods for HIE and small diffuse lesions in general.

Improved identification of multiple sclerosis brain lesions with three-dimensional double inversion recovery MRI

Background Multiple sclerosis (MS) is a chronic autoimmune disease that results in demyelination within the central nervous system, causing brain lesions and neurological dysfunction. Precise identification of these lesions is essential for proper diagnosis and management. Aim This study aims to assess the effectiveness of three-dimensional double inversion recovery (3D DIR) MRI in detecting MS brain lesions compared to two-dimensional fluid-attenuated inversion recovery (2D FLAIR) and T2-weighted imaging (T2WI). Patients and methods A cross-sectional study involving 49 MS patients (21 patients with clinically suspected MS, 28 patients with remitting relapsing MS). MRI scans were performed using a standardized protocol, including 3D DIR, 2D FLAIR, and T2WI sequences. Lesion detection rates and regional lesion visibility were analyzed and compared. Results 3D DIR MRI significantly improved lesion detection rates, identifying 19% more lesions than 2D FLAIR and 28% more than T2WI (P&lt;0.001 for both). Regionally, 3D DIR MRI showed superior detection in the periventricular (13%, 23% higher), deep white matter (8%, 14% higher), juxtacortical (10%, 27% higher), intracortical (71%, 91% higher), and infratentorial (27%, 10% higher) regions compared to 2D FLAIR and T2WI, respectively (P&lt;0.001 for all). Conclusion 3D DIR MRI is more effective in detecting MS brain lesions than 2D FLAIR and T2WI, suggesting its integration into routine MS imaging protocols for better diagnostic accuracy.

Visibility of mpMRI region of interest on ultrasound during cognitive fusion targeted biopsy predicts prostate cancer detection: a prospective single-center study.

The purpose of this study was to evaluate the nature of ultrasound characteristics during mpMRI/TRUS cognitive fusion targeted biopsy (cTB). From 2023 to 2024, data from 502 lesions in 426 men who underwent targeted combined systematic biopsy were analyzed. All lesions had a Prostate Imaging Reporting and Data System (PI-RADS) score of ≥ 3. The primary endpoint was the detection rate of prostate cancer (PCa) according to the PI-RADS score/ultrasound characteristics, categorized as benign or invisible (Bi), hypoechoic only (Ho), and hypoechoic with microcalcification (Hm), assessed through cross-stratification. The secondary endpoints included the distribution of ultrasound characteristics across PI-RADS scores, prostate zones, and histological types. Finally, associations between ultrasound characteristics and clinically significant PCa (csPCa) were assessed using multivariate logistic regression analysis (MVA). Among lesions, 233 (46%) were Bi, 210 (42%) Ho, and 59 (12%) Hm. First, Bi lesions had a 64% (103/161) non-cancer rate in PI-RADS 3, while Ho + Hm lesions showed the highest csPCa rate in PI-RADS 5 at 82% (102/124). Additionally, Ho + Hm lesions were predominantly observed in PI-RADS 5 (92% [114/124]) and in the peripheral zone (64% [179/278]). Notably, Hm lesions had a significantly higher percentage of cribriform morphology than Ho lesions (32% vs. 14%, P = 0.001). Finally, MVA confirmed Ho ([Ref Bi] OR 4.95, P < 0.001) and Hm ([Ref Bi] OR 27.7, P < 0.001) as independent predictors of csPCa. In cTB, the identification of Ho and Hm lesions on TRUS enhances the diagnostic yield of csPCa by facilitating more precise localization compared to Bi lesions. No. 2023-272-002, July 14, 2023.

Quantitative Structural Analysis of Hyperchromatic Crowded Cell Groups in Cervical Cytology: Overcoming Diagnostic Pitfalls.

The diagnostic challenges presented by hyperchromatic crowded cell groups (HCGs) in cervical cytology often result in either overdiagnosis or underdiagnosis due to their densely packed, three-dimensional structures. The objective of this study is to characterize the structural differences among HSIL-HCGs, AGC-HCGs, and NILM-HCGs using quantitative texture analysis metrics, with the aim of facilitating the differentiation of benign from malignant cases. A total of 585 HCGs images were analyzed, with assessments conducted on 8-bit gray-scale value, thickness, skewness, and kurtosis across various groups. HSIL-HCGs are distinctly classified based on 8-bit gray-scale value. Significant statistical differences were observed in all groups, with HSIL-HCGs exhibiting higher cellular density and cluster thickness compared to NILM and AGC groups. In the AGC group, HCGs shows statistically significant differences in 8-bit gray-scale value compared to NILM-HCGs, but the classification performance by 8-bit gray-scale value is not high because the cell density and thickness are almost similar. These variations reflect the characteristic cellular structures unique to each group and substantiate the potential of 8-bit gray-scale value as an objective diagnostic indicator, especially for HSIL-HCGs. Our findings indicate that the integration of gray-scale-based texture analysis has the potential to improve diagnostic accuracy in cervical cytology and break through current diagnostic limitations in the identification of high-risk lesions.

Comparison of radiation exposure from dual- and single-energy CT imaging protocols resulting in equivalent contrast-to-noise ratio of lesions for adults and children: a phantom study.

To compare the radiation exposure from single-energy CT (SECT) against rapid kV-switching dual-energy CT (DECT) imaging in both adults and children when resulting image data offer equivalent lesion identification power. Lesions in an adult and a 10-year-old-child body phantom were imitated using iodine solutions of different concentrations. Phantoms were subjected to several SECT and DECT thoracic and abdominal scans using a rapid kV-switching DECT scanner. The contrast-to-noise ratio (CNR) of each lesion was measured on resulting SECT images and virtual monoenergetic images (VMI) available from DECT. The SECT scans that resulted in CNR values similar to the maximum CNR observed in VMIs derived from corresponding DECT scans were identified. SECT and DECT scans with equivalent lesion-discriminating power were compared regarding the associated radiation dose burden. Doses to the lung, breast, and esophagus from thoracic imaging and doses to the liver, kidneys, and stomach from abdominal imaging were determined through Monte Carlo simulations of SECT and DECT exposures. Compared to SECT imaging of the adult body phantom, organ doses from DECT were found to be 5-11% lower in thoracic imaging and 44-45% lower in abdominal imaging. Compared to SECT imaging of the 10-year-old body phantom, organ doses from DECT were found to be 2.8-3.4 times higher in thoracic imaging and 1.5-1.6 times higher in abdominal imaging. The use of rapid kV-switching DECT instead of SECT imaging may be associated with a similar or lower dose burden in adults but a noticeably higher dose burden in children. Question How does the radiation exposure from single-energy and dual-energy CT imaging compare when both techniques provide equivalent lesion identification power? Findings Rapid kV-switching dual-energy CT compared to single-energy CT may result in a similar or lower radiation dose in adults, but higher radiation dose in children. Clinical relevance Rapid kV-switching dual-energy CT imaging in children should be preferred over single-energy CT imaging only in cases where the additional information provided is crucial for an effective diagnosis.

Mueller matrix polarimetry for quantitative evaluation of the Achilles tendon injury recovery

Achilles tendon injuries, as a widely existing disease, have attracted a lot of research interest. Mueller matrix polarimetry, as a novel label-free quantitative imaging method, has been widely used in various applications of lesion identification and pathological diagnosis. However, focusing on the recovery process of Achilles tendon injuries, current optical imaging methods have not yet achieved the label-free precise identification and quantitative evaluation. In this study, using Mueller matrix polarimetry, various Achilles tendon injury samples were characterized specifically, and the efficacy of different recovery schemes was evaluated accordingly. Experiments indicate that injured Achilles tendons show less phase retardance, larger diattenuation, and relatively disordered orientation. The combination of experiments with Monte Carlo simulation results illustrate the microscopic mechanism of the Achilles tendon recovery process from three aspects, that is, the increased fiber diameter, a more consistent fiber orientation, and greater birefringence induced by more collagen protein. Finally, based on the statistical distribution of polarization measurements, a polarization specific characterization parameter was extracted to construct a label-free image, which cannot only intuitively show the injury and recovery of Achilles tendon samples, but also give a quantitative evaluation of the treatment.Graphical

Compression optical coherence elastography as a new tool for non-invasive identification of precancerous lesions of the oral mucosa

Compression optical coherence elastography as a new tool for non-invasive identification of precancerous lesions of the oral mucosa

The Undetermined Significance of Screening for Monoclonal Gammopathy of Undetermined Significance

AbstractThe identification of premalignant lesions in solid tumors such as colorectal and cervical cancer has led to the development of highly effective population-wide screening programs for these malignancies. Although precursor clinical states are not well-established for most hematologic malignancies, multiple myeloma is a notable exception. Virtually all patients with multiple myeloma first develop monoclonal gammopathy of undetermined significance (MGUS), an asymptomatic but easily detectable condition. However, broad screening for MGUS has not been adopted primarily because there is no proven intervention to delay or prevent the progression of MGUS to multiple myeloma. Furthermore, the incidence of MGUS is poorly understood; a better understanding of its epidemiology will be critical in designing appropriate screening guidelines once an effective treatment has been developed. In the current issue of Cancer Epidemiology, Biomarkers &amp; Prevention, Ji and colleagues provide important epidemiologic insights on MGUS, including a critical discussion on how its incidence and preclinical duration vary by age and race, acknowledging that both MGUS and multiple myeloma are more common in Black than White populations.See related article by Ji et al., p. 1690

Superior lesion detection on 3D FSE T1WI with magnetization transfer and CHESS preparation pulses in children with focal epilepsy: Preliminary results.

In childhood drug-resistant focal epilepsy, the identification of a magnetic resonance imaging lesion significantly affects the management and prognosis, although it is often challenging. Herein we report the preliminary results of a modified MR sequence, in which both magnetization transfer and chemical shift selective preparation pulses are added to a 3D fast spin echo T1-weighted sequence to recognize focal cortical dysplasia. The scan time is short, and the images have expected uniform suppression of the background normal gray and white matter. We report four children with focal epilepsy, in whom the focal cortical and subcortical lesions are superiorly conspicuous on the aforementioned MR sequence compared to the high-resolution fluid-attenuated inversion recovery images obtained with typical epilepsy MR protocols.

Surgical Insight-guided Deep Learning for Colorectal Lesion Management.

Colonoscopy stands as a pivotal diagnostic tool in identifying gastrointestinal diseases, including potentially malignant tumors. The procedure, however, faces challenges in the precise identification of lesions during visual inspections. The recent strides in AI and machine learning technologies have opened avenues for enhanced medical imaging analysis, including in the field of colonoscopy. In this study, we developed and evaluated a deep learning (DL) model, ColoNet, for detecting lesions in colonoscopic images. We analyzed 1760 images from 306 patients who underwent colorectal surgery between 2009 and 2022, meeting specific inclusion criteria. These images were used to train and validate ColoNet, employing the YOLOv8 architecture and various data augmentation techniques. Deep learning metrics are assessed via YOLO architecture and trained model diagnostic accuracy was assessed via sensitivity, specifity, positive predictive value, and negative predictive value. Our results from the validation dataset revealed a precision of 0.79604, a recall of 0.78086, an mAP50 of 0.83243, and an mAP50-95 of 0.4439. In addition, on a separate real-time dataset of 91 images consisting both healthy and suspect lesions, ColoNet achieved a sensitivity of 70.73%, specificity of 92.00%, positive predictive value (PPV) of 87.88%, and negative predictive value (NPV) of 79.31%. The positive and negative likelihood ratios were 8.84 and 0.32, respectively, with an overall accuracy of 82.42%. In conclusion, our model has demonstrated promising results, indicating its potential as a valuable tool to assist surgeons during colonoscopy procedures. Its ability to detect suspicious lesions with potential malignancy offers a noteworthy advancement in the early diagnosis and management of colorectal cancers. Further multicentric, prospective research and validation are warranted to fully realize its clinical applicability and impact.

In Situ Light-Source Delivery During 5-Aminulevulinic Acid-Guided High-Grade Glioma Resection: Spatial, Functional and Oncological Informed Surgery.

5-aminulevulinic acid (5-ALA)-guided surgery for high-grade gliomas remains a challenge in neuro-oncological surgery. Inconsistent fluorescence visualisation, subjective quantification and false negatives due to blood, haemostatic agents or optical impediments from the external light source are some of the limitations of the present technology. The preliminary results from this single-centre retrospective study are presented from the first 35 patients operated upon with the novel Nico Myriad Spectra System©. The microdebrider (Myriad) with an additional in situ light system (Spectra) can alternately provide white and blue light (405 nm) to within 15 mm of the tissue surface to enhance the morphology of the anatomical structures and the fluorescence of the pathological tissues. A total of 35 patients were operated upon with this new technology. Eight patients (22.85%) underwent tubular retractor-assisted minimally invasive parafascicular surgery (tr-MIPS). The majority had high-grade gliomas (68.57%). Fluorescence was identified in 30 cases (85.71%), with residual fluorescence in 11 (36.66%). The main applications were better white-blue light alternation and visualisation during tr-MIPS, increase in the extent of resection at the border of the cavity, identification of satellite lesions in multifocal pathology, the differentiation between radionecrosis and tumour recurrence in redo surgery and the demarcation between normal ependyma versus pathological ependyma in tumours infiltrating the subventricular zone. This proof-of-concept study confirms that the novel in situ light-source delivery technology integrated with the usual intraoperative armamentarium provides a spatially, functionally and oncologically informed framework for glioblastoma surgery. It allows for the enhancement of the morphology of anatomical structures and the fluorescence of pathological tissues, increasing the extent of resection and, possibly, the prognosis for patients with high-grade gliomas.

Correlation of Prostate High-Resolution Micro-Ultrasound with Multiparametric Magnetic Resonance Imaging

ObjectiveTo assess the correlation between high-resolution micro-ultrasound (microUS) and multiparametric magnetic resonance imaging (MP-MRI) in clinically significant prostate cancer (csPCa) lesion identification. MethodsWe reviewed our prospectively maintained database of 267 consecutive patients who underwent MP-MRI and transperineal microUS-guided biopsy between February 2021 and April 2023. The Prostate Risk Identification using MicroUS (PRI-MUS) protocol was utilized to risk stratify prostate lesions, with PRI-MUS 3-5 defined as positive. MRI lesions were classified according to the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Clinicopathologic outcomes were analyzed. Spearman correlation testing was computed to assess the relationship between PRI-MUS and PI-RADS. ResultsA total of 161 patients met inclusion criteria. Mean ± standard deviation (SD) age was 65.6 ± 1.5 years and PSA was 7.6 ± 0.6 ng/mL. Ninety-two patients were found to have PIRADS 3-5 lesions. Spearman correlation analysis revealed a moderate positive correlation between PRI-MUS and PI-RADS (r = 0.40, P < 0.001). MicroUS-targeted cores detected higher grade disease than systematic and MRI-targeted cores in 8/161 (5.0%) patients. CsPCa would have been missed in 4/161 (2.5%) patients without microUS-targeted sampling. ConclusionsMicroUS/PRI-MUS demonstrates moderate positive correlation with MP-MRI/PI-RADS and offers improved csPCa detection compared to MRI-targeted biopsy alone. MicroUS may be useful in conjunction with MP-MRI or as an alternative imaging modality in MRI-ineligible patients.

Glutathione-activated near-infrared II fluorescent probe for lung metastatic diagnosis and intraoperative imaging of tumor

Accurate identification of intraoperative tumor lesions and effective treatment are crucial for improving surgical outcomes. Near-infrared (NIR) fluorescence imaging demonstrates advantages over traditional medical approaches in tumor interventions, garnering significant attention. However, clinically available imaging agents are generally limited by their "always on" characteristics, which can lead to non-specific imaging interference and "false-positive" results. In this context, we present a glutathione-activated NIR-II probe, LJ-GSH, designed for metastatic tumor imaging and specific imaging-guided tumor resection. LJ-GSH initially exhibits quenched fluorescence due to the weak electron-donating effect of the thiophenol moiety, which is recovered at 815/910 nm upon activation by the overexpressed levels of glutathione (GSH) in tumor cells and tissues, significantly enhancing the specificity of tumor imaging. This unique characteristic positions LJ-GSH as a reliable fluorescent sensor for monitoring GSH dynamics during physiological events. Notably, the probe's NIR-II emission feature markedly improves imaging contrast and resolution, facilitating real-time identification and imaging of lung metastatic lesions. With the aid of high-specific NIR-II imaging guidance, tumor tissues can be precisely resected, with the residual negative margin diameter reduced to approximately 0.2 mm. We envision that our tailored probe may offer an attractive option for clinical applications.

Multi-Marker Biosensor Integrated Explainable AI-Based Cancer Screening System

The Prostate Imaging Reporting and Data System (PI-RADS) score, which is widely used for prostate MRI screening, has established itself as a standard approach for detecting prostate cancer (PCa) due to its reliable diagnostic performance. However, PI-RADS 3 lesions present a significant clinical challenge, as the system delivers only 30 to 40% diagnostic accuracy and is frequently associated with a high rate of false positives. To tackle this issue, we introduce a prostate cancer screening system powered by explainable artificial intelligence (XAI), which incorporates a highly sensitive electrochemical biosensor based on a dual-gate field-effect transistor (DGFET). This innovative system is designed to improve the identification of ambiguous lesions by analyzing the electrochemical sensing profiles of three specific urinary exosomal biomarkers. By generating interpretable results, it allows clinicians to make more confident and evidence-based decisions. Our findings reveal that the XAI-powered PCa screening system achieves impressive diagnostic accuracy, with an area under the curve (AUC) of 0.93, as demonstrated using 102 blinded samples through a non-invasive process. Remarkably, in cases involving PI-RADS 3 lesions, the system more than doubled the diagnostic accuracy compared to traditional PI-RADS scoring methods. Furthermore, the system identified TMEM256 as a crucial biomarker in the accurate diagnosis of PI-RADS 3 lesions, offering clear insight into its decision-making rationale. This study underscores the promise of integrating XAI with electrochemical biosensing to aid healthcare professionals in delivering more informed and evidence-backed diagnoses for prostate cancer, particularly in complex cases.

EF-net: Accurate edge segmentation for segmenting COVID-19 lung infections from CT images

Despite advances in modern medicine including the use of computed tomography for detecting COVID-19, precise identification and segmentation of lesions remain a significant challenge owing to indistinct boundaries and low degrees of contrast between infected and healthy lung tissues. This study introduces a novel model called the edge-based dual-parallel attention (EDA)-guided feature-filtering network (EF-Net), specifically designed to accurately segment the edges of COVID-19 lesions. The proposed model comprises two modules: an EDA module and a feature-filtering module (FFM). EDA efficiently extracts structural and textural features from low-level features, enabling the precise identification of lesion boundaries. FFM receives semantically rich features from a deep-level encoder and integrates features with abundant texture and contour information obtained from the EDA module. After filtering through a gating mechanism of the FFM, the EDA features are fused with deep-level features, yielding features rich in both semantic and textural information. Experiments demonstrate that our model outperforms existing models including Inf_Net, GFNet, and BSNet considering various metrics, offering better and clearer segmentation results, particularly for segmenting lesion edges. Moreover, superior performance on the three datasets is achieved, with dice coefficients of 98.1, 97.3, and 72.1 %.

Deep learning for oncologic treatment outcomes and endpoints evaluation from CT scans in liver cancer

Accurate treatment response assessment using serial CT scans is essential in oncological clinical trials. However, oncologists’ assessment following the Response Evaluation Criteria in Solid Tumors (RECIST) guideline is subjective, time-consuming, and sometimes fallible. Advanced liver cancer often presents multifocal hepatic lesions on CT imaging, making accurate characterization more challenging than with other malignancies. In this work, we developed a tumor volume guided comprehensive objective response evaluation based on deep learning (RECORD) for liver cancer. RECORD performs liver tumor segmentation, followed by sum of the volume (SOV)-based treatment response classification and new lesion assessment. Then, it can provide treatment evaluations of response, stability, and progression, and calculates progression-free survival (PFS) and response time. The RECORD pipeline was developed with both CNN and ViT backbones. Its performance was evaluated in three longitudinal cohorts involving 60 multi-national centers, 206 patients, 891 CT scans, using internal five-fold cross-validation and external validations. RECORD with the most effective backbone achieved an average AUC-response of 0.981, AUC-stable of 0.929, and AUC-progression of 0.969 for SOV-based disease status classification, F1-score of 0.887 for new lesion identification, and accuracy of 0.889 for final treatment outcome assessments across all cohorts. RECORD’s PFS and response time predictions strongly correlated with clinician’s assessments (P < 0.001). Moreover, RECORD can better stratify high-risk versus low-risk patients for overall survival compared to the human-assessed RECIST results. In conclusion, RECORD demonstrates efficiency and objectivity in analyzing liver lesions for treatment response evaluation. Further research should extend the pipeline to other metastatic organ sites.

Artificial Intelligence for the Prenatal Ultrasound Diagnosis of Congenital Heart Disease: A Narrative Review

Objective: Congenital heart disease (CHD) is the most prevalent congenital anomaly, imposing a significant burden in morbidity and mortality. Recent advances in artificial intelligence (AI) have introduced numerous new tools to fetal cardiac ultrasound, including automated generation of fetal cardiac planes and identification of specific CHD diagnostic views. Mechanism: Through a narrative review of literature, we described AI technology on automated CHD detection, lesion identification, and associated challenges, such as training datasets and image segmentation. Findings in Brief: The search provided 28 eligible studies. Conclusions: Artificial intelligence seems to be a promising tool to help clinicians in daily clinical activity: it can automate the detection of standard cardiac planes and assist in identifying abnormalities. The main advantages that emerged from this review are related to the reduction of inter- and intra-operator variability, improvement of overall diagnostic performance and accuracy. However, nowadays, its integration into routine clinical practice gives rise to several issues.

A novel androgen-independent radiotracer with dual targeting of NTSR1 and PSMA for PET/CT imaging of prostate cancer

A substantial proportion of patients with prostate cancer (PCa) develop treatment resistance or mortality after androgen deprivation therapy (ADT). Current methods for identifying and locating recurrent lesions using prostate-specific membrane antigen (PSMA)-based positron emission tomography (PET) imaging, which relies on androgen levels, often result in diagnostic delays. Therefore, the development of an androgen-independent radiotracer is critical for the early identification of recurrent lesions. The neurotensin receptor 1 (NTSR1) is highly expressed in androgen-independent PCa lesions. Here, we synthesized a bispecific ligand targeting PSMA and NTSR1 by solid-phase peptide synthesis and formulated a68Ga-labeled bispecific radiotracer, ([68Ga]Ga-NT-PSMA). This radiotracer exhibited a high radiochemical yield (71.27 % ± 1.58 %) and demonstrated an affinity for NTSR1 (39.32 ± 2.98 nM) and PSMA (63.47 ± 5.14 nM) in vitro. Small animal PET imaging showed comparable uptake of [68Ga]Ga-NT-PSMA and the monomeric radiotracer [68Ga]Ga-DOTA-NT20.3 in mice bearing androgen-independent PC3 (3.64 ± 0.49 %ID/g vs. 5.60 ± 1.42 %ID/g, nonsignificant [ns]) and DU145 tumors (2.49 ± 0.20 %ID/g vs. 2.34 ± 0.18 %ID/g, ns) at 90 min post-injection. In androgen-dependent 22Rv1 xenografts, [68Ga]Ga-NT-PSMA uptake was lower (1.94 ± 0.29 %ID/g) than [68Ga]Ga-PSMA-11 (3.94 ± 0.26 %ID/g, P < 0.001). Nevertheless, [68Ga]Ga-NT-PSMA effectively imaged all three xenograft types with high contrast, an achievement not possible with monomeric radiotracers alone. These results indicate that imaging with [68Ga]Ga-NT-PSMA is independent of the androgen dependence of the model, highlighting its potential as a promising nuclear medicine diagnostic tool for the early identification and localization of castration-resistant PCa lesions.

Abstract 4135333: Peripheral Perfusion Index: Normative Values From Electronically Reported Critical Congenital Heart Disease Screenin

Background: Critical Congenital Heart Disease (CCHD) screening is performed in an effort to reduce morbidity and mortality associated with CCHD by facilitating early detection. This screening consists of pulse oximetry and is most effective at identification of cyanotic cardiac lesions, with less sensitivity for left sided obstructive lesions. Research: Question Peripheral perfusion index (PPI) is obtained from the plethysmographic signal of a pulse oximeter and represents the ratio of pulsatile to non-pulsatile blood flow. As such, it is a surrogate for peripheral perfusion at the site of measurement. PPI has been postulated to be an adjunctive screening method for low perfusion states in neonates, including left sided obstructive lesions. To date, reference ranges of PPI values in neonates have not been published in the United States. This project utilized electronically reported CCHD screening results to establish normative PPI data in healthy neonates. Methods: In Minnesota, CCHD screening results are electronically sent to the Minnesota Department of Health (MDH) and are cross referenced against the Minnesota Birth Information System, which tracks infants who are identified to have a congenital birth defect within the first year of life. These data were provided by the MDH for infants born in Minnesota from Jan 2017 through Dec 2022. Infants were included in the analysis if they did not have a known critical congenital heart defect, were born between 35 and 42 weeks gestation, and were 24-48 hours of life at time of screening. Results: PPI data from 11,179 cases were included in the analysis. Overall, there is a trend towards increasing PPI with gestational age. Pre-ductal PPI trended higher than post-ductal PPI. There was no difference between PPI in males and females. Conclusions: These data reflect trends identified in international data. This is the largest dataset to date of PPI in healthy neonates and the first in the United States. Future studies will compare neonates with left sided obstructive lesions against these normative data. If PPI is found to predict left sided obstructive lesions in neonates, there may be utility in use of PPI in CCHD screening to facilitate earlier detection of these lesions.

Utility of near-infrared fluorescent clip for the robot-assisted gastrectomy: Report of 2 cases (case series)

Introduction and importanceThe importance of preoperative tumor site marking has increased over the years, as the method of intraoperative primary lesion identification and determination of resection margins is one factor determining whether oncological safety and function-preserving gastrectomy are possible during surgery. We hypothesize that preoperative placement of the near-infrared fluorescent (NIRF) clip, ZEOCLIP FS, near the oral incision line of the gastric tumor will allow for Firefly recognition of the NIRF clip on da Vinci during surgery and easy determination of the tumor location and incision line. Hence, we report on two cases in which the procedure was performed. Case presentationCase 1: A 62-year-old woman was diagnosed with early gastric cancer of 35 mm in size located in the greater curvature of the gastric angle and underwent robot-assisted distal gastrectomy. NIRF clips were placed around the negative biopsy-confirmed area on the tumor's oral side by endoscopy on the day before surgery. The clips were identified intraoperatively in Firefly mode, and we performed gastrectomy without using an intraoperative endoscope. Case 2: A 60-year-old man was diagnosed with early gastric cancer 40 mm in size on the anterior wall of the gastric angle and underwent robot-assisted distal gastrectomy. Similarly, NIRF clips were placed around the site of negative biopsy confirmation the day before surgery. NIRF clips were identified, and we performed gastrectomy. Clinical discussionThe time taken to mark the gastric resection line after activating the Firefly imaging system was 120 and 154 s, respectively, and intraoperative endoscopy was not required. The advantage of our two-step method is that a surgeon can mark the clips the day before the surgery, even if they are not endoscopists. Increasing the recognition rate of fluorescent clips and preventing their remains are future issues. ConclusionBased on the results of the above two cases, ZEOCLIP FS is influential in determining the tumor's location and the resection line.