Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is time-consuming and has high interoperator variability, underscoring the need for more efficient methods. After training, we compared 2 deep-learning-based 3D segmentation models, DeepMedic and nnU-Net, with pediatric-specific multi-institutional brain tumor data based on multiparametric MR images. MATERIALS AND METHODS: Multiparametric preoperative MR imaging scans of 339 pediatric patients (n = 293 internal and n = 46 external cohorts) with a variety of tumor subtypes were preprocessed and manually segmented into 4 tumor subregions, ie, enhancing tumor, nonenhancing tumor, cystic components, and peritumoral edema. After training, performances of the 2 models on internal and external test sets were evaluated with reference to ground truth manual segmentations. Additionally, concordance was assessed by comparing the volume of the subregions as a percentage of the whole tumor between model predictions and ground truth segmentations using the Pearson or Spearman correlation coefficients and the Bland-Altman method. RESULTS: The mean Dice score for nnU-Net internal test set was 0.9 (SD, 0.07) (median, 0.94) for whole tumor; 0.77 (SD, 0.29) for enhancing tumor; 0.66 (SD, 0.32) for nonenhancing tumor; 0.71 (SD, 0.33) for cystic components, and 0.71 (SD, 0.40) for peritumoral edema, respectively. For DeepMedic, the mean Dice scores were 0.82 (SD, 0.16) for whole tumor; 0.66 (SD, 0.32) for enhancing tumor; 0.48 (SD, 0.27) for nonenhancing tumor; 0.48 (SD, 0.36) for cystic components, and 0.19 (SD, 0.33) for peritumoral edema, respectively. Dice scores were significantly higher for nnU-Net (P ≤ .01). Correlation coefficients for tumor subregion percentage volumes were higher (0.98 versus 0.91 for enhancing tumor, 0.97 versus 0.75 for nonenhancing tumor, 0.98 versus 0.80 for cystic components, 0.95 versus 0.33 for peritumoral edema in the internal test set). Bland-Altman plots were better for nnU-Net compared with DeepMedic. External validation of the trained nnU-Net model on the multi-institutional Brain Tumor Segmentation Challenge in Pediatrics (BraTS-PEDs) 2023 data set revealed high generalization capability in the segmentation of whole tumor, tumor core (a combination of enhancing tumor, nonenhancing tumor, and cystic components), and enhancing tumor with mean Dice scores of 0.87 (SD, 0.13) (median, 0.91), 0.83 (SD, 0.18) (median, 0.89), and 0.48 (SD, 0.38) (median, 0.58), respectively. CONCLUSIONS: The pediatric-specific data-trained nnU-Net model is superior to DeepMedic for whole tumor and subregion segmentation of pediatric brain tumors.

Towards Consistency in Pediatric Brain Tumor Measurements: Challenges, Solutions, and the Role of AI-Based Segmentation.

MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tumor histologies; however, the visual delineation of tumor components using MRIs is not always straightforward, and complexities not currently addressed by these criteria can introduce inter- and intra-observer variability in manual assessments. Differentiation of non-enhancing tumor from peritumoral edema, mild enhancement from absence of enhancement, and various cystic components can be challenging; particularly given a lack of sufficient and uniform imaging protocols in clinical practice. Automated tumor segmentation with artificial intelligence (AI) may be able to provide more objective delineations, but rely on accurate and consistent training data created manually (ground truth). Herein, this paper reviews existing challenges and potential solutions to identifying and defining subregions of pediatric brain tumors (PBTs) that are not explicitly addressed by current guidelines. The goal is to assert the importance of defining and adopting criteria for addressing these challenges, as it will be critical to achieving standardized tumor measurements and reproducible response assessment in PBTs, ultimately leading to more precise outcome metrics and accurate comparisons among clinical studies.

" I'm not a risk taker " : Risk Perceptions of Nursing Home Residents With Dementia.

BACKGROUND: Persons living with Alzheimer disease and related dementia (ADRD) in nursing homes (NH) are often excluded from conversations about their health/safety. These omissions impinge on personhood and the rights to have care preferences heard and honored. While persons with ADRD maintain the ability to communicate their preferences long after their decision-making abilities are affected, little is known about how persons with ADRD understand the risks associated with their preferences. METHODS: As part of a larger focused ethnography, in-depth interviews and an adapted risk propensity questionnaire explored the risk perceptions of NH residents with ADRD (N=7) associated with their preferences for care and activities of daily living. RESULTS: Residents generally self-identified as risk avoiders ( M =3.2±1.84) on the risk propensity scale and were able to rate risk associated with preferences described within 5 thematic categories: 1) participation in decision-making, 2) risk awareness, 3) paying attention to safety, 4) reliance on nursing home staff and family, and 5) impacts on quality of life and quality of care. DISCUSSION: Results suggest NH residents with ADRD can express risk surrounding their preferences and should be encouraged to participate in discussions about their health and safety.

A Qualitative Study of Resident Advocacy Work.

BACKGROUND: Advocacy is a critical component of pediatric training and practice. Pediatric resident advocacy experiences include skill development and real-world projects, but little is known about how pediatric residents participate in advocacy. Without this knowledge, educators run the risk of underpreparing residents for the full scope of advocacy work. This study sought to investigate how residents participate in advocacy by characterizing their projects using an evidence-informed conceptual framework and describing the unique lessons were learned by the residents. METHODS: The authors used principles of thematic analysis to interrogate existing documents derived from pediatric residents from 2013 to 2021 at 1 institution. They purposefully sampled and deidentified project proposals and written reflections. Using a constant comparative method, they created codes. Codes, connections between codes, and findings were refined by discussion. RESULTS: Residents demonstrated 4 different types of advocacy: some residents participated in directed agency or activism and others focused on shared agency or activism. Residents reflected on different learning experiences; residents who participated in shared forms of advocacy learned skills such as "Partnering," "Evaluating," and "Planning." Residents who were involved in directed forms of advocacy shared lessons on "Leading," "Presenting," and "Intervening." Advocacy work also changed over time: in later projects (2016-2021) residents took ownership of the role of "advocate"; social and political climate was salient in reflections. CONCLUSIONS: Pediatric residents advocate through shared activism and agency and directed activism and agency. Educators should recognize, support, and supplement the experiences of residents as they participate in different types of advocacy.

Why Competency Frameworks Are Insufficiently Nuanced for Health Equity Teaching and Assessment.

This article suggests how competency-based medical education should robustly integrate health equity by focusing on physicians' responsibilities to (1) know why and how underlying structural mechanisms contribute to health equity and then (2) take action to achieve health equity in their practice. This article first canvasses currently available frameworks for helping trainees cultivate these 2 specific skills of discernment and action. This article then offers strategies for teaching and assessing these skills in specific learning activities.

Role of Low-Energy (<20 eV) Secondary Electrons in the Extraterrestrial Synthesis of Prebiotic Molecules.

We demonstrate for the first time that Galactic cosmic rays with energies as high as ∼1010 eV can trigger a cascade of low-energy (<20 eV) secondary electrons that could be a significant contributor to the interstellar synthesis of prebiotic molecules whose delivery by comets, meteorites, and interplanetary dust particles may have kick-started life on Earth. For the energetic processing of interstellar ice mantles inside dark, dense molecular clouds, we explore the relative importance of low-energy (<20 eV) secondary electrons-agents of radiation chemistry-and low-energy (<10 eV), nonionizing photons-instigators of photochemistry. Our calculations indicate fluxes of ∼102 electrons cm-2 s-1 for low-energy secondary electrons produced within interstellar ices due to attenuated Galactic cosmic-ray protons. Consequently, in certain star-forming regions where internal high-energy radiation sources produce ionization rates that are observed to be a thousand times greater than the typical interstellar Galactic ionization rate, the flux of low-energy secondary electrons should far exceed that of nonionizing photons. Because reaction cross sections can be several orders of magnitude larger for electrons than for photons, even in the absence of such enhancement, our calculations indicate that secondary low-energy (<20 eV) electrons are at least as significant as low-energy (<10 eV) nonionizing photons in the interstellar synthesis of prebiotic molecules. Most importantly, our results demonstrate the pressing need for explicitly incorporating low-energy electrons in current and future astrochemical simulations of cosmic ices. Such models are critically important for interpreting James Webb Space Telescope infrared measurements, which are currently being used to probe the origins of life by studying complex organic molecules found in ices near star-forming regions.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.

Inequity is woven into the fabric: a discourse analysis of assessment in pediatric residency training.

Intrinsic inequity in assessment refers to sources of harmful discrimination inherent in the design of assessment tools and systems. This study seeks to understand intrinsic inequity in assessment systems by studying assessment policies and associated procedures in residency training, using general pediatrics as a discourse case study. Foucauldian discourse analysis (FDA) was conducted on assessment policy and procedure documents. Two authors independently prepared structured analytic notes using guiding questions. Documents and respective analytic notes were subsequently reviewed independently by all authors. Each author prepared further unstructured analytic notes on the documents' discourse. The authors then compared notes and constructed truth statements (i.e., interpretations of what the discourse establishes as true about the construct under study) and sub-strands (i.e., themes) that were repeated and legitimized across the documents via iterative discussion. Based on analysis, the authors constructed two truth statements. These truth statements, "good assessment is equitable assessment," and "everyone is responsible for inequity," conceptualized inequity in assessment as an isolated or individual-level aberration in an otherwise effective or neutral system. Closer examination of the truth statements and sub-strands in the discourse presented an alternative view, suggesting that inequity may in fact not be an aberration but rather an inherent feature of assessment systems.

Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma.

Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the approximate Bayesian computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended fourier amplitude sensitivity test. Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for use with predictive analytics such as artificial intelligence (AI) methods, which require large datasets. To address this unmet need, we provide a multi-institutional, large-scale pediatric dataset of 23,101 multi-parametric MRI exams acquired through routine care for 1,526 brain tumor patients, as part of the Children's Brain Tumor Network. This includes longitudinal MRIs across various cancer diagnoses, with associated patient-level clinical information, digital pathology slides, as well as tissue genotype and omics data. To facilitate downstream analysis, treatment-naïve images for 370 subjects were processed and released through the NCI Childhood Cancer Data Initiative via the Cancer Data Service. Through ongoing efforts to continuously build these imaging repositories, our aim is to accelerate discovery and translational AI models with real-world data, to ultimately empower precision medicine for children.

Adding Value to Liquid Biopsy for Brain Tumors: The Role of Imaging.

Clinical management in neuro-oncology has changed to an integrative approach that incorporates molecular profiles alongside histopathology and imaging findings. While the World Health Organization (WHO) guideline recommends the genotyping of informative alterations as a routine clinical practice for central nervous system (CNS) tumors, the acquisition of tumor tissue in the CNS is invasive and not always possible. Liquid biopsy is a non-invasive approach that provides the opportunity to capture the complex molecular heterogeneity of the whole tumor through the detection of circulating tumor biomarkers in body fluids, such as blood or cerebrospinal fluid (CSF). Despite all of the advantages, the low abundance of tumor-derived biomarkers, particularly in CNS tumors, as well as their short half-life has limited the application of liquid biopsy in clinical practice. Thus, it is crucial to identify the factors associated with the presence of these biomarkers and explore possible strategies that can increase the shedding of these tumoral components into biological fluids. In this review, we first describe the clinical applications of liquid biopsy in CNS tumors, including its roles in the early detection of recurrence and monitoring of treatment response. We then discuss the utilization of imaging in identifying the factors that affect the detection of circulating biomarkers as well as how image-guided interventions such as focused ultrasound can help enhance the presence of tumor biomarkers through blood-brain barrier (BBB) disruption.

Risk factors for postoperative complications after adrenalectomy for phaeochromocytoma: multicentre cohort study.

BACKGROUND: To determine the incidence and risk factors for postoperative complications and prolonged hospital stay after adrenalectomy for phaeochromocytoma. METHODS: Demographics, perioperative outcomes and complications were evaluated for consecutive patients who underwent adrenalectomy for phaeochromocytoma from 2012 to 2020 in nine high-volume UK centres. Odds ratios were calculated using multivariable models. The primary outcome was postoperative complications according to the Clavien---Dindo classification and secondary outcome was duration of hospital stay. RESULTS: Data were available for 406 patients (female n = 221, 54.4 per cent). Two patients (0.5 per cent) had perioperative death, whilst 148 complications were recorded in 109 (26.8 per cent) patients. On adjusted analysis, the age-adjusted Charlson Co-morbidity Index ≥3 (OR 8.09, 95 per cent c.i. 2.31 to 29.63, P = 0.001), laparoscopic converted to open (OR 10.34, 95 per cent c.i. 3.24 to 36.23, P <0.001), and open surgery (OR 11.69, 95 per cent c.i. 4.52 to 32.55, P <0.001) were independently associated with postoperative complications. Overall, 97 of 430 (22.5 per cent) had a duration of stay ≥5 days and this was associated with an age-adjusted Charlson Co-morbidity Index ≥3 (OR 4.31, 95 per cent c.i. 1.08 to 18.26, P = 0.042), tumour size (OR 1.15, 95 per cent c.i. 1.05 to 1.28, P = 0.006), laparoscopic converted to open (OR 32.11, 95 per cent c.i. 9.2 to 137.77, P <0.001), and open surgery (OR 28.01, 95 per cent c.i. 10.52 to 83.97, P <0.001). CONCLUSION: Adrenalectomy for phaeochromocytoma is associated with a very low mortality rate, whilst postoperative complications are common. Several risk factors, including co-morbidities and operative approach, are independently associated with postoperative complications and/or prolonged hospitalization, and should be considered when counselling patients.

Temporal variability in nutrient use among Streptomyces suggests dynamic niche partitioning.

Soil bacteria spend significant periods in dormant or semi-dormant states that are interrupted by resource pulses which can lead to periods of rapid growth and intense nutrient competition. Microbial populations have evolved diverse strategies to circumvent competitive interactions and facilitate coexistence. Here, we show that nutrient use of soilborne Streptomyces is temporally partitioned during experimental resource pulses, leading to reduced niche overlap, and potential coexistence. Streptomyces grew rapidly on the majority of distinct 95 carbon sources but varied in which individual resources were utilized in the first 24 h. Only a handful of carbon sources (19 out of 95) were consistently utilized (>95% of isolates) most rapidly in the first 24 h. These consistently utilized carbon sources also generated the majority of biomass accumulated by isolates. Our results shed new light on a novel mechanism microbes may employ to alleviate competitive interactions by temporally partitioning the consumption of carbon resources. As competitive interactions have been proposed to drive the suppression of disease-causing microbes in agronomic soils, our findings may hold widespread implications for soil management for plant health.

Paraneoplastic Pemphigus/Paraneoplastic Autoimmune Multiorgan Syndrome: Part II. Diagnosis and Management.

In the second part of this Continuing Medical Education article on paraneoplastic pemphigus/paraneoplastic autoimmune multiorgan syndrome (PNP/PAMS), its diagnostic criteria, investigative work-up, and management are reviewed. PNP/PAMS is a rare autoimmune blistering disorder associated with high morbidity and mortality. Recognizing PNP/PAMS's key features and its diagnostic criteria is critical in initiating appropriate work-up. Evaluating PNP/PAMS requires knowledge of its findings on histopathology, direct immunofluorescence, indirect immunofluorescence, and enzyme-linked immunosorbent assay. Lastly, treatments for PNP/PAMS are reviewed with suggestions based on case reports and expert opinions in the literature. LEARNING OBJECTIVES: After completing this learning objective, the reader will be able to identify the criteria necessary for diagnosing paraneoplastic pemphigus (PNP/PAMS), learn how to work-up a diagnosis of PNP/PAMS, and understand important principles in the management of PNP/PAMS.

Paraneoplastic pemphigus/paraneoplastic autoimmune multiorgan syndrome: Part I. clinical overview and pathophysiology.

Paraneoplastic pemphigus/paraneoplastic autoimmune multiorgan syndrome (PNP/PAMS) is a highly fatal autoimmune blistering disease. The condition occurs in patients with underlying benign or malignant neoplasms, most commonly lymphoproliferative disorders. Both humoral and cell-mediated immunities contribute to the pathogenesis, and autoantibodies against plakin family proteins are characteristic. Patients typically present with severe stomatitis and polymorphous skin lesions, which are often resistant to treatment. Bronchiolitis obliterans (BO) is a frequent complication which contributes to the high mortality rate of PNP/PAMS. Given the rarity of this disorder and heterogeneity of clinical presentation, clinicians should maintain a high index of suspicion for PNP/PAMS to avoid delayed diagnosis. In this first part of a two-part continuing medical education (CME) series, risk factors, pathogenesis, and clinical features of PNP/PAMS are discussed.

Stats on the desats: alarm fatigue and the implications for patient safety.

BACKGROUND: Physiological monitoring systems, like Masimo, used during inpatient hospitalisation, offer a non-invasive approach to capture critical vital signs data. These systems trigger alarms when measurements deviate from preset parameters. However, often non-urgent or potentially false alarms contribute to 'alarm fatigue,' a form of sensory overload that can have adverse effects on both patients and healthcare staff. The Joint Commission, in 2021, announced a target to mitigate alarm fatigue-related fatalities through improved alarm management. Yet, no established guidelines are presently available. This study aims to address alarm fatigue at the Mayo Clinic to safeguard patient safety, curb staff burnout and improve the sensitivity of oxygen saturation monitoring to promptly detect emergencies. METHODS: A quality improvement project was conducted to combat minimise the false alarm burden, with data collected 2 months prior to intervention commencement. The project's goal was to decrease the total alarm value by 20% from 55%-85% to 35%-75% within 2 months, leveraging quality improvement methodologies. INTERVENTIONS: February to April 2021, we implemented a two-pronged intervention: (1) instituting a protocol to evaluate patients' continuous monitoring needs and discontinuing it when appropriate, and (2) introducing educational signage for patients and Mayo Clinic staff on monitoring best practices. RESULTS: Baseline averages of red alarms (158.6), manual snoozes (37.8) and self-resolves (120.7); the first postintervention phase showed reductions in red alarms (125.5), manual snoozes (17.8) and self-resolves (107.8). Second postintervention phase recorded 138 red alarms, 13 manual snoozes and 125 self-resolves. Baseline comparison demonstrated an average of 16.92% reduction of alarms among both interventions (p value: 0.25). CONCLUSION: Simple interventions like education and communication techniques proved instrumental in lessening the alarm burden for patients and staff. The findings underscore the practical use and efficacy of these methods in any healthcare setting, thus contributing to mitigating the prevalent issue of alarm fatigue.

Primary Retinal Detachment Repair in Eyes Deemed High Risk for Proliferative Vitreoretinopathy: Surgical Outcomes in 389 Eyes.

PURPOSE: To evaluate surgical outcomes in eyes with primary rhegmatogenous retinal detachment (RRD) deemed at high risk for postoperative proliferative vitreoretinopathy (PVR). DESIGN: Retrospective, consecutive case cohort study. PARTICIPANTS: Eyes undergoing primary RRD repair with pars plana vitrectomy (PPV) or combined PPV with scleral buckling (PPV/SB) between January 1, 2016, and December 30, 2017, at Wills Eye Hospital. METHODS: Eyes were defined as "high risk" if ≥ 1 of the following risk factors for PVR was present on preoperative examination: preoperative PVR grade A or B, vitreous hemorrhage, RRD involving ≥ 50% of retinal area, presence of ≥ 3 retinal breaks, history of prior cryotherapy, presence of choroidal detachment, or duration of RRD > 2 weeks. Surgical failure was defined as an additional intervention required for the retinal reattachment. MAIN OUTCOMES MEASURES: Single surgery attachment success (SSAS) rate 3 months after first surgical intervention for primary RRD. RESULTS: Of 2053 reviewed charts, a total of 389 eyes (18.9%) met the definition of high risk and were included in the analysis. Mean patient age was 63.5 years. PPV/SB was performed in 125 (32.1%) eyes and PPV alone in 264 (67.9%) eyes. SSAS rate of the overall cohort was 71.5% at 3 months. SSAS rate was significantly higher in eyes treated with PPV/SB compared with PPV (80.8% vs. 67%, respectively, P = 0.006). On multivariate analysis, use of PPV/SB was the only feature associated with SSAS (odds ratio, 2.04; 95% confidence interval, 1.12-3.69, P = 0.019). CONCLUSION: In eyes with primary RRD and risk factors for PVR, overall SSAS was 71.5% after primary repair. In this cohort, use of PPV/SB was associated with a significantly higher SSAS compared with PPV alone. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Predicting clinical outcomes of patients with serum thyroglobulin antibodies after thyroidectomy for differentiated thyroid cancer: a retrospective study from a UK regional center.

BACKGROUND: Twenty-twenty-five percent of patients with differentiated thyroid cancer (DTC) can have elevated thyroglobulin antibodies (TgAb). The study aimed to find any prognostic significance of elevated TgAb during follow-up. METHODS: Ten-year retrospective study from a tertiary center including 79 patients with raised TgAb after total/staged thyroidectomy for DTC. We identified patients with stable (7.6%), increasing (15%) and decreasing levels of TgAb (77.2%); groups 1, 2 and 3 respectively. During follow-up we analyzed TgAb in subcategories by TgAb trend (>50% rise, <50% rise, >50% decline, <50% decline, positive to negative/normalization, negative to positive and stable levels), gender, age, surgery, autoimmune disease, histology, RAI uptake, distant metastases, and recurrence. RESULTS: The incidence of raised TgAb levels was 33.2%, with female predominance. No connection was identified regarding other parameters. 11.4% had distant metastases. The highest mean maximum levels of TgAb was in group 2 (1918.75 IU/mL) and the lowest in group 3 (412.70 IU/mL). The recurrence rate changed significantly between the 3 groups: 50% in group 1, 75% in group 2, and 25% in group 3 (P=0.002). Recurrence rates decreased to 15% in the subcategory where TgAb became negative/normal from positive (P=0.0001). In patients with a negative to positive TgAb level trend or >50% rise, recurrence rates were 100% (P=0.041) and 70% (P=0.012) respectively. CONCLUSIONS: Patients with increasing TgAb levels during follow-up have a higher rate of recurrence, distinctly for those with negative to positive trend and >50% rise in TgAb. These patients need closer follow-up, and TgAb may be used as a dynamic follow-up marker.