Treatment of Ischemic Stroke by Atorvastatin-Loaded PEGylated Liposome.

There is insufficient evidence on the effect of nanoparticles, particularly liposomes loaded with a statin, on acute ischemic stroke. We investigated the impact of atorvastatin-loaded PEG (polyethylene glycol) conjugated liposomes (LipoStatin) on the outcomes in rats with cerebral ischemia-reperfusion. PEGylated liposome loaded with atorvastatin was developed as a nanoparticle to specifically accumulate in an ischemic region and release the drug to ameliorate the harmful effects of the stroke. LipoStatin was administered to rats with transient middle cerebral artery occlusion through the tail vein immediately after reperfusion (LipoStatin group). LipoStatin efficiently accumulated at the cerebral ischemic injury site of the rat. The LipoStatin group showed a significantly reduced infarct volume (p < 0.01) in brain micro-MR imaging and improved neurological function recovery compared to the control group (p < 0.05). In addition, markedly improved brain metabolism using fluorine-18 fluorodeoxyglucose micro-PET/CT imaging was demonstrated in the LipoStatin group compared with the control group (p < 0.01). Mechanistically, as a result of evaluation through IL-1 beta, TNF-alpha, ICAM-1, and Iba-1 mRNA expression levels at 5 days after cerebral ischemia, LipoStatin showed significant anti-inflammatory effects. Protein expression of occludin, JAM-A, Caveolin-1, and eNOS by western blot at 3 days and fluorescent images at 7 days showed considerable recovery of blood-brain barrier breakdown and endothelial dysfunction. PEGylated LipoStatin can be more effectively delivered to the ischemic brain and may have significant neuroprotective effects. Thus, PEGylated LipoStatin can be further developed as a promising targeted therapy for ischemic stroke and other major vascular diseases.

Discordant Uptake of Leg Thrombi Versus Pulmonary Emboli on 68 Ga-FAPI-46 PET/CT.

ABSTRACT: Fibroblast activation protein inhibitor (FAPI) PET is gaining clinical relevance for visualizing activated fibroblasts in various diseases. Here, we report discordant FAPI uptake between venous thrombi of the lower extremities and pulmonary emboli. An 86-year-old man complained of left leg swelling and acute dyspnea; he was diagnosed with deep vein thrombosis involving the left femoral vein and acute pulmonary thromboembolism. Positive FAPI uptake was observed only in the thrombi of the left femoral vein, but not in the pulmonary emboli. Such discrepancies may indicate different thrombus constituents and chronologies even in the same patient.

Serial 68Ga-FAPI PET/CT After Treatment of Immunoglobulin G4-Related Pancreatitis and Retroperitoneal Fibrosis.

ABSTRACT: Immunoglobulin G4 (IgG4)-related disease is a fibroinflammatory condition involving diverse organs. We report a case of IgG4-related pancreatitis and retroperitoneal fibrosis with serial 68Ga-FAPI PET/CT scans after treatment. A 64-year-old man presented with left flank and epigastric pain. Laboratory, abdominal CT, and 68Ga-FAPI PET/CT findings were suggestive of IgG4-related pancreatitis and retroperitoneal fibrosis. Histology of the pancreas confirmed IgG4-related pancreatitis. The follow-up PET/CT scans after treatment with steroid therapy showed regression of 68Ga-FAPI uptake in the pancreas and periureteral soft tissue. The changes on 68Ga-FAPI PET/CT scans were much more prominent compared with the CT scans.

Tc-99m DMSA SPECT for Follow-Up of Non-Operative Treatments in Renal Injuries: A Prospective Single-Center Study.

OBJECTIVE: The assessment of cortical integrity following renal injuries with planar Tc-99m dimercaptosuccinic acid (DMSA) scintigraphy depends on measuring relatively decreased cortical uptake (i.e., split renal function [SRF]). We analyzed the additive values of the volumetric and quantitative analyses of the residual cortical integrity using single-photon emission computed tomography (SPECT) compared to the planar scintigraphy. MATERIALS AND METHODS: This prospective study included 47 patients (male:female, 32:15; age, 47 ± 22 years) who had non-operatively managed renal injuries and underwent DMSA planar and SPECT imaging 3-6 months after the index injury. In addition to planar SRF, SPECT SRF, cortical volume, and absolute cortical uptake were measured for the injured kidney and both kidneys together. The correlations of planar SRF with SPECT SRF and those of SRF with volumetric/quantitative parameters obtained with SPECT were analyzed. The association of SPECT parameters with renal function, grades of renal injuries, and the risk of renal failure was also analyzed. RESULTS: SPECT SRF was significantly lower than planar SRF, with particularly higher biases in severe renal injuries. Planar and SPECT SRF (dichotomized with a cutoff of 45%) showed 19%-36% of discrepancies with volumetric and quantitative DMSA indices (when dichotomized as either high or low). Absolute cortical uptake of the injured kidney best correlated with glomerular filtration rate (GFR) at follow-up (ρ = 0.687, P < 0.001) with significant stepwise decreases by GFR strata (90 and 60 mL/min/1.73 m²). Total renal cortical uptake was significantly lower in patients with moderate-to-high risk of renal failure than those with low risk. However, SRF did not reflect GFR decrease below 60 mL/min/1.73 m² or the risk of renal failure, regardless of planar or SPECT (count- or volume-based SRF) imaging. CONCLUSION: Quantitative measurements of renal cortical integrity assessed with DMSA SPECT can provide more clinically relevant and comprehensive information than planar imaging or SRF alone.

Multimodal multitask learning for predicting MCI to AD conversion using stacked polynomial attention network and adaptive exponential decay.

Early identification and treatment of moderate cognitive impairment (MCI) can halt or postpone Alzheimer's disease (AD) and preserve brain function. For prompt diagnosis and AD reversal, precise prediction in the early and late phases of MCI is essential. This research investigates multimodal framework-based multitask learning in the following situations: (1) Differentiating early mild cognitive impairment (eMCI) from late MCI and (2) predicting when an MCI patient would acquire AD. Clinical data and two radiomics features on three brain areas deduced from magnetic resonance imaging were investigated (MRI). We proposed an attention-based module, Stack Polynomial Attention Network (SPAN), to firmly encode clinical and radiomics data input characteristics for successful representation from a small dataset. To improve multimodal data learning, we computed a potent factor using adaptive exponential decay (AED). We used experiments from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort study, which included 249 eMCI and 427 lMCI participants at baseline visits. The proposed multimodal strategy yielded the best c-index score in time prediction of MCI to AD conversion (0.85) and the best accuracy in MCI-stage categorization ([Formula: see text]). Moreover, our performance was equivalent to that of contemporary research.

68 Ga-FAPI PET/CT Imaging of the Pancreas in a Patient With Fulminant Type 1 Diabetes.

ABSTRACT: Fulminant type 1 diabetes is a recently recognized diabetes subtype characterized by extremely rapid destruction of the pancreatic beta cells, leading to an absolute deficiency in insulin secretion. Fulminant type 1 diabetes is clinically characterized by the drastic onset of hyperglycemia and ketoacidosis within a few days, as well as near-normal glycated hemoglobin (HbA 1c ) levels despite remarkable hyperglycemia at initial presentation. A 41-year-old woman diagnosed with fulminant type 1 diabetes underwent 68 Ga-FAPI PET/CT, which showed intense FAPI uptake throughout the pancreas, especially in the pancreatic tail. Contrast-enhanced abdominal CT failed to reveal any pancreatic abnormalities. This case indicated that 68 Ga-FAPI PET/CT might be useful for evaluating patients with fulminant type 1 diabetes.

Magnetothermal-based non-invasive focused magnetic stimulation for functional recovery in chronic stroke treatment.

Magnetic heat-based brain stimulation of specific lesions could promote the restoration of impaired motor function caused by chronic stroke. We delivered localized stimulation by nanoparticle-mediated heat generation within the targeted brain area via focused magnetic stimulation. The middle cerebral artery occlusion model was prepared, and functional recovery in the chronic-phase stroke rat model was demonstrated by the therapeutic application of focused magnetic stimulation. We observed a transient increase in blood-brain barrier permeability at the target site of < 4 mm and metabolic brain activation at the target lesion. After focused magnetic stimulation, the rotarod score increased by 390 ± 28% (p < 0.05) compared to the control group. Standardized uptake value in the focused magnetic stimulation group increased by 2063 ± 748% (p < 0.01) compared to the control group. Moreover, an increase by 24 ± 5% (p < 0.05) was observed in the sham group as well. Our results show that non-invasive focused magnetic stimulation can safely modulate BBB permeability and enhance neural activation for chronic-phase stroke treatment in the targeted deep brain area.

Applying Pix2pix to Translate Hyperemia in Blood Pool Image into Corresponding Increased Bone Uptake in Delayed Image in Three-Phase Bone Scintigraphy.

Purpose: Delayed images may not be acquired due to severe pain, drowsiness, or worsening vital signs while waiting after blood pool imaging in three-phase bone scintigraphy. If the hyperemia in the blood pool image contains information from which increased uptake on the delayed images can be inferred, the generative adversarial network (GAN) can generate the increased uptake from the hyperemia. We attempted to apply pix2pix, a type of conditional GAN, to transform hyperemia into increased bone uptake. Methods: We enrolled 1464 patients who underwent three-phase bone scintigraphy for inflammatory arthritis, osteomyelitis, complex regional pain syndrome (CRPS), cellulitis, and recent bone injury. Blood pool images were acquired 10 min after intravenous injection of Tc-99 m hydroxymethylene diphosphonate, and delayed bone images were obtained after 3 h. The model was based on the open-source code of the pix2pix model with perceptual loss. Increased uptake in the delayed images generated by the model was evaluated using lesion-based analysis by a nuclear radiologist in areas consistent with hyperemia in the blood pool images. Results: The model showed sensitivities of 77.8% and 87.5% for inflammatory arthritis and CRPS, respectively. In osteomyelitis and cellulitis, their sensitivities of about 44% were observed. However, in cases of recent bone injury, the sensitivity was only 6.3% in areas consistent with focal hyperemia. Conclusion: The model based on pix2pix generated increased uptake in delayed images matching the hyperemia in the blood pool image in inflammatory arthritis and CRPS.

Polyarteritis nodosa presenting as leg pain with resolution of positron emission tomography-images: A case report.

BACKGROUND: Although fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) is widely used for diagnosis and follow-up of large sized vessel vasculitis, it is still not widely used for small to medium sized vessel vasculitis. CASE SUMMARY: This is the case of a 68-year-old male who presented at the emergency department complaining of fever, myalgia, and bilateral leg pain of over two weeks duration, with elevated levels of C-reactive protein. He was subsequently admitted and despite the absence of clinically significant findings, the patient continued to exhibit recurrent fever. A fever of unknown origin workup, which included imaging studies using FDG-PET/CT, revealed vasculitis involving small to medium-sized vessels of both lower extremities, demonstrated by linear hypermetabolism throughout the leg muscles. The patient was treated with methylprednisolone and methotrexate after diagnosis leading to the gradual resolution of the patient's symptoms. Three weeks later, a follow-up FDG-PET/CT was performed. Previously hypermetabolic vessels were markedly improved. CONCLUSION: Our case report demonstrated that FDG-PET/CT has tremendous potential to detect medium-sized vessel inflammation; it can also play a crucial role in prognosticating outcomes and monitoring therapeutic efficacy.

Deep learning-based personalised outcome prediction after acute ischaemic stroke.

BACKGROUND: Whether deep learning models using clinical data and brain imaging can predict the long-term risk of major adverse cerebro/cardiovascular events (MACE) after acute ischaemic stroke (AIS) at the individual level has not yet been studied. METHODS: A total of 8590 patients with AIS admitted within 5 days of symptom onset were enrolled. The primary outcome was the occurrence of MACEs (a composite of stroke, acute myocardial infarction or death) over 12 months. The performance of deep learning models (DeepSurv and Deep-Survival-Machines (DeepSM)) and traditional survival models (Cox proportional hazards (CoxPH) and random survival forest (RSF)) were compared using the time-dependent concordance index ([Formula: see text] index). RESULTS: Given the top 1 to all 60 clinical factors according to feature importance, CoxPH and RSF yielded [Formula: see text] index of 0.7236-0.8222 and 0.7279-0.8335, respectively. Adding image features improved the performance of deep learning models and traditional models assisted by deep learning models. DeepSurv and DeepSM yielded the best [Formula: see text] index of 0.8496 and 0.8531 when images were added to all 39 relevant clinical factors, respectively. In feature importance, brain image was consistently ranked highly. Deep learning models automatically extracted the image features directly from personalised brain images and predicted the risk and date of future MACEs at the individual level. CONCLUSIONS: Deep learning models using clinical data and brain images could improve the prediction of MACEs and provide personalised outcome prediction for patients with AIS. Deep learning models will allow us to develop more accurate and tailored prognostic prediction systems that outperform traditional models.

Evaluation of Non-infarct-Related Arteries Using C-11 Acetate PET in STEMI With Multivessel Disease.

BACKGROUND: We analyzed whether C-11 acetate positron emission tomography (PET) can be used for the evaluation of non-infarct-related artery (NIRA) in patients with ST-elevation myocardial infarction (STEMI) and multivessel disease. METHODS: We prospectively enrolled 31 patients with STEMI and at least one NIRA stenosis (diameter stenosis [DS] ≥ 50%). C-11 acetate PET was performed after successful revascularization for the infarct-related artery (IRA). Myocardial blood flow (MBF) and oxidative metabolism (kmono) were measured and compared between NIRA vs. IRA, stenotic (DS ≥ 50%) vs. non-stenotic (DS < 50%) NIRAs, and NIRAs with significant stenosis (DS ≥ 70% or fractional flow reserve [FFR] ≤ 0.80) vs. those without (neither DS ≥ 70% nor FFR ≤ 0.80). The correlations between PET and angiographic parameters were also analyzed. RESULTS: MBF and kmono were significantly higher in NIRAs than those in IRAs. Stenotic NIRAs showed significantly reduced stress MBF, myocardial flow reserve (MFR), relative flow reserve (RFR) (0.72 ± 0.12 vs. 0.82 ± 0.14; p = 0.001), and stress kmono, as compared to those in non-stenotic NIRAs. NIRAs with significant stenosis had significantly lower stress MBF, MFR, and RFR (0.70 ± 0.10 vs. 0.80 ± 0.14; p = 0.001). RFR showed the best, but modest linear correlation with DS of NIRA stenosis (r = -0.429, p = 0.001). RFR > 0.81 could effectively exclude the presence of significant NIRA stenosis. CONCLUSIONS: C-11 acetate PET could be a feasible alternative noninvasive modality in patients with STEMI and multivessel disease, by excluding the presence of significant NIRA stenosis.

Predicting progression of Alzheimer's disease using forward-to-backward bi-directional network with integrative imputation.

If left untreated, Alzheimer's disease (AD) is a leading cause of slowly progressive dementia. Therefore, it is critical to detect AD to prevent its progression. In this study, we propose a bidirectional progressive recurrent network with imputation (BiPro) that uses longitudinal data, including patient demographics and biomarkers of magnetic resonance imaging (MRI), to forecast clinical diagnoses and phenotypic measurements at multiple timepoints. To compensate for missing observations in the longitudinal data, we use an imputation module to inspect both temporal and multivariate relations associated with the mean and forward relations inherent in the time series data. To encode the imputed information, we define a modification of the long short-term memory (LSTM) cell by using a progressive module to compute the progression score of each biomarker between the given timepoint and the baseline through a negative exponential function. These features are used for the prediction task. The proposed system is an end-to-end deep recurrent network that can accomplish multiple tasks at the same time, including (1) imputing missing values, (2) forecasting phenotypic measurements, and (3) predicting the clinical status of a patient based on longitudinal data. We experimented on 1,335 participants from The Alzheimer's Disease Prediction of Longitudinal Evolution (TADPOLE) challenge cohort. The proposed method achieved a mean area under the receiver-operating characteristic curve (mAUC) of 78% for predicting the clinical status of patients, a mean absolute error (MAE) of 3.5ml for forecasting MRI biomarkers, and an MAE of 6.9ml for missing value imputation. The results confirm that our proposed model outperforms prevalent approaches, and can be used to minimize the progression of Alzheimer's disease.

Prediction of cardiac events following concurrent chemoradiation therapy for non-small-cell lung cancer using FDG PET.

OBJECTIVE: No imaging biomarkers are available for the prediction of cardiac events following concurrent chemoradiation therapy (CCRT) for non-small-cell lung cancer (NSCLC). We evaluated whether F-18 fluorodeoxyglucose positron emission tomography (FDG PET) early after CCRT, in addition to cardiac dosimetry, could predict late cardiac events in NSCLC. METHODS: We retrospectively enrolled 133 consecutive patients with locally advanced, unresectable stage III NSCLC, who underwent FDG PET early after CCRT and survived at least 6 months. The primary endpoint was cardiac event ≥ grade 2 according to the Common Terminology Criteria for Adverse Events (version 5.0). Myocardial FDG uptake was measured and its association with the risk of cardiac events was evaluated. RESULTS: FDG PET was performed after a median interval of 11 days of completing CCRT. Overall, 42 (32%) patients experienced cardiac events during a median follow-up of 45 months. The mean heart dose, maximum left ventricular (LV) standardized uptake value (SUV), changes in maximum and mean LV SUV, right ventricular uptake, tumor stage, white blood cell count, and diabetes were associated with cardiac events in univariable analysis. In multivariable analysis, maximum LV SUV (cutoff > 12.84; hazard ratio [95% confidence interval] = 2.140 [1.140-4.016]; p = 0.018) was an independent predictor of cardiac events along with the mean heart dose (> 11.1 Gy; 3.646 [1.792-7.417]; p < 0.001) and tumor stage (IIIB; 1.986 [1.056-3.734]; p = 0.033). It remained predictive of cardiac events in those with higher mean heart dose but not in those with lower mean heart dose. CONCLUSIONS: Early FDG PET after CCRT for NSCLC could aid in predicting late cardiac events, especially in patients with higher mean heart dose.

Precise characterization of a solitary pulmonary nodule using tumor shadow disappearance rate-corrected F-18 FDG PET and enhanced CT.

ABSTRACT: We aimed to characterize solitary pulmonary nodule (SPN) using imaging parameters for F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) or enhanced CT corrected by tumor shadow disappearance rate (TDR) to reflect the tissue density.We enrolled 51 patients with an SPN who underwent PET/CT and chest CT with enhancement. The FDG uptake of SPN was evaluated using maximum standardized uptake value (SUVmax) on PET/CT. The mean Hounsfield unit (HU) for each SPN was evaluated over the region of interest on nonenhanced and enhanced CT images. The change in mean HU (HUpeak-pre) was quantified by subtracting the mean HU of the preenhanced CT from that of the post-enhanced CT. TDR was defined as the ratio of the tumor area, which disappears at a mediastinal window, to the tumor area of the lung window. We investigated which parameters (SUVmax or HUpeak-pre) could contribute to the characterization of SPN classified by TDR value and whether diagnostic performance could be improved using TDR-corrected imaging parameters.For SPN with higher tissue density (TDR <42%, n = 22), high value of SUVmax (≥3.1) was a significant factor to predict malignancy (P = .006). High value of HUpeak-pre (≥38) was a significant factor to characterize SPN (P = .002) with lower tissue density (TDR ≥42%, n = 29). The combined approach using TDR-corrected parameters had better predictive performance to characterize SPN than SUVmax only (P = .031).Applying imaging parameters such as SUVmax or HUpeak-pre in consideration of tissue density calculated with TDR could contribute to accurate characterization of SPN.

Diagnostic Blood Biomarkers in Alzheimer's Disease.

Potential biomarkers for Alzheimer's disease (AD) include amyloid ß1-42 (Aß1-42), t-Tau, p-Tau181, neurofilament light chain (NFL), and neuroimaging biomarkers. Their combined use is useful for diagnosing and monitoring the progress of AD. Therefore, further development of a combination of these biomarkers is essential. We investigated whether plasma NFL/Aß1-42 can serve as a plasma-based primary screening biomarker reflecting brain neurodegeneration and amyloid pathology in AD for monitoring disease progression and early diagnosis. We measured the NFL and Aß1-42 concentrations in the CSF and plasma samples and performed correlation analysis to evaluate the utility of these biomarkers in the early diagnosis and monitoring of AD spectrum disease progression. Pearson's correlation analysis was used to analyse the associations between the fluid biomarkers and neuroimaging data. The study included 136 participants, classified into five groups: 28 cognitively normal individuals, 23 patients with preclinical AD, 22 amyloid-negative patients with amnestic mild cognitive impairment, 32 patients with prodromal AD, and 31 patients with AD dementia. With disease progression, the NFL concentrations increased and Aß1-42 concentrations decreased. The plasma and CSF NFL/Aß1-42 were strongly correlated (r = 0.558). Plasma NFL/Aß1-42 was strongly correlated with hippocampal volume/intracranial volume (r = 0.409). In early AD, plasma NFL/Aß1-42 was associated with higher diagnostic accuracy than the individual biomarkers. Moreover, in preclinical AD, plasma NFL/Aß1-42 changed more rapidly than the CSF t-Tau or p-Tau181 concentrations. Our findings highlight the utility of plasma NFL/Aß1-42 as a non-invasive plasma-based biomarker for early diagnosis and monitoring of AD spectrum disease progression.

Change of Therapeutic Response Classification According to Recombinant Human Thyrotropin-Stimulated Thyroglobulin Measured at Different Time Points in Papillary Thyroid Carcinoma.

PURPOSE: We investigated whether response classification after total thyroidectomy and radioactive iodine (RAI) therapy could be affected by serum levels of recombinant human thyrotropin (rhTSH)-stimulated thyroglobulin (Tg) measured at different time points in a follow-up of patients with papillary thyroid carcinoma (PTC). METHODS: A total of 147 PTC patients underwent serum Tg measurement for response assessment 6 to 24 months after the first RAI therapy. Serum Tg levels were measured at 24 h (D1Tg) and 48-72 h (D2-3Tg) after the 2nd injection of rhTSH. Responses were classified into three categories based on serum Tg corresponding to the excellent response (ER-Tg), indeterminate response (IR-Tg), and biochemical incomplete response (BIR-Tg). The distribution pattern of response classification based on serum Tg at different time points (D1Tg vs. D2-3Tg) was compared. RESULTS: Serum D2-3Tg level was higher than D1Tg level (0.339 ng/mL vs. 0.239 ng/mL, P < 0.001). The distribution of response categories was not significantly different between D1Tg-based and D2-3Tg-based classification. However, 8 of 103 (7.8%) patients and 3 of 40 (7.5%) patients initially categorized as ER-Tg and IR-Tg based on D1Tg, respectively, were reclassified to IR-Tg and BIR-Tg based on D2-3Tg, respectively. The optimal cutoff values of D1Tg for the change of response categories were 0.557 ng/mL (from ER-Tg to IR-Tg) and 6.845 ng/mL (from IR-Tg to BIR-Tg). CONCLUSION: D1Tg measurement was sufficient to assess the therapeutic response in most patients with low level of D1Tg. Nevertheless, D2-3Tg measurement was still necessary in the patients with D1Tg higher than a certain level as response classification based on D2-3Tg could change.

d-dimer Level as a Predictor of Recurrent Stroke in Patients With Embolic Stroke of Undetermined Source.

Background and Purpose: This study aimed to investigate the value of d-dimer levels in predicting recurrent stroke in patients with embolic stroke of undetermined source. We also evaluated the underlying causes of recurrent stroke according to d-dimer levels. Methods: A total of 1431 patients with undetermined source were enrolled in this study and divided into quartiles according to their baseline plasma d-dimer levels. The primary outcome measure was the occurrence of recurrent stroke (ischemic or hemorrhagic) in the year following the stroke event. Results: The risk of recurrent stroke increased significantly with the increasing d-dimer quartile (log-rank P=0.001). Patients in the higher d-dimer quartiles had a higher probability of recurrent embolic stroke because of covert atrial fibrillation, hidden malignancy, or undetermined sources. Most recurrent strokes in Q3 and Q4 were embolic but not in Q1 or Q2. Multivariate analysis revealed that patients in Q3 and Q4 had a significantly increased risk of recurrent stroke compared with those in Q1 (hazard ratio, 3.12 [95% CI, 1.07−9.07], P=0.036; hazard ratio, 7.29 [95% CI, 2.59−20.52], P<0.001, respectively; Ptrend<0.001). Binary analyses showed a significant association between a high d-dimer level above normal range and the risk of recurrent stroke (hazard ratio, 2.48 [95% CI, 1.31−4.70], P=0.005). In subgroup analyses, a high d-dimer level was associated with a significantly higher risk of recurrent stroke in men than in women (P=0.039). Conclusions: Our findings suggest that d-dimer levels can be a useful risk assessment biomarker for predicting recurrent stroke, especially embolic ischemic stroke, in patients with undetermined source.