Imaging Biomarkers Research Articles

Time-to-Event Endpoints in Imaging Biomarker Studies.

Time-to-event endpoints are widely used as measures of patients' well-being and indicators of prognosis. In imaging-based biomarker studies, there are increasingly more studies that focus on examining imaging biomarkers' prognostic or predictive utilities on those endpoints, whether in a trial or an observational study setting. In this educational review article, we briefly introduce some basic concepts of time-to-event endpoints and point out potential pitfalls in the context of imaging biomarker research in hope of improving radiologists' understanding of related subjects. Besides, we have included some review and discussions on the benefits of using time-to-event endpoints and considerations on selecting overall survival or progression-free survival for primary analysis. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.

Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (). In addition, the change in normalized tumor upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

Dataset of weekly intra-treatment diffusion weighted imaging in head and neck cancer patients treated with MR-Linac

Radiation therapy (RT) is a crucial treatment for head and neck squamous cell carcinoma (HNSCC); however, it can have adverse effects on patients’ long-term function and quality of life. Biomarkers that can predict tumor response to RT are being explored to personalize treatment and improve outcomes. While tissue and blood biomarkers have limitations, imaging biomarkers derived from magnetic resonance imaging (MRI) offer detailed information. The integration of MRI and a linear accelerator in the MR-Linac system allows for MR-guided radiation therapy (MRgRT), offering precise visualization and treatment delivery. This data descriptor offers a valuable repository for weekly intra-treatment diffusion-weighted imaging (DWI) data obtained from head and neck cancer patients. By analyzing the sequential DWI changes and their correlation with treatment response, as well as oncological and survival outcomes, the study provides valuable insights into the clinical implications of DWI in HNSCC.

Noninvasive Atherosclerotic Phenotyping: The Next Frontier into Understanding the Pathobiology of Coronary Artery Disease.

Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease. Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation.

Differences in imaging biomarkers between patients with intermediate and advanced non-neovascular age-related macular degeneration (AMD) in the University of Colorado AMD registry.

To quantify and compare the different prevalence rates of specific retinal imaging biomarkers in patients with intermediate AMD (iAMD) and advanced non-neovascular AMD (nnAMD). Cross-sectional study of patients with iAMD and advanced nnAMD. Imaging studies were reviewed for qualitative imaging biomarkers. Choroidal thickness measurements were obtained subfoveally and in 1000 um and 2000 um intervals away from the fovea. The Chi-squared test and Fisher's exact test were used to compare rates of imaging biomarkers among the two cohorts. P-value of <0.05 was considered significant. 376 eyes of 197 patients with iAMD and 187 eyes of 97 patients with advanced nnAMD were recruited. There were significantly lower rates of the following imaging biomarkers in the iAMD compared with the advanced nnAMD cohorts: soft drusen (66.0% vs. 84.2%, p = 0.001), calcified drusen (4.3% vs. 40.0%, p < 0.0001), RPD (26.2% vs. 53.3%, p < 0.0001), ORT (0.5% vs. 46.9%, p < 0.0001), RP (1.1% vs. 46.3%, p < 0.0001), pigment migration (53.2% vs. 100%, p < 0.0001), and iRORA (17.9% vs. 80.2%, p < 0.0001). In the iAMD cohort, choroidal thickness was significantly greater at 188 µm (SD: 60) and 194 µm (SD: 69), compared to the advanced nnAMD with measurements of 153 µm (SD: 68), and 161 µm (SD: 76). This difference was statistically significant (p < 0.0001 and p = 0.0002). Our results highlight significant differences in imaging biomarkers between both cohorts. Key biomarkers, such as iRORA, RPD, pigment migration, and thinner choroidal thickness, were associated with advanced nnAMD. Identifying these biomarkers early may help target patients who could benefit from new treatments, potentially delaying vision loss.

When Two Eyes Don’t Suffice—Learning Difficult Hyperfluorescence Segmentations in Retinal Fundus Autofluorescence Images via Ensemble Learning

Hyperfluorescence (HF) and reduced autofluorescence (RA) are important biomarkers in fundus autofluorescence images (FAF) for the assessment of health of the retinal pigment epithelium (RPE), an important indicator of disease progression in geographic atrophy (GA) or central serous chorioretinopathy (CSCR). Autofluorescence images have been annotated by human raters, but distinguishing biomarkers (whether signals are increased or decreased) from the normal background proves challenging, with borders being particularly open to interpretation. Consequently, significant variations emerge among different graders, and even within the same grader during repeated annotations. Tests on in-house FAF data show that even highly skilled medical experts, despite previously discussing and settling on precise annotation guidelines, reach a pair-wise agreement measured in a Dice score of no more than 63–80% for HF segmentations and only 14–52% for RA. The data further show that the agreement of our primary annotation expert with herself is a 72% Dice score for HF and 51% for RA. Given these numbers, the task of automated HF and RA segmentation cannot simply be refined to the improvement in a segmentation score. Instead, we propose the use of a segmentation ensemble. Learning from images with a single annotation, the ensemble reaches expert-like performance with an agreement of a 64–81% Dice score for HF and 21–41% for RA with all our experts. In addition, utilizing the mean predictions of the ensemble networks and their variance, we devise ternary segmentations where FAF image areas are labeled either as confident background, confident HF, or potential HF, ensuring that predictions are reliable where they are confident (97% Precision), while detecting all instances of HF (99% Recall) annotated by all experts.

T2-FLAIR Mismatch: An Imaging Biomarker for Children’sMYB/MYBL1–Altered Diffuse Astrocytoma or Angiocentric Glioma

T2-FLAIR Mismatch: An Imaging Biomarker for Children’s<i>MYB/MYBL1</i>–Altered Diffuse Astrocytoma or Angiocentric Glioma

Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline

IntroductionAlzheimer’s Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent.MethodsTo better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus.ResultsSCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD.DiscussionThe diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.

A pathway linking pulse pressure to dementia in adults with Down syndrome

Abstract Individuals with Down syndrome (DS) are less likely to have hypertension than neurotypical adults. However, whether blood pressure measures are associated with brain health and clinical outcomes in this population has not been studied in detail. Here, we assessed whether pulse pressure is associated with markers of cerebrovascular disease and is linked to a diagnosis of dementia in adults with DS via structural imaging markers of cerebrovascular disease and atrophy. The study included participants with DS from the Biomarkers of Alzheimer’s Disease in Adults with Down Syndrome study (ADDS; n=195, age=50.6+7.2 years, 44% women, 18% diagnosed with dementia). Higher pulse pressure was associated with greater global, parietal, and occipital white matter hyperintensity (WMH) volume but not to enlarged perivascular spaces (PVS), microbleeds, or infarcts. Through a structural equation model, we found that pulse pressure was associated with greater WMH volume, which in turn was related to increased neurodegeneration, and subsequent dementia diagnosis. Pulse pressure is an important determinant of brain health and clinical outcomes in individuals with DS despite the low likelihood of frank hypertension.

Increased [18F]Fluorodeoxyglucose Uptake in the Left Pallidum in Military Veterans with Blast-Related Mild Traumatic Brain Injury: Potential as an Imaging Biomarker and Mediation with Executive Dysfunction and Cognitive Impairment.

Blast-related mild traumatic brain injury (blast-mTBI) can result in a spectrum of persistent symptoms leading to substantial functional impairment and reduced quality of life. Clinical evaluation and discernment from other conditions common to military service can be challenging and subject to patient recall bias and the limitations of available assessment measures. The need for objective biomarkers to facilitate accurate diagnosis, not just for symptom management and rehabilitation but for prognostication and disability compensation purposes is clear. Toward this end, we compared regional brain [18F]fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET) intensity-scaled uptake measurements and motor, neuropsychological, and behavioral assessments in 79 combat Veterans with retrospectively recalled blast-mTBI with 41 control participants having no lifetime history of TBI. Using an agnostic and unbiased approach, we found significantly increased left pallidum [18F]FDG-uptake in Veterans with blast-mTBI versus control participants, p < 0.0001; q = 3.29 × 10-9 [Cohen's d, 1.38, 95% confidence interval (0.96, 1.79)]. The degree of left pallidum [18F]FDG-uptake correlated with the number of self-reported blast-mTBIs, r2 = 0.22; p < 0.0001. Greater [18F]FDG-uptake in the left pallidum provided excellent discrimination between Veterans with blast-mTBI and controls, with a receiver operator characteristic area under the curve of 0.859 (p < 0.0001) and likelihood ratio of 21.19 (threshold:SUVR ≥ 0.895). Deficits in executive function assessed using the Behavior Rating Inventory of Executive Function-Adult Global Executive Composite T-score were identified in Veterans with blast-mTBI compared with controls, p < 0.0001. Regression-based mediation analyses determined that in Veterans with blast-mTBI, increased [18F]FDG-uptake in the left pallidum-mediated executive function impairments, adjusted causal mediation estimate p = 0.021; total effect estimate, p = 0.039. Measures of working and prospective memory (Auditory Consonant Trigrams test and Memory for Intentions Test, respectively) were negatively correlated with left pallidum [18F]FDG-uptake, p < 0.0001, with mTBI as a covariate. Increased left pallidum [18F]FDG-uptake in Veterans with blast-mTBI compared with controls did not covary with dominant handedness or with motor activity assessed using the Unified Parkinson's Disease Rating Scale. Localized increased [18F]FDG-uptake in the left pallidum may reflect a compensatory response to functional deficits following blast-mTBI. Limited imaging resolution does not allow us to distinguish subregions of the pallidum; however, the significant correlation of our data with behavioral but not motor outcomes suggests involvement of the ventral pallidum, which is known to regulate motivation, behavior, and emotions through basal ganglia-thalamo-cortical circuits. Increased [18F]FDG-uptake in the left pallidum in blast-mTBI versus control participants was consistently identified using two different PET scanners, supporting the generalizability of this finding. Although confirmation of our results by single-subject-to-cohort analyses will be required before clinical deployment, this study provides proof of concept that [18F]FDG-PET bears promise as a readily available noninvasive biomarker for blast-mTBI. Further, our findings support a causative relationship between executive dysfunction and increased [18F]FDG-uptake in the left pallidum.

Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer's Disease: A Pragmatic Review for Clinicians.

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer's disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

Human versus Artificial Intelligence: Validation of a Deep Learning Model for Retinal Layer and Fluid Segmentation in Optical Coherence Tomography Images from Patients with Age-Related Macular Degeneration

Artificial intelligence (AI) models have received considerable attention in recent years for their ability to identify optical coherence tomography (OCT) biomarkers with clinical diagnostic potential and predict disease progression. This study aims to externally validate a deep learning (DL) algorithm by comparing its segmentation of retinal layers and fluid with a gold-standard method for manually adjusting the automatic segmentation of the Heidelberg Spectralis HRA + OCT software Version 6.16.8.0. A total of sixty OCT images of healthy subjects and patients with intermediate and exudative age-related macular degeneration (AMD) were included. A quantitative analysis of the retinal thickness and fluid area was performed, and the discrepancy between these methods was investigated. The results showed a moderate-to-strong correlation between the metrics extracted by both software types, in all the groups, and an overall near-perfect area overlap was observed, except for in the inner segment ellipsoid (ISE) layer. The DL system detected a significant difference in the outer retinal thickness across disease stages and accurately identified fluid in exudative cases. In more diseased eyes, there was significantly more disagreement between these methods. This DL system appears to be a reliable method for accessing important OCT biomarkers in AMD. However, further accuracy testing should be conducted to confirm its validity in real-world settings to ultimately aid ophthalmologists in OCT imaging management and guide timely treatment approaches.

Revisiting the pathophysiology of intracranial hemorrhage in fetuses with Chiari II malformation - novel imaging biomarkers of disease severity?

Intracranial hemorrhage (ICH) has emerged as a notable concern in Chiari II malformation (CM II), yet its origins and clinical implications remain elusive. This study aims to validate the in-utero prevalence of ICH in CM II and investigate contributing factors, and visualize the findings in a network format. A single-center retrospective review of fetal MRI scans obtained in fetuses with CM II presenting (January 2007 to December 2022) was performed for ICH utilizing EPI-T2* blood-sensitive sequence. Fetuses with aqueduct stenosis (AS) were included as a control group. The incidence of ICH and corresponding gestational ages were compared between CM II and AS cases, and morphometric measurements (inner/outer CSF spaces, posterior fossa, venous structure) were compared among the four 1:1 age-matched groups: CM II+ICH, CM II-ICH, AS+ICH, and AS-ICH. Additionally, a co-occurrence network was constructed to visualize associations between phenotypic features in ICH cases. A total of 101 fetuses with CM II and 90 controls with AS at a median gestational age of 24.4 weeks and 22.8 weeks (P=.138) were included. Prevalence of ICH in fetuses with CM II was higher compared to the AS cases (28.7% vs 18.9%, P=.023), accompanied by congested veins (deep vein congestion mainly in young fetuses, and cortical veins may also be affected in older fetuses). ICH was notably correlated with specific anatomical features, essentially characterized by reduced outer cerebrospinal fluid spaces and clivus-supraocciput angle. The co-occurrence network analysis reveals complex connections including bony defects, small posterior fossa dimensions, vermis ectopia, reduced CSF spaces as well as venous congestion and venous sinus stenosis as pivotal components within the network. The high prevalence of ICH - detected by fetal MRI -among fetuses with CM emphasizes the pathophysiological importance of venous congestion, ICH, and vasogenic edema. As indicators of disease severity, these features may serve as helpful additional imaging biomarkers for the identification of potential candidates for fetal surgery.ABBREVIATIONS: CM II＝Chiari type II malformation; AS＝aqueduct stenosis; ICH ＝Intracranial hemorrhage.

Analysis of the clinical diagnostic capabilities of kidney imaging biomarkers based on diffusion-weighted imaging and ASL-perfusion data

Acute kidney failure is a polyetiological disease that is often occurs in patients, which requires a rapid therapeutic response to avoid progression of the condition. Magnetic resonance imaging of the kidneys (MRI) improves the understanding and assessment of pathological processes, supplementing the mandatory diagnostic minimum information in the study of kidney pathology.Objective. To evaluate the clinical diagnostic capabilities of kidney imaging biomarkers using diffusion-weighted imaging (DWI) and ASL-perfusion data for intensive care unit patients.Materials and methods. At the first Clinical Hospital in Smolensk 54 patients were examined who were inpatient treatment and in the intensive care unit. All patients underwent ultrasound examination of the kidneys with assessment of blood flow in the main kidney vessels, MRI of the kidneys, with DWI of the kidney parenchyma and ASL-perfusion included in the study protocol. MRI was carried with assessed b-factor 800 and was drawn apparent diffusion coefficient (ADC) maps. When carried ASL perfusion, the field of view covered the area of the parenchyma of both kidneys. The reference method was glomerular filtration rate for all of the patients. The control group was represented by healthy people (n=59). Consent to participate in the study was obtained from patients or their legal representatives. All stages of the study comply with the normative and regulatory documentation of Ministry of Health ща the Russian Federation.Results. It was concluded that there is a significant difference in ADC for prerenal causes and in ASL for renal causes. In 9 (16.7 %) patients, kidney ADC was 1.5±0.3 mm2/sec, ASL – perfusion – ≤ 250 ml/100g/min, compared with the control group. In this group, negative dynamics were observed within a week, тnegative laboratory dynamics correlates with radiation-based kidney biomarkers (r=0,965).Conclusion. The criteria of DWI and ASL-perfusion allow us to suspect or confirm the cause of acute kidney failure. A high correlation has been established between radiation biomarkers and laboratory criteria of functional damages (r=0.998), direct correlation between imaging biomarkers and organic kidney disease (r=0,901). These biomarkers make it possible to predict the first stage of acute kidney failure (AUROC 0,995, DI 0,867–0,999).

38-year-old woman with septic arthritis and retroperitoneal abscess after intraarticular corticosteroid injection: A case report

Rationale: Septic arthritis (SA) is an uncommon condition in which a pathogen invades a joint. SA presents clinically with monoarticular joint pain, swelling, and fever. Computed tomography and magnetic resonance imaging are common diagnostic modalities for SA in conjunction with lab work such as white blood cell count. SA is typically treated by joint drainage and antibiotics and is associated with poor outcomes. Patient concerns: A 38-year-old woman with 3 prior arthroscopies over a seven-year period presented with an unresolved eight-year history of sharp intermittent pain in the groin and lateral hip. She was referred for nonsurgical treatment of her pain and received 2 corticosteroid hip injections. Subsequently following the injection, the patient developed fever, chills, and a mottled rash over her hip. Diagnoses: Magnetic resonance imaging and inflammatory markers were obtained. Osteomyelitis with septic arthritis of the right hip with extension into the retroperitoneum was confirmed. Interventions: The patient underwent resection arthroplasty with open retroperitoneal decompression of the iliopsoas abscess. Cultures isolated Staphylococcus aureus. Subsequent staged articulating hip spacer followed by reimplantation with total hip arthroplasty were performed. Outcomes: The patient had significant improvement as measured by patient reported outcomes scores. Lessons: This case report describes a unique case of hip septic arthritis, with retroperitoneal abscess post-intra articular injection, that resulted in subsequent open retroperitoneal incision and debridement followed by two-stage resection arthroplasty with articulating spacer and total hip arthroplasty.

Deep learning-based whole-body PSMA PET/CT attenuation correction utilizing Pix-2-Pix GAN.

Sequential PET/CT studies oncology patients can undergo during their treatment follow-up course is limited by radiation dosage. We propose an artificial intelligence (AI) tool to produce attenuation-corrected PET (AC-PET) images from non-attenuation-corrected PET (NAC-PET) images to reduce need for low-dose CT scans. A deep learning algorithm based on 2D Pix-2-Pix generative adversarial network (GAN) architecture was developed from paired AC-PET and NAC-PET images. 18F-DCFPyL PSMA PET-CT studies from 302 prostate cancer patients, split into training, validation, and testing cohorts (n = 183, 60, 59, respectively). Models were trained with two normalization strategies: Standard Uptake Value (SUV)-based and SUV-Nyul-based. Scan-level performance was evaluated by normalized mean square error (NMSE), mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Lesion-level analysis was performed in regions-of-interest prospectively from nuclear medicine physicians. SUV metrics were evaluated using intraclass correlation coefficient (ICC), repeatability coefficient (RC), and linear mixed-effects modeling. Median NMSE, MAE, SSIM, and PSNR were 13.26%, 3.59%, 0.891, and 26.82, respectively, in the independent test cohort. ICC for SUVmax and SUVmean were 0.88 and 0.89, which indicated a high correlation between original and AI-generated quantitative imaging markers. Lesion location, density (Hounsfield units), and lesion uptake were all shown to impact relative error in generated SUV metrics (all p < 0.05). The Pix-2-Pix GAN model for generating AC-PET demonstrates SUV metrics that highly correlate with original images. AI-generated PET images show clinical potential for reducing the need for CT scans for attenuation correction while preserving quantitative markers and image quality.

Feasibility of high-frequency ultrasound for seminiferous tubule assessment and correlation of B-mode imaging with pathological findings in the testis in azoospermia.

To determine the feasibility of high-frequency ultrasound (HFUS) for assessing seminiferous tubules and to understand high-resolution B-mode images of the testes in cases of azoospermia. We verified how the histopathological images of testicular biopsy specimens can be observed using HFUS images and measurement analysis of seminiferous tubules was performed to 28 testes of 14 cases with azoospermia who underwent preoperative ultrasound and microdissection testicular sperm extraction (micro-TESE). The population consisted of obstructive azoospermia (OA) and non-obstructive azoospermia (NOA), including Sertoli cell-only syndrome (SCOS), and the other pathologies. Statistical verification of differences in seminiferous tubule diameters among preoperative ultrasound examination, ultrasound examination of pathological specimens, and histopathological specimens. We also examined the imagingpathology correlation via a case series presentation, aiming to identify imaging markers of testicular pathology and determine the possibility of predicting each condition. A comparison between HFUS images and histopathology from the same biopsy specimens suggested that ultrasonography could be seen as stereoscopic images due to its significantly greater slice thickness. The diameters of tubules were generally larger in pathological tissues as compared to ultrasonographic findings in OA and SCOS, but not in the other conditions. Comparisons provided insights into the predictability of SCOS and revealed imaging findings such as gaps between tubules and decreased diameter reflective of testicular damage. Seminiferous tubules can be observed however the diameter of seminiferous tubules varies in imaging and histopathology depending on the pathology. Imaging findings that reflect testicular damage and the predictability of SCOS were revealed in this study, but further verification is required.

2-[18F]FDG PET imaging biomarkers for clinical and metabolic assessment in ectopic cushing syndrome. increased spleen FDG uptake as a helpful parameter to predict the presence of metastases - a pilot study

2-[18F]FDG PET imaging biomarkers for clinical and metabolic assessment in ectopic cushing syndrome. increased spleen FDG uptake as a helpful parameter to predict the presence of metastases - a pilot study

Aberrant cortical morphology patterns are associated with cognitive impairment in patients with chronic heart failure.

A mounting body of evidences suggests that patients with chronic heart failure (HF) frequently experience cognitive impairments, but the neuroanatomical mechanism underlying these impairments remains elusive. In this retrospective study, 49 chronic HF patients and 49 healthy controls (HCs) underwent brain structural MRI scans and cognitive assessments. Cortical morphology index (cortical thickness, complexity, sulcal depth and gyrification) were evaluated. Correlations between cortical morphology and cognitive scores and clinical variables were explored. Logistic regression analysis was employed to identify risk factors for predicting 3-year major adverse cardiovascular events. Compared with HCs, patients with chronic HF exhibited decreased cognitive scores (p < .001) and decreased cortical thickness, sulcal depth and gyrification in brain regions involved cognition, sensorimotor, autonomic nervous system (family-wise error correction, all p values <.05). Notably, HF duration and New York Heart Association (NYHA) demonstrated negative correlations with abnormal cortex morphology, particularly HF duration and thickness in left precentral gyrus (r = -.387, p = .006). Cortical morphology characteristics exhibited positive associations with global cognition, particularly cortical thickness in left pars opercularis (r= .476, p< .001). NYHA class is an independent risk factor for adverse outcome (p = .001). The observed correlation between abnormal cortical morphology and global cognition suggested that cortical morphology may serve as a promising imaging biomarker and provide insights into neuroanatomical underpinnings of cognitive impairment in patients with chronic HF.

Coronary Computed Tomography Angiography-Derived Modified Duke Index Is Associated with Peri-Coronary Fat Attenuation Index and Predicts Severity of Coronary Inflammation

Background and Objectives: The modified Duke index derived from coronary computed tomography angiography (CCTA) was designed to predict cardiovascular outcomes based on the severity of coronary stenosis. However, it does not take into consideration the presence or severity of peri-coronary inflammation. The peri-coronary fat attenuation index (FAI) is a novel imaging marker determined by CCTA which reflects the degree of inflammation in the coronary tree in patients with coronary artery disease. To assess the association between the modified Duke index assessed by CCTA, cardiovascular risk factors, and peri-coronary inflammation in the coronary arteries of patients with coronary artery disease. Materials and Methods: One hundred seventy-two patients who underwent CCTA for typical angina were assigned into two groups based on the modified Duke index: group 1—patients with low index, ≤3 (n = 107), and group 2—patients with high index, &gt;3 (n = 65). Demographic, clinical, and CCTA data were collected for all patients, and FAI analysis of coronary inflammation was performed. Results: Patients with increased values of the modified Duke index were significantly older compared to those with a low index (61.83 ± 9.89 vs. 64.78 ± 8.9; p = 0.002). No differences were found between the two groups in terms of gender distribution, hypertension, hypercholesterolemia, or smoking history (all p &gt; 0.5). The FAI score was significantly higher in patients from group 2, who presented a significantly higher score of inflammation compared to the patients in group 1, especially at the level of the right coronary artery (FAI score, 20.85 ± 15.80 vs. 14.61 ± 16.66; p = 0.01 for the right coronary artery, 13.85 ± 8.04 vs. 10.91 ± 6.5; p = 0.01 for the circumflex artery, 13.26 ± 10.18 vs. 11.37 ± 8.84; p = 0.2 for the left anterior descending artery). CaRi-Heart® analysis identified a significantly higher risk of future events among patients with a high modified Duke index (34.84% ± 25.86% vs. 16.87% ± 15.80%; p &lt; 0.0001). ROC analysis identified a cut-off value of 12.1% of the CaRi-Heart® risk score for predicting a high severity of coronary lesions, with an AUC of 0.69. Conclusions: The CT-derived modified Duke index correlates well with local perilesional inflammation as assessed using the FAI score at different levels of the coronary circulation.