Publications by authors named "Ashkan A Malayeri"
Background: Cell-free DNA (cfDNA) sequence analysis to screen for fetal aneuploidy can incidentally detect maternal cancer. Additional data are needed to identify DNA-sequencing patterns and other biomarkers that can identify pregnant persons who are most likely to have cancer and to determine the best approach for follow-up.
Methods: In this ongoing study we performed cancer screening in pregnant or postpartum persons who did not perceive signs or symptoms of cancer but received unusual clinical cfDNA-sequencing results or results that were nonreportable (i.
Current surgical approaches for renal malignancies primarily rely on qualitative factors such as patient preferences, surgeon experience, and hospital capabilities. Applying a quantitative method for consistent and reliable assessment of renal lesions would significantly enhance surgical decision-making and facilitate data comparison. Nephrometry scoring (NS) systems systematically evaluate and describe renal tumors based on their anatomical features.
View Article and Find Full Text PDFPurpose: To characterize brain MR imaging findings in a cohort of 58 patients with ECD and to evaluate relationship between these findings and the BRAF pathogenic variant.
Methods: ECD patients of any gender and ethnicity, aged 2-80 years, with biopsy-confirmed ECD were eligible to enroll in this study. Two radiologists experienced in evaluating ECD CNS disease activity reviewed MRI studies.
Purpose: Succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) is a newly defined, rare subtype of renal cancer, associated with pathogenic variations in the Succinate Dehydrogenase Subunit B (SDHB) gene. Our aim is to investigate the imaging findings of SDHB-associated renal tumors, utilizing cross-sectional and FDG-PET imaging in patients with pathogenic variations in SDHB gene, to facilitate accurate tumor characterization.
Methods: Twenty SDH-deficient tumors from 16 patients with pathogenic variations in SDHB gene were retrospectively evaluated using cross-sectional and FDG-PET imaging.
Introduction: This study explores the use of the latest You Only Look Once (YOLO V7) object detection method to enhance kidney detection in medical imaging by training and testing a modified YOLO V7 on medical image formats.
Methods: Study includes 878 patients with various subtypes of renal cell carcinoma (RCC) and 206 patients with normal kidneys. A total of 5657 MRI scans for 1084 patients were retrieved.
Objectives: The aim of this study was to assess the interreader reliability and per-RCC sensitivity of high-resolution photon-counting computed tomography (PCCT) in the detection and characterization of renal masses in comparison to MRI.
Materials And Methods: This prospective study included 24 adult patients (mean age, 52 ± 14 years; 14 females) who underwent PCCT (using an investigational whole-body CT scanner) and abdominal MRI within a 3-month time interval and underwent surgical resection (partial or radical nephrectomy) with histopathology (n = 70 lesions). Of the 24 patients, 17 had a germline mutation and the remainder were sporadic cases.
Erdheim-Chester disease (ECD) is a rare histiocytic disease that affects multiple systems in the body. While it typically targets long bones, cardiovascular structures, the retroperitoneum, and the central nervous system, reports of tendon and skeletal muscle involvement are scarce. This review presents 2 cases: a case of ECD involving the left Achilles tendon and left abductor hallucis, as well as an unusual manifestation of ECD in the thigh musculature.
View Article and Find Full Text PDFArticle Synopsis
- This study investigates the use of a deep learning algorithm called YOLOv7 for automating the detection of kidney tumors on contrast-enhanced MRI scans.
- The research involved analyzing data from 326 patients with a total of 1,034 tumors, utilizing both 2D and a new 2.5D evaluation method, yielding varying performance metrics for tumor detection.
- Overall, the results indicate that YOLOv7 is a promising tool for identifying kidney cancers, with better performance observed in the 2.5D evaluation compared to traditional 2D methods.
Article Synopsis
- The study investigates the classification of growth rates in clear cell renal cell carcinoma (ccRCC) among patients with Von Hippel-Lindau (VHL) syndrome, using machine learning to predict these rates based on MRI characteristics.
- Researchers analyzed data from 55 VHL patients with 128 ccRCC tumors, separating them into 'slow-growing' and 'fast-growing' categories, utilizing two machine-learning models to assess their accuracy in predicting growth rates.
- The best-performing model showed high accuracy and predictive values, indicating that machine learning could enhance individualized monitoring and surgical planning for ccRCC in VHL patients.
Background: Pathology grading is an essential step for the treatment and evaluation of the prognosis in patients with clear cell renal cell carcinoma (ccRCC).
Purpose: To investigate the utility of texture analysis in evaluating Fuhrman grades of renal tumors in patients with Von Hippel-Lindau (VHL)-associated ccRCC, aiming to improve non-invasive diagnosis and personalized treatment.
Study Type: Retrospective analysis of a prospectively maintained cohort.
Objective: The aim of this study was to characterize the distribution of skeletal involvement in Erdheim-Chester disease (ECD) by using radiography, computed tomography (CT), F-FDG positron emission tomography/computed tomography (PET/CT), and bone scans, as well as looking for associations with the BRAF mutation.
Material And Methods: Prospective study of 50 consecutive patients with biopsy-confirmed ECD who had radiographs, CT, F-FDG PET/CT, and Tc-99m MDP bone scans. At least two experienced radiologists with expertise in the relevant imaging studies analyzed the images.
Background: The von Hippel-Lindau disease (VHL) is a hereditary cancer syndrome with multifocal, bilateral cysts and solid tumors of the kidney. Surgical management may include multiple extirpative surgeries, which ultimately results in parenchymal volume loss and subsequent renal function decline. Recent studies have utilized parenchyma volume as an estimate of renal function prior to surgery for renal cell carcinoma; however, it is not yet validated for surgically altered kidneys with multifocal masses and complex cysts such as are present in VHL.
View Article and Find Full Text PDFUnlabelled: Understanding of tumor biology and identification of effective therapies is lacking for many rare tumors. My Pediatric and Adult Rare Tumor (MyPART) network was established to engage patients, advocates, and researchers and conduct a comprehensive longitudinal Natural History Study of Rare Solid Tumors. Through remote or in-person enrollment at the NIH Clinical Center, participants with rare solid tumors ≥4 weeks old complete standardized medical and family history forms, patient reported outcomes, and provide tumor, blood and/or saliva samples.
View Article and Find Full Text PDFPurpose: Advantages of virtual monoenergetic images (VMI) have been reported for dual energy CT of the head and neck, and more recently VMIs derived from photon-counting (PCCT) angiography of the head and neck. We report image quality metrics of VMI in a PCCT angiography dataset, expanding the anatomical regions evaluated and extending observer-based qualitative methods further than previously reported.
Methods: In a prospective study, asymptomatic subjects underwent contrast enhanced PCCT of the head and neck using an investigational scanner.
(1) Background: A reduction in the diffusion capacity of the lung for carbon monoxide is a prevalent longer-term consequence of COVID-19 infection. In patients who have zero or minimal residual radiological abnormalities in the lungs, it has been debated whether the cause was mainly due to a reduced alveolar volume or involved diffuse interstitial or vascular abnormalities. (2) Methods: We performed a cross-sectional study of 45 patients with either zero or minimal residual lesions in the lungs (total volume < 7 cc) at two months to one year post COVID-19 infection.
View Article and Find Full Text PDFPurpose: Differentiation of fat-poor angiomyolipoma (fp-AMLs) from renal cell carcinoma (RCC) is often not possible from just visual interpretation of conventional cross-sectional imaging, typically requiring biopsy or surgery for diagnostic confirmation. However, radiomics has the potential to characterize renal masses without the need for invasive procedures. Here, we conducted a systematic review on the accuracy of CT radiomics in distinguishing fp-AMLs from RCCs.
View Article and Find Full Text PDFArticle Synopsis
- The main kidney cancer treatments include surgical partial nephrectomy (PN) and image-guided percutaneous thermal ablation, both of which aim to minimize damage to kidney tissue.
- Despite being effective, PN carries potential complications, like vascular injuries and urinary leaks, influenced by factors like tumor location and surgeon skill.
- In contrast, percutaneous renal ablation has emerged as a safe alternative for small tumors, offering similar outcomes to PN with fewer serious complications, while requiring radiologists to recognize imaging indicators of potential issues post-procedure.
Article Synopsis
- The study aimed to identify the clinical features and genetic basis of a familial cancer syndrome linked to lipomas, fibrofolliculomas, and kidney cancer in affected patients.
- Genomic analysis revealed a pathogenic variant in the PRDM10 gene, which is associated with a severe form of bilateral, multifocal papillary renal cell carcinoma and affects the expression of other related genes.
- The findings suggest those with specific skin manifestations and subcutaneous lipomas should be tested for PRDM10 variants, and kidney tumors in these individuals should be treated with surgical removal rather than merely monitored.
Background: von Hippel-Lindau syndrome (VHL) is an autosomal dominant hereditary syndrome with an increased predisposition of developing numerous cysts and tumors, almost exclusively clear cell renal cell carcinoma (ccRCC). Considering the lifelong surveillance in such patients to monitor the disease, patients with VHL are preferentially imaged using MRI to eliminate radiation exposure.
Purpose: Segmentation of kidney and tumor structures on MRI in VHL patients is useful in lesion characterization (e.
Article Synopsis
- Researchers developed a method using convolutional neural networks (CNN) to automatically segment clear cell renal cell carcinomas (ccRCC), cysts, and normal kidney tissue from MRI scans in patients with von Hippel-Lindau syndrome.
- The study analyzed MRI scans from 115 VHL patients, using manual segmentation to train 2D and 3D U-Net models, which were evaluated based on their performance metrics including the dice similarity coefficient (DSC).
- The 2D U-Net model showed better performance with a detection AUC of 0.88 and moderate segmentation results, indicating potential for assisting radiologists in monitoring kidney disease severity in VHL patients.
Background: Radiomics is a type of quantitative analysis that provides a more objective approach to detecting tumor subtypes using medical imaging. The goal of this paper is to conduct a comprehensive assessment of the literature on computed tomography (CT) radiomics for distinguishing renal cell carcinomas (RCCs) from oncocytoma.
Methods: From February 15th 2012 to 2022, we conducted a broad search of the current literature using the PubMed/MEDLINE, Google scholar, Cochrane Library, Embase, and Web of Science.
Purpose: Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome is associated with an aggressive form of renal cell carcinoma with high risk of metastasis, even in small primary tumors with unequivocal imaging findings. In this study, we compare the performance of ultra-high b-value diffusion-weighted imaging (DWI) sequence (b = 2000 s/mm) to standard DWI (b = 800 s/mm) sequence in identifying malignant lesions in patients with HLRCC.
Methods: Twenty-eight patients (n = 18 HLRCC patients with 22 lesions, n = 10 controls) were independently evaluated by three abdominal radiologists with different levels of experience using four combinations of MRI sequences in two separate sessions (session 1: DWI with b-800, session 2: DWI with b-2000).