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1.
Nucl Med Mol Imaging ; 58(2): 86-91, 2024 Apr.
Article in English | MEDLINE | ID: mdl-38510819

ABSTRACT

Transarterial radioembolization using yttrium-90 (90Y) therapy has become a standard modality of treatment for primary and metastatic liver malignancies due to its high efficacy rate and relatively low risk of adverse effects compared to other forms of locoregional and systemic therapies. Non-target distribution of radio embolic beads and adjacent structure radiation are the two most common adverse effects. However, these are rarely encountered due to thorough imaging and mapping studies prior to 90Y therapy. We present the case of a 66-year-old male who developed a radiation-induced gastric ulcer following 90Y therapy with negative pre-procedural imaging and mapping who was retrospectively found to have an accessory artery from the left hepatic artery to the gastric antrum.

3.
Neuroimaging Clin N Am ; 32(1): 133-144, 2022 Feb.
Article in English | MEDLINE | ID: mdl-34809834

ABSTRACT

Advances in MR and computed tomography (CT) techniques have resulted in greater fidelity in the assessment of treatment response and residual tumor on one hand and the assessment of recurrent head and neck malignancies on the other hand. The advances in MR techniques primarily are related to diffusion and perfusion imaging which rely on the intrinsic architecture of the tissues and organ systems. The techniques exploit the density of the cellular architecture; and the vascularity of benign and malignant lesions which in turn affect the changes in the passage of contrast through the vascular bed. Dual-energy CT and CT perfusion are the major advances in CT techniques that have found significant applications in the assessment of treatment response and tumor recurrence.


Subject(s)
Head and Neck Neoplasms , Neoplasm Recurrence, Local , Head and Neck Neoplasms/diagnostic imaging , Head and Neck Neoplasms/therapy , Humans , Magnetic Resonance Imaging , Neck , Neoplasm Recurrence, Local/diagnostic imaging , Tomography, X-Ray Computed
4.
Radiol Case Rep ; 16(8): 2299-2305, 2021 Aug.
Article in English | MEDLINE | ID: mdl-34194594

ABSTRACT

Ollier disease is a rare condition presenting with enchondromas in an irregular distribution within the medullary cavity of bones. The disease is well known for sarcomatous transformation to chondrosarcomas. It also increases the risk of other malignancies like leukemia, ovarian tumors, and glial tumors. Central nervous system malignancies associated with Ollier disease are thought to arise by somatic IDH mosaicism with their atypical features of distribution, multifocality, and age of onset. We present a case with imaging consistent with diffuse midline glioma in a patient with Ollier disease. We conclude with a brief review of the literature on Ollier Disease with a focus on central nervous system malignancies, tumorigenesis and pathophysiology.

5.
Sci Rep ; 10(1): 20331, 2020 11 23.
Article in English | MEDLINE | ID: mdl-33230285

ABSTRACT

Differentiating pseudoprogression from true tumor progression has become a significant challenge in follow-up of diffuse infiltrating gliomas, particularly high grade, which leads to a potential treatment delay for patients with early glioma recurrence. In this study, we proposed to use a multiparametric MRI data as a sequence input for the convolutional neural network with the recurrent neural network based deep learning structure to discriminate between pseudoprogression and true tumor progression. In this study, 43 biopsy-proven patient data identified as diffuse infiltrating glioma patients whose disease progressed/recurred were used. The dataset consists of five original MRI sequences; pre-contrast T1-weighted, post-contrast T1-weighted, T2-weighted, FLAIR, and ADC images as well as two engineered sequences; T1post-T1pre and T2-FLAIR. Next, we used three CNN-LSTM models with a different set of sequences as input sequences to pass through CNN-LSTM layers. We performed threefold cross-validation in the training dataset and generated the boxplot, accuracy, and ROC curve, AUC from each trained model with the test dataset to evaluate models. The mean accuracy for VGG16 models ranged from 0.44 to 0.60 and the mean AUC ranged from 0.47 to 0.59. For CNN-LSTM model, the mean accuracy ranged from 0.62 to 0.75 and the mean AUC ranged from 0.64 to 0.81. The performance of the proposed CNN-LSTM with multiparametric sequence data was found to outperform the popular convolutional CNN with a single MRI sequence. In conclusion, incorporating all available MRI sequences into a sequence input for a CNN-LSTM model improved diagnostic performance for discriminating between pseudoprogression and true tumor progression.


Subject(s)
Astrocytoma/diagnostic imaging , Brain Neoplasms/diagnostic imaging , Deep Learning , Disease Progression , Multiparametric Magnetic Resonance Imaging/methods , Oligodendroglioma/diagnostic imaging , Adult , Aged , Area Under Curve , Astrocytoma/pathology , Biopsy , Brain Neoplasms/pathology , Data Accuracy , Feasibility Studies , Female , Follow-Up Studies , Humans , Male , Middle Aged , Neoplasm Recurrence, Local , Oligodendroglioma/pathology , ROC Curve , Retrospective Studies
6.
Insights Imaging ; 10(1): 125, 2019 Dec 21.
Article in English | MEDLINE | ID: mdl-31865450

ABSTRACT

OBJECTIVE: To investigate the presence of gender disparity in academic involvement during radiology residency and to identify and characterize any gender differences in perceived barriers for conducting research. METHODS: An international call for participation in an online survey was promoted via social media and through multiple international and national radiological societies. A 35-question survey invited radiology trainees worldwide to answer questions regarding exposure and barriers to academic radiology during their training. Gender differences in response proportions were analyzed using either Fisher's exact or chi-squared tests. RESULTS: Eight hundred fifty-eight participants (438 men, 420 women) from Europe (432), Asia (241), North and South America (144), Africa (37), and Oceania (4) completed the survey. Fewer women radiology residents were involved in research during residency (44.3%, 186/420 vs 59.4%, 260/438; p ≤ 0.0001) and had fewer published original articles (27.9%, 117/420 vs. 40.2%, 176/438; p = 0.001). Women were more likely to declare gender as a barrier to research (24.3%, 102/420 vs. 6.8%, 30/438; p < 0.0001) and lacked mentorship/support from faculty (65%, 273/420 vs. 55.7%, 244/438; p = 0.0055). Men were more likely to declare a lack of time (60.3%, 264/438 vs. 50.7%, 213/420; p = 0.0049) and lack of personal interest (21%, 92/438 vs. 13.6%, 57/420, p = 0.0041) in conducting research. CONCLUSION: Fewer women were involved in academic activities during radiology residency, resulting in fewer original published studies compared to their men counterparts. This is indicative of an inherent gender imbalance. Lack of mentorship reported by women radiologists was a main barrier to research.

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