-
Magnetic Resonance in Medical Sciences... Jun 2024To compare the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo...
PURPOSE
To compare the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo T2WI with DLIR for evaluating pancreatic protocol.
METHODS
This retrospective study included 42 patients (mean age, 70.2 years) with pancreatic cancer who underwent gadoxetic acid-enhanced MRI. Three fat-suppressed T2WI, including conventional fast-spin echo with 6 mm thickness (FSE 6 mm), single-shot fast-spin echo with 6 mm and 3 mm thickness (SSFSE 6 mm and SSFSE 3 mm), were acquired for each patient. For quantitative analysis, the SNRs of the upper abdominal organs were calculated between images with and without DLIR. The pancreas-to-lesion contrast on DLIR images was also calculated. For qualitative analysis, two abdominal radiologists independently scored the image quality on a 5-point scale in the FSE 6 mm, SSFSE 6 mm, and SSFSE 3 mm with DLIR.
RESULTS
The SNRs significantly improved among the three T2-weighted images with DLIR compared to those without DLIR in all patients (P < 0.001). The pancreas-to-lesion contrast of SSFSE 3 mm was higher than those of the FSE 6 mm (P < 0.001) and tended to be higher than SSFSE 6 mm (P = 0.07). SSFSE 3 mm had the highest image qualities regarding pancreas edge sharpness, pancreatic duct clarity, and overall image quality, followed by SSFSE 6 mm and FSE 6 mm (P < 0.0001).
CONCLUSION
SSFSE 3 mm with DLIR demonstrated significant improvements in SNRs of the pancreas, pancreas-to-lesion contrast, and image quality more efficiently than did SSFSE 6 mm and FSE 6 mm. Thin-slice fat-suppressed single-shot T2WI with DLIR can be easily implemented for pancreatic MR protocol.
PubMed: 38910138
DOI: 10.2463/mrms.mp.2024-0017 -
Academic Radiology Jun 2024Cardiovascular CT is required for planning transcatheter aortic valve implantation (TAVI).
BACKGROUND
Cardiovascular CT is required for planning transcatheter aortic valve implantation (TAVI).
PURPOSE
To compare image quality, suitability for TAVI planning, and radiation dose of photon-counting CT (PCCT) with that of dual-source CT (DSCT).
MATERIAL AND METHODS
Retrospective study on consecutive TAVI candidates with aortic valve stenosis who underwent contrast-enhanced aorto-ilio-femoral PCCT and/or DSCT between 01/2022 and 07/2023. Signal-to-noise (SNR) and contrast-to-noise ratio (CNR) were calculated by standardized ROI analysis. Image quality and suitability for TAVI planning were assessed by four independent expert readers (two cardiac radiologists, two cardiologists) on a 5-point-scale. CT dose index (CTDI) and dose-length-product (DLP) were used to calculate effective radiation dose (eRD).
RESULTS
300 patients (136 female, median age: 81 years, IQR: 76-84) underwent 302 CT examinations, with PCCT in 202, DSCT in 100; two patients underwent both. Although SNR and CNR were significantly lower in PCCT vs. DSCT images (33.0 ± 10.5 vs. 47.3 ± 16.4 and 47.3 ± 14.8 vs. 59.3 ± 21.9, P < .001, respectively), visual image quality was higher in PCCT vs. DSCT (4.8 vs. 3.3, P < .001), with moderate overall interreader agreement among radiologists and among cardiologists (κ = 0.60, respectively). Image quality was rated as "excellent" in 160/202 (79.2%) of PCCT vs. 5/100 (5%) of DSCT cases. Readers found images suitable to depict the aortic valve hinge points and to map the femoral access path in 99% of PCCT vs. 85% of DSCT (P < 0.01), with suitability ranked significantly higher in PCCT vs. DSCT (4.8 vs. 3.3, P < .001). Mean CTDI and DLP, and thus eRD, were significantly lower for PCCT vs. DSCT (22.4 vs. 62.9; 519.4 vs. 895.5, and 8.8 ± 4.5 mSv vs. 15.3 ± 5.8 mSv; all P < .001).
CONCLUSION
PCCT improves image quality, effectively avoids non-diagnostic CT imaging for TAVI planning, and is associated with a lower radiation dose compared to state-of-the-art DSCT. Radiologists and cardiologists found PCCT images more suitable for TAVI planning.
PubMed: 38906782
DOI: 10.1016/j.acra.2024.06.014 -
Medicine Jun 2024The diagnosis of pneumoconiosis is complex and subjective, leading to inevitable variability in readings. This is especially true for inexperienced doctors. To improve... (Observational Study)
Observational Study
The diagnosis of pneumoconiosis is complex and subjective, leading to inevitable variability in readings. This is especially true for inexperienced doctors. To improve accuracy, a computer-assisted diagnosis system is used for more effective pneumoconiosis diagnoses. Three models (Resnet50, Resnet101, and DenseNet) were used for pneumoconiosis classification based on 1250 chest X-ray images. Three experienced and highly qualified physicians read the collected digital radiography images and classified them from category 0 to category III in a double-blinded manner. The results of the 3 physicians in agreement were considered the relative gold standards. Subsequently, 3 models were used to train and test these images and their performance was evaluated using multi-class classification metrics. We used kappa values and accuracy to evaluate the consistency and reliability of the optimal model with clinical typing. The results showed that ResNet101 was the optimal model among the 3 convolutional neural networks. The AUC of ResNet101 was 1.0, 0.9, 0.89, and 0.94 for detecting pneumoconiosis categories 0, I, II, and III, respectively. The micro-average and macro-average mean AUC values were 0.93 and 0.94, respectively. The accuracy and Kappa values of ResNet101 were 0.72 and 0.7111 for quadruple classification and 0.98 and 0.955 for dichotomous classification, respectively, compared with the relative standard classification of the clinic. This study develops a deep learning based model for screening and staging of pneumoconiosis is using chest radiographs. The ResNet101 model performed relatively better in classifying pneumoconiosis than radiologists. The dichotomous classification displayed outstanding performance, thereby indicating the feasibility of deep learning techniques in pneumoconiosis screening.
Topics: Humans; Pneumoconiosis; Deep Learning; Radiography, Thoracic; Male; Middle Aged; Reproducibility of Results; Female; Diagnosis, Computer-Assisted; Aged; Neural Networks, Computer
PubMed: 38905434
DOI: 10.1097/MD.0000000000038478 -
Medicine Jun 2024The aim of this study is to estimate the normal cross-sectional area and diameter of the stellate ganglion (SG) by ultrasound (US) in healthy adults. The study sample... (Observational Study)
Observational Study
The aim of this study is to estimate the normal cross-sectional area and diameter of the stellate ganglion (SG) by ultrasound (US) in healthy adults. The study sample included 80 stellate ganglia in 40 participants (15 males, 25 females), mean age 38 years, mean height 162.5 cm, mean weight 67.8 kg, mean body mass index 25.4 kg/m2. Two radiologists separately obtained US images of the bilateral SG. Each participant was scanned 3 times bilaterally to assess for intra-observer reliability. The mean diameter of the SG was 1 mm (range: 0.1-2). The mean CSA of the bilateral SG was 1.3 mm2 (range: 0.6-3.9). The SG diameter positively correlated with age. Our study demonstrates the ability of US to image the SG and estimate its normal diameter and CSA. Knowledge of how to identify and measure the SG during ultrasound-guided procedures would be expected to decrease the risk of associated complications and help establish normal reference values.
Topics: Humans; Male; Female; Adult; Stellate Ganglion; Ultrasonography; Middle Aged; Reference Values; Healthy Volunteers; Young Adult; Reproducibility of Results; Observer Variation
PubMed: 38905380
DOI: 10.1097/MD.0000000000038646 -
Cureus Jun 2024Accessory liver lobes are indeed morphological variations of the liver, representing additional lobes or smaller structures connected to the main liver mass. Beaver tail...
Accessory liver lobes are indeed morphological variations of the liver, representing additional lobes or smaller structures connected to the main liver mass. Beaver tail liver is a rare anatomic variation where the left lobe of the liver encroaches to enclose the spleen. These variants, often found by chance in patients, can create challenges in accurately distinguishing between the liver and spleen in imaging, potentially leading to misdiagnosis as splenic trauma or a subcapsular hematoma. While conducting routine dissections of the abdomen region, a variation in the size, position, and anatomical connections of the liver was noticed in a female cadaver of age 45 years. The left lobe of the liver was elongated more towards the left lateral side with some angulated narrowing after extending across the midline, encroaching the left upper quadrant of the abdomen, reaching in between the stomach and the visceral surface of the spleen, above the hilum of the spleen. The narrow end of the left lobe of the liver, placed in between the stomach and spleen, is named the hiding beaver tail liver. This variation differs from the typical beaver tail liver as well as the "kissing sign" of the liver and spleen. Unfamiliarity with such an anomaly of the liver may lead radiologists and clinicians to identify a normal anatomical variant as a pathological condition mistakenly or could confuse radiologists with fluid collections that often suggest trauma, potentially leading to fatal outcomes during invasive abdominal procedures.
PubMed: 38903980
DOI: 10.7759/cureus.62665 -
Frontiers in Medicine 2024Previous studies showed that contrast-enhanced (CE) morpho-functional magnetic resonance imaging (MRI) detects abnormalities in lung morphology and perfusion in patients...
Contrast agent-free functional magnetic resonance imaging with matrix pencil decomposition to quantify abnormalities in lung perfusion and ventilation in patients with cystic fibrosis.
BACKGROUND
Previous studies showed that contrast-enhanced (CE) morpho-functional magnetic resonance imaging (MRI) detects abnormalities in lung morphology and perfusion in patients with cystic fibrosis (CF). Novel matrix pencil decomposition MRI (MP-MRI) enables quantification of lung perfusion and ventilation without intravenous contrast agent administration.
OBJECTIVES
To compare MP-MRI with established morpho-functional MRI and spirometry in patients with CF.
METHODS
Thirty-nine clinically stable patients with CF (mean age 21.6 ± 10.7 years, range 8-45 years) prospectively underwent morpho-functional MRI including CE perfusion MRI, MP-MRI and spirometry. Two blinded chest radiologists assessed morpho-functional MRI and MP-MRI employing the validated chest MRI score. In addition, MP-MRI data were processed by automated software calculating perfusion defect percentage (QDP) and ventilation defect percentage (VDP).
RESULTS
MP perfusion score and QDP correlated strongly with the CE perfusion score (both = 0.81; < 0.01). MP ventilation score and VDP showed strong inverse correlations with percent predicted FEV1 ( = -0.75 and = -0.83; < 0.01). The comparison of visual and automated parameters showed that both MP perfusion score and QDP, and MP ventilation score and VDP were strongly correlated ( = 0.74 and = 0.78; both < 0.01). Further, the MP perfusion score and MP ventilation score, as well as QDP and VDP were strongly correlated ( = 0.88 and = 0.86; both < 0.01).
CONCLUSION
MP-MRI detects abnormalities in lung perfusion and ventilation in patients with CF without intravenous or inhaled contrast agent application, and correlates strongly with the well-established CE perfusion MRI score and spirometry. Automated analysis of MP-MRI may serve as quantitative noninvasive outcome measure for diagnostic monitoring and clinical trials.
PubMed: 38903825
DOI: 10.3389/fmed.2024.1349466 -
ArXiv Feb 2024In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging....
In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging. Current metrics, such as Conventional Natural Language Generation (NLG) and Clinical Efficacy (CE), often fall short in capturing the semantic intricacies of clinical contexts or overemphasize clinical details, undermining report clarity. To overcome these issues, our proposed method synergizes the expertise of professional radiologists with Large Language Models (LLMs), like GPT-3.5 and GPT-4. Utilizing In-Context Instruction Learning (ICIL) and Chain of Thought (CoT) reasoning, our approach aligns LLM evaluations with radiologist standards, enabling detailed comparisons between human and AI-generated reports. This is further enhanced by a Regression model that aggregates sentence evaluation scores. Experimental results show that our "Detailed GPT-4 (5-shot)" model achieves a 0.48 score, outperforming the METEOR metric by 0.19, while our "Regressed GPT-4" model shows even greater alignment with expert evaluations, exceeding the best existing metric by a 0.35 margin. Moreover, the robustness of our explanations has been validated through a thorough iterative strategy. We plan to publicly release annotations from radiology experts, setting a new standard for accuracy in future assessments. This underscores the potential of our approach in enhancing the quality assessment of AI-driven medical reports.
PubMed: 38903745
DOI: No ID Found -
ArXiv May 2024Multi-parametric MRI (mpMRI) studies are widely available in clinical practice for the diagnosis of various diseases. As the volume of mpMRI exams increases yearly,...
Multi-parametric MRI (mpMRI) studies are widely available in clinical practice for the diagnosis of various diseases. As the volume of mpMRI exams increases yearly, there are concomitant inaccuracies that exist within the DICOM header fields of these exams. This precludes the use of the header information for the arrangement of the different series as part of the radiologist's hanging protocol, and clinician oversight is needed for correction. In this pilot work, we propose an automated framework to classify the type of 8 different series in mpMRI studies. We used 1,363 studies acquired by three Siemens scanners to train a DenseNet-121 model with 5-fold cross-validation. Then, we evaluated the performance of the DenseNet-121 ensemble on a held-out test set of 313 mpMRI studies. Our method achieved an average precision of 96.6%, sensitivity of 96.6%, specificity of 99.6%, and F1 score of 96.6% for the MRI series classification task. To the best of our knowledge, we are the first to develop a method to classify the series type in mpMRI studies acquired at the level of the chest, abdomen, and pelvis. Our method has the capability for robust automation of hanging protocols in modern radiology practice.
PubMed: 38903740
DOI: No ID Found -
Cureus May 2024Cancer is often accompanied by bone metastasis, which may lead to skeletal-related events (SREs), such as pain, hypercalcemia, pathological fractures, spinal cord...
Cancer is often accompanied by bone metastasis, which may lead to skeletal-related events (SREs), such as pain, hypercalcemia, pathological fractures, spinal cord compression, orthopedic surgical intervention, and palliative radiation directed at the bone. Herein, we report the case of a 75-year-old female patient diagnosed with diffuse large B-cell lymphoma (DLBCL) with bone metastasis and a pathological fracture of the right iliac bone. The management strategy and follow-up were determined by a multidisciplinary cancer board comprising physicians, physiatrists, orthopedic surgeons, radiologists, and rehabilitation therapists. A conservative approach was chosen, incorporating a bone-modifying agent and weight-bearing restrictions for the right leg, along with rehabilitation therapy and post-discharge support. A multidisciplinary rehabilitation approach for two months enabled the patient to walk independently upon discharge. She maintains her activities of daily living (ADL) for over six months after discharge without any skeletal issues. This case highlights the effectiveness of a multidisciplinary approach in managing bone metastasis or involvement in patients with lymphoma.
PubMed: 38903364
DOI: 10.7759/cureus.60713 -
Canadian Association of Radiologists... Jun 2024In the immunocompromised setting, there are distinct radiologic findings of primary central nervous system lymphoma (PCNSL), including necrotic ring-enhancing lesions,... (Review)
Review
In the immunocompromised setting, there are distinct radiologic findings of primary central nervous system lymphoma (PCNSL), including necrotic ring-enhancing lesions, increased propensity for intralesional haemorrhage, and multiplicity. In this clinical context, advanced imaging with MR perfusion, spectroscopy, and diffusion-weighted imaging can be used to increase accuracy in the diagnosis of lymphoma over mimics such as high-grade glioma, metastases, or infection. This review summarizes the histology and pathophysiology of PCNSL in immunodeficient hosts, which provide a basis for its imaging appearances, prognosis, and treatment. This discussion is important for the general radiologist as the incidence of immunodeficiency-related PCNSL may be increasing.
PubMed: 38902978
DOI: 10.1177/08465371241259951