Effect of Slab Thickness on the Detection of Pulmonary Nodules by Use of CT Maximum and Minimum Intensity Projection

A novel predictor of ischemic complications in the treatment of ruptured middle cerebral artery aneurysms: Neck-branching angle

Objective

The risk factors of procedural cerebral ischemia (CI) in ruptured middle cerebral artery (MCA) aneurysms are unclear. This study proposed the neck-branching angle (NBA), a simple quantitative indicator of the aneurysm neck and branch vessels, and analyzed its usefulness as a predictor of procedural CI in ruptured MCA aneurysms.

Methods

We retrospectively analyzed 128 patients with ruptured saccular MCA aneurysms who underwent surgical or endovascular treatment between January 2014 and June 2021. We defined the NBA as the angle formed by the MCA aneurysm neck and M2 superior or inferior branch vessel line. The superior and inferior NBA were measured on admission via three-dimensional computed tomography angiography on admission. We divided the patients into clipping (106 patients) and coiling (22 patients) groups according to the treatment. Risk factors associated with procedural CI were analyzed in each group.

Results

Both groups showed that an enlarged superior NBA was a significant risk factor for procedural CI (clipping, P < 0.0005; coiling group, P = 0.007). The receiver operating characteristic curve showed the closed thresholds of the superior NBA with procedural CI in both groups (clipping group, 128.5°, sensitivity and specificity of 0.667 and 0.848, respectively; coiling group, 130.9°, sensitivity and specificity of 1 and 0.889, respectively).

Conclusion

The NBA can estimate the procedural risk of ruptured MCA aneurysms. In addition, an enlarged superior NBA is a risk factor for procedural CI in both clipping and coiling techniques.

Clinical usability of 3D gradient-echo-based ultrashort echo time imaging: Is it enough to facilitate diagnostic decision in real-world practice?

BACKGROUND

With recent advances in magnetic resonance imaging (MRI) technology, the practical role of lung MRI is expanding despite the inherent challenges of the thorax. The purpose of our study was to evaluate the current status of the concurrent dephasing and excitation (CODE) ultrashort echo-time sequence and the T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence in the evaluation of thoracic disease by comparing it with the gold standard computed tomography (CT).

METHODS

Twenty-four patients with lung cancer and mediastinal masses underwent both CT and MRI including T1-weighted VIBE and CODE. For CODE images, data were acquired in free breathing and end-expiratory images were reconstructed using retrospective respiratory gating. All images were evaluated through qualitative and quantitative approaches regarding various anatomical structures and lesions (nodule, mediastinal mass, emphysema, reticulation, honeycombing, bronchiectasis, pleural plaque and lymphadenopathy) inside the thorax in terms of diagnostic performance in making specific decisions.

RESULTS

Depiction of the lung parenchyma, mediastinal and pleural lesion was not significant different among the three modalities (p > 0.05). Intra-tumoral and peritumoral features of lung nodules were not significant different in the CT, VIBE or CODE images (p > 0.05). However, VIBE and CODE had significantly lower image quality and poorer depiction of airway, great vessels, and emphysema compared to CT (p < 0.05). Image quality of central airways and depiction of bronchi were significantly better in CODE than in VIBE (p < 0.001 and p = 0.005). In contrast, the depiction of the vasculature was better for VIBE than CODE images (p = 0.003). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were significant greater in VIBE than CODE except for SNRlung and SNRnodule (p < 0.05).

CONCLUSIONS

Our study showed the potential of CODE and VIBE sequences in the evaluation of localized thoracic abnormalities including solid pulmonary nodules.

Comparison of clinical outcomes between unilateral biportal endoscopic discectomy and percutaneous endoscopic interlaminar discectomy for migrated lumbar disc herniation at lower lumbar spine: a retrospective controlled study

BACKGROUND

Both Unilateral Biportal Endoscopic Discectomy (UBED) and Percutaneous Endoscopic Interlaminar Discectomy (PEID) have resulted in favorable clinical outcomes in the management of LDH. The aim of this study is to comprehensively compare the efficacy of UBED and PEID in treating migrated LDH in the lower lumbar spine, with a specific focus on high-grade migrated LDH.

METHODS

96 patients who underwent UBED (31 cases) and PEID (65 cases) procedures were enrolled in the study. All patients received a minimum follow-up period of 6 months. Clinical outcomes of the patients were assessed with incision length, operation time, total hemoglobin loss, hospital stay, intraoperative fluoroscopy times, visual analogue scale (VAS) for lower back and leg pain, Oswestry disability index (ODI), modified MacNab criteria, complications, area of lamina loss and increased intervertebral height.

RESULTS

The VAS scores for lower back and leg pain and ODI significantly decreased in both groups after the operation. Preoperatively, at 1 day, 1 month, and 6 months after the procedure, the VAS and ODI scores exhibited no significant differences between the two groups. There was no significant difference in terms of modified MacNab criteria, area of lamina loss, and increased intervertebral height. The UBED group had a longer incision length, operation time and postoperative hospital stay, and fewer intraoperative fluoroscopy times than to the PEID group. Complications were noted in both groups throughout the follow-up period, but there was no significant difference in the rate of complications. Moreover, there were no notable differences in clinical outcomes between the two groups in the high-grade migrated LDH.

CONCLUSIONS

Both UBED and PEID could achieve favorable clinical outcomes for treating migrated LDH at the lower lumbar spine. Despite the longer operative time and postoperative hospital stay associated with the UBED group, UBED remains safe and innovative for treating migrated LDH at the lower lumbar spine.

Imaging in rhabdomyosarcoma: a patient journey

Rhabdomyosarcoma, although rare, is the most frequent soft tissue sarcoma in children and adolescents. It can present as a mass at nearly any site in the body, with most common presentations in the head and neck, genitourinary tract and extremities. The optimal diagnostic approach and management of rhabdomyosarcoma require a multidisciplinary team with multimodal treatment, including chemotherapy and local therapy. Survival has improved over the last decades; however, further improvement in management is essential with current 5-year overall survival ranging from 35% to 100%, depending on disease and patient characteristics. In the full patient journey, from diagnosis, staging, management to follow-up after therapy, the paediatric radiologist and nuclear physician are essential members of the multidisciplinary team. Recently, guidelines of the European paediatric Soft tissue sarcoma Study Group, the Cooperative Weichteilsarkom Studiengruppe and the Oncology Task Force of the European Society of Paediatric Radiology (ESPR), in an ongoing collaboration with the International Soft-Tissue Sarcoma Database Consortium, provided guidance for high-quality imaging. In this educational paper, given as a lecture during the 2022 postgraduate ESPR course, the multi-disciplinary team of our national paediatric oncology centre presents the journey of two patients with rhabdomyosarcoma and discusses the impact on and considerations for the clinical (paediatric) radiologist and nuclear physician. The key learning points of the guidelines and their implementation in clinical practice are highlighted and up-to-date insights provided for all aspects from clinical suspicion of rhabdomyosarcoma and its differential diagnosis, to biopsy, staging, risk stratification, treatment response assessment and follow-up.

Computer-Aided Detection of Subsolid Nodules on Chest Computed Tomography: Assessment of Visualization on Vessel-Suppressed Images

OBJECTIVES

This study aimed to clarify the performance of automatic detection of subsolid nodules by commercially available software on computed tomography (CT) images of various slice thicknesses and compare it with visualization on the accompanying vessel-suppression CT (VS-CT) images.

METHODS

A total of 95 subsolid nodules from 84 CT examinations of 84 patients were included. The reconstructed CT image series of each case with 3-, 2-, and 1-mm slice thicknesses were loaded into a commercially available software application (ClearRead CT) for automatic detection of subsolid nodules and generation of VS-CT images. Automatic nodule detection sensitivity was assessed for 95 nodules on each series of images acquired at 3 slice thicknesses. Four radiologists subjectively evaluated visual assessment of the nodules on VS-CT.

RESULTS

ClearRead CT automatically detected 69.5% (66/95 nodules), 68.4% (65/95 nodules), and 70.5% (67/95 nodules) of all subsolid nodules in 3-, 2-, and 1-mm slices, respectively. The detection rate was higher for part-solid nodules than for pure ground-glass nodules at all slice thicknesses. In the visualization assessment on VS-CT, 3 nodules at each slice thickness (3.2%) were judged as invisible, while 26 of 29 (89.7%), 27 of 30 (90.0%), and 25 of 28 (89.3%) nodules, which were missed by computer-aided detection, were judged as visible in 3-, 2-, and 1-mm slices, respectively.

CONCLUSIONS

The automatic detection rate of subsolid nodules by ClearRead CT was approximately 70% at all slice thicknesses. More than 95% of subsolid nodules were visualized on VS-CT, including nodules undetected by the automated software. Computed tomography acquisition at slices thinner than 3 mm did not confer any benefits.

Anatomical Description of Loggerhead Turtle (Caretta caretta) and Green Iguana (Iguana iguana) Skull by Three-Dimensional Computed Tomography Reconstruction and Maximum Intensity Projection Images

The growing interest in reptiles has posed a challenge to veterinary clinicians due to the lack of a standardized system to perform anatomical studies similar to those used for dogs and cats. In this paper, we have attempted to describe, employing computed tomography and subsequent three-dimensional reconstructions, the normal anatomical features that comprise the skulls of two species of reptiles: the loggerhead turtle (Caretta caretta) and the green iguana (Iguana iguana). Computed tomography (CT) and subsequent image processing allowed the identification of the bony structures that comprise the head of these species. As a result, and based on previous articles, we propose the most significant anatomical differences and similarities between these species.

Solitary Pulmonary Nodule Evaluation: Pearls and Pitfalls

Lung nodules are frequently encountered while interpreting chest CTs and are challenging to detect, characterize, and manage given they can represent both benign or malignant etiologies. An understanding of features associated with malignancy and causes of interpretive pitfalls is helpful to avoid misdiagnoses. This review addresses pertinent topics related to the etiologies for missed lung nodules on radiography and CT. Additionally, CT imaging technical pitfalls and challenges in addition to issues in the evaluation of nodule morphology, attenuation, and size will be discussed. Nodule management guidelines will be addressed as well as recent investigations that further our understanding of lung nodules.

A New General Maximum Intensity Projection Technology via the Hybrid of U-Net and Radial Basis Function Neural Network

Maximum intensity projection (MIP) technology is a computer visualization method that projects three-dimensional spatial data on a visualization plane. According to the specific purposes, the specific lab thickness and direction can be selected. This technology can better show organs, such as blood vessels, arteries, veins, and bronchi and so forth, from different directions, which could bring more intuitive and comprehensive results for doctors in the diagnosis of related diseases. However, in this traditional projection technology, the details of the small projected target are not clearly visualized when the projected target is not much different from the surrounding environment, which could lead to missed diagnosis or misdiagnosis. Therefore, it is urgent to develop a new technology that can better and clearly display the angiogram. However, to the best of our knowledge, research in this area is scarce. To fill this gap in the literature, in the present study, we propose a new method based on the hybrid of convolutional neural network (CNN) and radial basis function neural network (RBFNN) to synthesize the projection image. We first adopted the U-net to obtain feature or enhanced images to be projected; subsequently, the RBF neural network performed further synthesis processing for these data; finally, the projection images were obtained. For experimental data, in order to increase the robustness of the proposed algorithm, the following three different types of datasets were adopted: the vascular projection of the brain, the bronchial projection of the lung parenchyma, and the vascular projection of the liver. In addition, radiologist evaluation and five classic metrics of image definition were implemented for effective analysis. Finally, compared to the traditional MIP technology and other structures, the use of a large number of different types of data and superior experimental results proved the versatility and robustness of the proposed method.

Comparison of Maximum Intensity Projection and Volume Rendering in Detecting Pulmonary Nodules on Multidetector Computed Tomography

Introduction Lung cancer is the most common cancer overall, and the foremost cause of cancer-related mortality. Almost all lung cancers evolve from pulmonary nodules. As multidetector CT (MDCT) scanners are now widely available, there is an increased rate of detection of pulmonary nodules. It is of utmost importance to evaluate pulmonary nodules to rule out the possibility of neoplastic diseases. With advancements in technology, there are various manual and automatic analytic software providing a wide range of post-processing techniques. Maximum intensity projection (MIP) and volume rendering (VR) techniques have been analyzed previously regarding pulmonary nodules but there is a scarcity of data in terms of low-density nodules. This study aims to delineate the comparison and supremacy of both techniques in terms of low-density nodules. Methodology The current prospective study was conducted from June 2019 to June 2020 in the Radiology Department at Dr. Ziauddin Hospital, Karachi. Chest CT scans were performed on 16 slice MDCT (Alexion 16 Multi-slice, Toshiba Medical System Corporation, Houston, TX). A consultant radiologist of six years experience and a postgraduate trainee of three years experience analyzed each patient on a workstation (Vitrea 6.2.0, Vital Images, Minnetonka, MN). SPSS 23.0 (SPSS Inc., Chicago, IL) was incorporated for data analysis. Data were expressed in the median and interquartile range (IQR). Data collected for this study were analyzed using analyzing the median difference in nodule count using Wilcoxon's signed-rank test. A p-value of <0.05 was considered significant. Results After informed consent, 236 patients were recruited for the study. MIP outperformed VR in terms of nodule detection and low-density nodules at each evaluated slab thicknesses (p<0.001). A 10-mm MIP was superior to all other techniques in terms of detection of pulmonary nodules and low-density nodules (p<0.001). MIP was also considered an easier technique as there was excellent inter-rater reliability and agreement. Conclusion This study is robust evidence regarding the supremacy of MIP. MIP outperformed VR on every slab thicknesses. The 10-mm MIP technique was superior to all others evaluated and was recorded to be an easier analyzing technique.

Deep convolutional neural networks for multiplanar lung nodule detection: Improvement in small nodule identification

PURPOSE

Early detection of lung cancer is of importance since it can increase patients' chances of survival. To detect nodules accurately during screening, radiologists would commonly take the axial, coronal, and sagittal planes into account, rather than solely the axial plane in clinical evaluation. Inspired by clinical work, the paper aims to develop an accurate deep learning framework for nodule detection by a combination of multiple planes.

METHODS

The nodule detection system is designed in two stages, multiplanar nodule candidate detection, multiscale false positive (FP) reduction. At the first stage, a deeply supervised encoder-decoder network is trained by axial, coronal, and sagittal slices for the candidate detection task. All possible nodule candidates from the three different planes are merged. To further refine results, a three-dimensional multiscale dense convolutional neural network that extracts multiscale contextual information is applied to remove non-nodules. In the public LIDC-IDRI dataset, 888 computed tomography scans with 1186 nodules accepted by at least three of four radiologists are selected to train and evaluate our proposed system via a tenfold cross-validation scheme. The free-response receiver operating characteristic curve is used for performance assessment.

RESULTS

The proposed system achieves a sensitivity of 94.2% with 1.0 FP/scan and a sensitivity of 96.0% with 2.0 FPs/scan. Although it is difficult to detect small nodules (i.e., <6 mm), our designed CAD system reaches a sensitivity of 93.4% (95.0%) of these small nodules at an overall FP rate of 1.0 (2.0) FPs/scan. At the nodule candidate detection stage, results show that the system with a multiplanar method is capable to detect more nodules compared to using a single plane.

CONCLUSION

Our approach achieves good performance not only for small nodules but also for large lesions on this dataset. This demonstrates the effectiveness of our developed CAD system for lung nodule detection.

Shades of Gray: Subsolid Nodule Considerations and Management

Subsolid nodules are common on chest CT imaging and may be either benign or malignant. Their varied features and broad differential diagnoses present management challenges. Although subsolid nodules often represent lung adenocarcinomas, other possibilities are common and influence management. Practice guidelines exist for subsolid nodule management for both incidentally and screening-detected nodules, incorporating patient and nodule characteristics. This review highlights the similarities and differences among these algorithms, with the intent of providing a resource for comparison and aid in choosing management options.

Diagnostic Accuracy of Maximum Intensity Projection in Diagnosis of Malignant Pulmonary Nodules

Introduction Pulmonary nodules are frequently encountered during chest imaging, and its evaluation is usually done by chest radiograph and computed tomography (CT) scan of chest. High resolution of multidetector CT (MDCT) has improved the nodule detection. Post processing techniques such as maximum intensity projection (MIP) can further improve the sensitivity of MDCT for nodule detection. Failure to diagnose malignancy in pulmonary nodules can delay the treatment. Therefore, the aim of this study was to determine the diagnostic accuracy of MIP in the diagnosis of malignant pulmonary nodules taking histopathology findings as gold standard. Materials and methods A retrospective cross-sectional study was conducted at Dow Institute of Radiology, Dow University of Health Sciences, from 1 December 2018 till 30 June 2019. Both male and female patients aged 18 years and above who underwent CT scan of chest with suspicion of pulmonary nodules were included. Patients already diagnosed with malignant pulmonary nodules and presenting for follow-up were excluded. Contrast-enhanced CT chest was performed on a multi-slice scanner. MIP reconstruction and evaluation was performed on the workstation. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of MIP were calculated taking histopathology findings as gold standard. Results A total of 202 patients were included in this study. The mean age of the patients was 55.87 ± 13.08 years. A total of 103 patients (51.0%) were males and 99 patients (49.0%) were females. There were 131 (64.9%) nodules with smooth margins and 71 (35.1%) nodules with irregular margins. The mean size of nodule was 3.1 ± 0.7 cm. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of MIP in diagnosing malignant pulmonary nodules were found to be 85.82%, 82.35%, 90.55%, 74.67%, and 84.65%, respectively, taking histopathology findings as gold standard. The nodules >3 cm in size had a higher sensitivity for diagnosing malignant pulmonary nodules. Smooth margin nodule had high sensitivity, specificity, and diagnostic accuracy for diagnosing malignant pulmonary nodules. Conclusion MIP images have high sensitivity, specificity, and diagnostic accuracy in the diagnosis of malignant pulmonary nodules. The utilization of MIP images can aid in the detection of malignant pulmonary nodules and help in formulating early treatment strategies for the patients. Other post processing techniques such as volume rendering and computer-aided detection can help in further improving patient care.