Computed Tomography Magnetic Resonance Imaging Research Articles

Retrospective analysis of efficacy of the National Emergency X-Radiography Utilization Study low-risk criteria and the Canadian cervical spine rules for cervical spine trauma

Background: With increasing road traffic accidents, cervical spine injuries are a major health hazard in the developed as well as the developing world. Over the years, the National Emergency X-radiography Utilization Study (NEXUS) low-risk criteria and the Canadian cervical spine rules (CCRs) have acted as primary guidelines in emergency departments around the world to decide on the need for cervical spine X-ray in emergency settings. The aim of this study was to retrospectively analyze the efficiency of both the NEXUS low-risk criteria and CCR in confirming positive cervical spine injuries in emergency department settings. Aims and Objectives: The aim was to retrospectively analyze the efficiency of both the NEXUS low-risk criteria and CCR in confirming positive cervical spine injuries. Methods: A retrospective study involving 631 patients for 4 years aged above 18 years, who underwent a cervical spine X-ray from June 2018 to June 2022, were included in the study. From the eligible case records, the data pertaining to the NEXUS low-risk criteria and CCR were recorded. Along with this, the final diagnosis regarding the cervical spine injury, confirmed by subsequent computed tomography (CT) scan or magnetic resonance imaging (MRI), was also recorded. Results: The NEXUS low-risk criteria and CCR were met in 92.7% and 98.6% of the patients, respectively. The cervical spine X-rays were normal in 87.8% of the patients, fractures were recorded in 9.5% of the patients, and in 2.7% of the patients, doubtful lesions were present, which needed additional investigations in the form of CT scan or MRI or both. Conclusion: Both the Nexus and CCR guidelines act as a good guiding light in deciding about the need for the cervical spine X-ray in the emergency setup. Both guidelines are effective in ruling out cervical spine injuries in the majority of cases.

Analysis of Deep Learning Techniques for Brain Tumour Classification from CT & MRI Images

Brain tumour detection in an initialpoint is a critical step to saving human life. Computed Tomography (CT) and Magnetic Resonance Image (MRI) provide very detailed information about brain tumour tissues. So the segmentation of tumour region is possible from pancreatic CT and brain MRI. CT and MRI is a non-invasive technique and it does not produce any harmful radiation to the patient. The patient suspected of tumour undergoes radiological evaluation such that the area, location and grade of the tumour can be predicted from the CT and MRI analysis. This critical information helps the doctors to decide about further treatment like chemotherapy, surgery, or radiation. The diagnosis requires an accurate and very fast segmentation and classification of CT and MRI images. But nowadays radiologists are doing this task manually and it is a tedious and time-consuming procedure. Also, there is a chance of variation in the result from one expert to another. Here comes the significance of automatic segmentation and classification of tumour types with the help of computers.The proposed work aims to develop an efficient system that can detect pancreatic and brain tumour and can classify the pancreatic CT and brain MRI into normal, benign or malignant. This work can be categorized into two approaches. Thus the dataset prepared for this research work contains CT and MRI images.The first approach proposes traditional machine learning technologies to achieve the goal. Image pre-processing, feature extraction, segmentation and classification are the various steps of the traditional machine learning method. A detailed investigation is performed through various feature extraction techniques and classification techniques for pancreatic (CT) and brain MRI. Discrete Wavelet Transform (DWT) feature, Grey Level Co-occurrence Matrix (GLCM) feature, Gabor feature, Tamura features and Edge Orientation Histogram (EOH) features and their combinations are used for the extraction of CT and MRI features. Benign tumours are non-cancerous, but malignant tumours are cancerous. In the first approach, the Support Vector Machine (SVM) is the main classifier used for pancreatic CT and brain MRI classification as normal, benign or malignant.In this technology, a huge amount of data and machines with high computational capabilities like Graphic Processing Unit (GPU) are available. Thus the second approach of this paper is to exploit all these available resources to produce accurate results. In this part, deep learning, the latest fast growing technology introduced in 2015 is used for the classification of brain MRI. A Deep Convolutional Neural Networks (DCNN) model is proposed to perform the classification task efficiently. The CNN results are compared with the results of a simple neural network classifier. This method provides accurate and it shows that deep learning based classification outperforms traditional machine learning techniques which produce an accurate result only. This research work again concentrates on the Transfer Learning (TL) methods to classify pancreatic CT and brain MRI.

Wavelet Decomposition and Feedforward Neural Network for Classification of Acute Ischemic Stroke based on Electroencephalography

Stroke is one of the leading causes of death in Indonesia. From 2013 to 2018, the prevalence of stroke increased from 7% to 10.9%. There are two types of strokes, namely Hemorrhagic and Acutte Ischemic Stroke (AIS) with the majority of it being AIS. Early detection and diagnosis are essential in stroke as it is a life-threatening disease, and the stroke treatment is based on its type. Currently, the gold imaging standards in stroke diagnosis are Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI). However, the mentioned services for stroke diagnosis are primarily available in hospitals classified as “class A” (general hospitals with extensive facilities and medical services). Compared to CT scans and MRI, electroencephalography (EEG) is a cost-friendly, non-invasive device studied for various brain-related diseases. This study aimed to determine the optimal epoch length to classify four stroke classes (healthy, minor, moderate, and severe) during resting condition for a machine learning-based AIS computer-aided diagnostics system. 32-channel EEG, CT scan, and NIHSS Scores were the obtained data. The features were delta-theta to alpha-beta ratio (DTABR), delta to alpha ratio (DAR), relative power ratio (RPR), and asymmetry, which were extracted using wavelet decomposition technique. The epoch length was varied by 1s, 2s, 10s, 30s, 60s, and 120s. The severity of stroke were classified using a feedforward neural network. The best performance was obtained at the 60-second epoch length with 89% accuracy using 15 hidden layers. This EEG-based diagnostic system would be expected to be implemented in “class C” hospitals, where only essential medical services and facilities are available, usually in rural areas.

Comparison of MRI and CT-based radiomics for preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma.

The preoperative prediction of lymph node metastasis (LNM) in pancreatic ductal adenocarcinoma (PDAC) is essential in prognosis and treatment strategy formulation. To compare the performance of computed tomography (CT) and magnetic resonance imaging (MRI) radiomics models for the preoperative prediction of LNM in PDAC. In total, 160 consecutive patients with PDAC were retrospectively included, who were divided into the training and validation sets (ratio of 8:2). Two radiologists evaluated LNM basing on morphological abnormalities. Radiomics features were extracted from T2-weighted imaging, T1-weighted imaging, and multiphase contrast enhanced MRI and multiphase CT, respectively. Overall, 1184 radiomics features were extracted from each volume of interest drawn. Only features with an intraclass correlation coefficient ≥0.75 were included. Three sequential feature selection steps-variance threshold, variance thresholding and least absolute shrinkage selection operator-were repeated 20 times with fivefold cross-validation in the training set. Two radiomics models based on multiphase CT and multiparametric MRI were built with the five most frequent features. Model performance was evaluated using the area under the curve (AUC) values. Multiparametric MRI radiomics model achieved improved AUCs (0.791 and 0.786 in the training and validation sets, respectively) than that of the CT radiomics model (0.672 and 0.655 in the training and validation sets, respectively) and of the radiologists' assessment (0.600-0.613 and 0.560-0.587 in the training and validation sets, respectively). Multiparametric MRI radiomics model may serve as a potential tool for preoperatively evaluating LNM in PDAC and had superior predictive performance to multiphase CT-based model and radiologists' assessment.

Whether individualized dose escalation should be recommended for lymph nodes with different sizes in the definitive radiotherapy of cervical cancer?

Background and purposeDose escalation for positive node maybe improve the regional control of patients with node-positive cervical cancer, but the optimal dose for nodes of different sizes remains controversial. The purpose of this study was to explore the individualized dose escalation for lymph nodes (LNs) with different sizes in the definitive radiotherapy of cervical cancer.MethodsA total of 1002 cervical cancer patients with the International Federation of Gynecology and Obstetrics (FIGO 2009) stage IB1–IVA, who were treated by definitively radiotherapy between September 2013 and December 2016 were enrolled. All LNs identified by computed tomography/magnetic resonance imaging (CT/MRI) were assigned into three groups according to the short diameters of < 1 cm, 1–2 cm or ≥ 2 cm at pretreatment.ResultsIn total, 580 patients with 1310 LNs were detected. The nodal control rate in groups of LNs < 1 cm, 1–2 cm and ≥ 2 cm was 99.4%, 96%, and 75.9%, respectively (P = 0.000). Among LNs < 1 cm, the control, overall survival (OS) and progression-free survival (PFS) rates did not significantly differ among three dose-based groups (≤ 50.4 Gy, 50.4–60 Gy, > 60 Gy) (control rate, 99.4% vs. 99.3% vs. 100%, P = 0.647) (5-year OS, 76.2% vs. 79% vs. 81.6%, P = 0.682) (5-year PFS, 74.1% vs. 73.9% vs. 78.9% P = 0.713). Among LNs of 1–2 cm, the control and PFS rates were significantly higher in the group of dose ≥ 55 Gy than the group of dose < 55 Gy (control rate, 98% vs. 93.6%, P = 0.028) (5-year PFS, 69.6% vs. 56.7%, P = 0.025). However, this did not cause a significant difference for 5-year OS rate (72.6% vs. 68.3%, P = 0.5). Among LNs ≥ 2 cm, the control, OS, and PFS rates were higher in the group of dose ≥ 55 Gy than the group of dose < 55 Gy, while no significant difference was found (control rate, 82.1% vs. 63.2%, P = 0.107) (5-year OS, 60.6% vs. 37.5%, P = 0.141) (5-year PFS, 51.5% vs.37.5%, P = 0.232).ConclusionsRadiation dose escalation is not necessary for LNs < 1 cm, and dose escalation of 55 Gy is enough for LNs of 1–2 cm.

Massive Single Lesion in a Patient With Sickle Cell Disease

Massive Single Lesion in a Patient With Sickle Cell Disease

PO071 / #863 THE ACCURACY OF DIRECT TARGETING USING FUSION OF MR AND CT IMAGING FOR DEEP BRAIN STIMULATION OF THE SUBTHALAMIC NUCLEUS IN PATIENTS WITH PARKINSON'S DISEASE: E-POSTER VIEWING

In 33 consecutive patients with Parkinson's disease (PD) undergoing awake deep brain stimulation (DBS) without microelectrode recording (MER), we assessed and validated the precision and accuracy of direct targeting of the subthalamic nucleus (STN) using preoperative magnetic resonance imaging (MRI) and stereotactic computed tomography (CT) image fusion combined with immediate postoperative stereotactic CT and postoperative MRI, and we report on the side effects and clinical results up to 6 months' follow-up.

Differentiating Primary Tumors for Brain Metastasis with Integrated Radiomics from Multiple Imaging Modalities

Objectives To differentiate the primary site of brain metastases (BMs) is of high clinical value for the successful management of patients with BM. The purpose of this study is to investigate a combined radiomics model with computer tomography (CT) and magnetic resonance imaging (MRI) images in differentiating BMs originated from lung and breast cancer. Methods Pretreatment cerebral contrast enhanced CT and T1-weighted MRI images of 78 patients with 179 BMs from primary lung and breast cancer were retrospectively analyzed. Radiomic features were extracted from contoured BM lesions and selected using the Mann–Whitney U test and the least absolute shrinkage and selection operator (LASSO) logistic regression. Binary logistic regression (BLR) and support vector machine (SVM) models were built and evaluated based on selected radiomic features from CT alone, MRI alone, and combined images to differentiate BMs originated from lung and breast cancer. Results A total of 10 and 6 optimal radiomic features were screened out of 1288 CT and 1197 MRI features, respectively. The mean area under the curves (AUCs) of the BLR and SVM models using fivefolds cross-validation were 0.703 vs. 0.751, 0.718 vs. 0.754, and 0.781 vs. 0.803 in the training dataset and 0.708 vs. 0.763, 0.715 vs. 0.717, and 0.771 vs. 0.805 in the testing dataset for models with CT alone, MRI alone, and combined CT and MRI radiomic features, respectively. Conclusions Radiomics model based on combined CT and MRI features is feasible and accurate in the differentiation of the primary site of BMs from lung and breast cancer.

Neonatal cardiorespiratory imaging-a multimodality state-of-the-art review.

Advanced cardiorespiratory imaging of the chest with ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI) plays an important role in diagnosing respiratory and cardiac conditions in neonates when radiography and echocardiography alone are not sufficient. This pictorial essay highlights the particularities, clinical indications and technical aspects of applying chest US, cardiac CT and cardiorespiratory MRI techniques specifically to neonates, summarising the first session of the European Society of Paediatric Radiology's cardiothoracic task force.

Tumor predisposition syndromes and nephroblastoma : Early diagnosis with imaging

The Beckwith-Wiedemann spectrum (BWSp) as well as the WT1-related syndromes, Denys-Drash syndrome (DDS) and WAGR spectrum (Wilms tumor, Aniridia, genitourinary anomalies and arange of developmental delays) are tumor predisposition syndromes (TPS) of Wilms tumor (WT). Patients with associated TPS are at higher risk of developing chronic kidney disease and bilateral and metachronous tumors as well as nephrogenic rests. Standard imaging diagnostics for WT include renal ultrasound and magnetic resonance imaging (MRI). In the current renal tumor studies Umbrella SIOP-RTSG 2016 and Randomet 2017, thoracic computed tomography (CT) is also recommended as standard. Positron emission tomography (PET)-CT and whole-body MRI, on the other hand, are not part of routine diagnostics. In recent publications, renal ultrasound is recommended every 3months until the age of 7years in cases of clinical suspicion or molecularly proven TPS. Patients with TPS and regular renal ultrasounds have smaller tumor volumes and lower tumor stages at WT diagnosis than patients without such ascreening. This allows areduction of therapy intensity and facilitates the performance of nephron sparing surgery, which is prognostically relevant especially in bilateral WT. Early diagnosis of WT in the context of TPS ensures the greatest possible preservation of healthy and functional renal tissue. Standardized screening by regular renal ultrasounds should therefore be firmly established in clinical practice. The initial diagnosis of TPS is clinical and requires askilled and attentive examiner in the presence of sometimes subtle clinical manifestations, especially in the case of BWSp. Clinical diagnosis should be followed by genetic testing, which should then be followed by sonographic screening.

A Phase Ib Dose-finding Study of Panobinostat and Ruxolitinib in Myelofibrosis.

A Phase Ib Dose-finding Study of Panobinostat and Ruxolitinib in Myelofibrosis.

Comparison of Outcomes of Ischemic Stroke Initially Imaged With Cranial Computed Tomography Alone vs Computed Tomography Plus Magnetic Resonance Imaging

Patients with acute ischemic stroke often undergo magnetic resonance imaging (MRI) in addition to computed tomography (CT), but its association with clinical outcomes is uncertain. To assess whether clinical outcomes of patients with acute ischemic stroke with initial CT alone were noninferior to those with additional MRI. A retrospective observational propensity score-matched cohort study of clinical outcomes at discharge and 1 year for patients hospitalized with acute ischemic stroke was conducted at an academic medical center between January 2015 and December 2017. Data collection from an electronic medical record system performed from May 2020 through January 2022 was not completely blinded. Noninferiority margins were based on the designs of previous randomized clinical trials of ischemic stroke treatments. Statistical analysis was performed in January 2022. Participants were adults hospitalized with acute ischemic stroke with admission diagnosis based on CT. Exclusion criteria were primarily missing data. From 508 eligible patients, all 123 cases with additional MRI were propensity-score matched to 123 controls without. MRI after initial diagnosis. Death or dependence at hospital discharge (modified Rankin Scale score of 3-6) and stroke or death occurring in survivors within 1 year after discharge. Among 246 participants, the median age was 68 years (IQR, 58-78.8 years) and 131 (53.0%) were men. Death or dependence at discharge occurred more often in patients with additional MRI (59 of 123 [48.0%]) than in those with CT alone (52 of 123 [42.3%]; absolute difference, 5.7%; 95% CI, -6.7% to 18.1%), meeting the -7.50% criterion for noninferiority. Stroke or death within 1 year after discharge determined for 225 of 235 (96%) survivors occurred more often in patients with additional MRI (22 of 113 [19.5%]) than in those with CT alone (14 of 112 [12.5%]; relative risk, 1.14; 95% CI, 0.86-1.50), meeting the 0.725 relative risk criterion for noninferiority. This propensity score-matched cohort study of patients hospitalized with acute ischemic stroke found that a diagnostic imaging strategy of initial CT alone was noninferior to initial CT plus additional MRI with regard to clinical outcomes at discharge and at 1 year. Further research is needed to determine which patients hospitalized with acute ischemic stroke benefit from MRI.

Unusual Neurological Manifestation of Langerhans Cell Histiocytosis in an Adult.

Langerhans Cell Histiocytosis is a rare disorder characterized by an abnormal proliferation of Langerhans cells in one or multiple organs. It rarely presents with a central vestibular involvement. We report a case of a multisystem Langerhans Cell Histiocytosis with mucosal, hepatic, and neurological involvement, presenting with dizziness and balance disorders. A 39-year-old woman with a histopathologically confirmed mucosal palatal Langerhans Cell Histiocytosis presented with a history of dizziness for a year. Vestibular examination revealed a saccadic eyes pursuit, an up beating spontaneous nystagmus, a bilateral gaze nystagmus and a prolonged positional nystagmus, in the supine roll test. Pure tone audiometry showed a slight left sensorineural hearing loss at the 8000Hz frequency. Computed tomography (CT) scan showed a bilateral maxillary sinus fullness and a peripheral osteosclerosis of the surrounding bony walls. Hepatic magnetic resonance imaging (MRI) showed a typical hepatic involvement with a hepatomegaly with countless cysts. Temporal bone CT scan and MRI were normal. Cerebral MRI showed an hyperintense nodular signal at T2 FLAIR weighted images lateral to the right pons, at the level of the left middle cerebellar peduncle and at the left mesencephalon. Balance disorders can rarely present a sign of a degenerative neurological cerebellar involvement. Such a rare manifestation can present in different neurological disorders such as Langerhans' cell Histiocytosis.

Geometric distortion assessment in 3T MR images used for treatment planning in cranial Stereotactic Radiosurgery and Radiotherapy.

Magnetic Resonance images (MRIs) are employed in brain Stereotactic Radiosurgery and Radiotherapy (SRS/SRT) for target and/or critical organ localization and delineation. However, MRIs are inherently distorted, which also impacts the accuracy of the Magnetic Resonance Imaging/Computed Tomography (MRI/CT) co-registration process. In this phantom-based study, geometric distortion is assessed in 3T T2-weighted images (T2WIs), while the efficacy of an MRI distortion correction technique is also evaluated. A homogeneous polymer gel-filled phantom was CT-imaged before being irradiated with 26 4-mm Gamma Knife shots at predefined locations (reference control points). The irradiated phantom was MRI-scanned at 3T, implementing a T2-weighted protocol suitable for SRS/SRT treatment planning. The centers of mass of all shots were identified in the 3D image space by implementing an iterative localization algorithm and served as the evaluated control points for MRI distortion detection. MRIs and CT images were spatially co-registered using a mutual information algorithm. The inverse transformation matrix was applied to the reference control points and compared with the corresponding MRI-identified ones to evaluate the overall spatial accuracy of the MRI/CT dataset. The mean image distortion correction technique was implemented, and resulting MRI-corrected control points were compared against the corresponding reference ones. For the scanning parameters used, increased MRI distortion (>1mm) was detected at areas distant from the MRI isocenter (>5cm), while median radial distortion was 0.76mm. Detected offsets were slightly higher for the MRI/CT dataset (0.92mm median distortion). The mean image distortion correction improves geometric accuracy, but residual distortion cannot be considered negligible (0.51mm median distortion). For all three datasets studied, a statistically significant positive correlation between detected spatial offsets and their distance from the MRI isocenter was revealed. This work contributes towards the wider adoption of 3T imaging in SRS/SRT treatment planning. The presented methodology can be employed in commissioning and quality assurance programmes of corresponding treatment workflows.

Predictors of Thyroid Gland Invasion in Total Laryngectomy for Advanced Laryngeal Squamous Cell Carcinoma.

Objectives: Thyroidectomy for advanced laryngeal squamous cell carcinoma (LSCC) is controversial. This study aimed to identify predictors of thyroid gland invasion in patients with LSCC and management of the thyroid gland during total laryngectomy. Patients and Methods: Clinical data and pathological characteristics of 113 patients, who underwent laryngectomy with thyroidectomy for advanced LSCC in Guangdong Provincial People's Hospital between 2009 and 2019, were retrospectively analyzed. The incidence and predictors of thyroid gland invasion were analyzed, and a new predictor was proposed using a parallel test. Results: Of 113 patients, 25.7% exhibited thyroid invasion. A new predictor that combined the lower third of thyroid cartilage invasion and thyroid gland invasion on computed tomography/magnetic resonance imaging (CT/MRI) was associated with pathological thyroid gland invasion (P = 0.001; sensitivity, 88.2%; negative predictive value, 95%). Conclusion: Thyroidectomy may be required during total laryngectomy in those with invasion of the lower third of thyroid cartilage and/or thyroid gland invasion revealed on CT/MRI instead of being performed routinely.

Factors contributing to poor outcome in COVID associated mucormycosis

&lt;p class="abstract"&gt;&lt;strong&gt;Background:&lt;/strong&gt; Mucormycosis is an uncommon but a fatal fungal infection that usually affects patients with altered immunity. Mucormycosis is proven to be a life-threatening condition. This occurred in the delta variant epidemic of coronavirus in India. This prompted us to conduct a systematic review of deaths in mucormycosis to know its temporal associations in relation to comorbidities, association with drugs being used in COVID-19 and overall characteristics of patients with its outcome.&lt;/p&gt;&lt;p class="abstract"&gt;&lt;strong&gt;Methods:&lt;/strong&gt; This retrospective study was conducted over 21 deaths out of 140 mucormycosis patients in the tertiary care centre between time period from May 2021 to July 2021. Based on the detailed history, clinical examination, endoscopic examination, blood investigations and radiological investigations, data was collected and analysed. &lt;/p&gt;&lt;p class="abstract"&gt;&lt;strong&gt;Results:&lt;/strong&gt; In the study 19 patients were post covid and 2 were COVID positive at the time of admission to the hospital. 13 patients were having random blood sugars above 300 and 8 were having below 300 mg/dl. 13 patients had diabetic ketoacidosis. The maximum C-reactive protein (CRP) values was 200 and declined on treatment. The prothrombin time international normalized ratio (PT INR) values range between 0.99 and 1.3. Serum electrolytes were found to be normal in most of the patients. In the present study, 3 patients had electrolyte imbalance not responding to treatment. According to computed tomography/magnetic resonance imaging (CT/MRI) findings,12 had pansinusitis, 3 had pansinusitis with orbital cellulitis, 5 had pansinusitis with cavernous sinus thrombosis and 1 had pansinusitis with mandibular osteomyelitis.&lt;/p&gt;&lt;p class="abstract"&gt;&lt;strong&gt;Conclusions:&lt;/strong&gt; Early diagnosis, prompt treatment of comorbidities and immediate surgical debridement prevents death in mucormycosis patients.&lt;/p&gt;

Cardiac functional imaging

During the last 20 years, cardiac imaging has drastically evolved. Positron emission tomography (PET), fast three-dimensional (3D) imaging with the latest generations of echocardiography & multi-detector computed tomography (CT), stress perfusion assessed by magnetic resonance imaging (MRI), blood flow analysis using four-dimensional (4D) flow MRI, all these techniques offer new trends for optimal noninvasive functional cardiac imaging. Dynamic functional imaging is obtained by acquiring images of the heart at different phases of the cardiac cycle, allowing assessment of cardiac motion, function, and perfusion. Between CT and Cardiac MRI (CMR), CMR has the best temporal resolution, which is suitable for functional imaging while cardiac CT provides higher spatial resolution with isotropic data that have an identical resolution in the three dimensions of the space. The latest generations of CT scanners enable whole heart assessment in one beat, offering also an acceptable temporal resolution with the possibility to display the images in a dynamic mode. Another rapidly growing technique using functional and molecular imaging for the assessment of biological and metabolic pathways is the PET using radio-labeled tracers. Meanwhile, the oldest cardiac imaging tool with doppler ultrasound technology has never stopped evolving. Echocardiography today performs 3D imaging, stress perfusion, and myocardial strain assessment, with high temporal resolution. It still is the first line and more accessible exam for the patient. These different modalities are complementary and may be even combined into PET-CT or PET-MRI. The ability to combine the functional/molecular data with anatomical images may implement a new dimension to our diagnostic tools.

Liver, kidney and spleen segmentation from CT scans and MRI with deep learning: A survey

Deep Learning approaches for automatic segmentation of organs from CT scans and MRI are providing promising results, leading towards a revolution in the radiologists’ workflow. Precise delineations of abdominal organs boundaries reveal fundamental for a variety of purposes: surgical planning, volumetric estimation (e.g. Total Kidney Volume – TKV – assessment in Autosomal Dominant Polycystic Kidney Disease – ADPKD), diagnosis and monitoring of pathologies. Fundamental imaging techniques exploited for these tasks are Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), which enable clinicians to perform 3D analyses of all Regions of Interests (ROIs). In the realm of existing methods for segmentation and classification of these zones, Convolutional Neural Networks (CNNs) are emerging as the reference approach. In the last five years an enormous research effort has been done about the possibility of applying CNNs in Medical Imaging, resulting in more than 8000 documents on Scopus and more than 80000 results on Google Scholar. The high accuracy provided by those systems cannot be denied as motivation of all obtained results, though there are still problems to be addressed with. In this survey, major article databases, as Scopus, for instance, were systematically investigated for different kinds of Deep Learning approaches in segmentation of abdominal organs with a particular focus on liver, kidney and spleen. In this work, approaches are accurately classified, both by relevance of each organ (for instance, segmentation of liver has specific properties, if compared to other organs) and by type of computational approach, as well as the architecture of the employed network. For this purpose, a case study of segmentation for each of these organs is presented.

Survival benefit associated with postoperative PET–CT before adjuvant radiotherapy or chemoradiotherapy in patients with oral squamous cell carcinoma

The aim of this study was to analyse the impact of postoperative positron emission tomography–computed tomography (PET–CT) before adjuvant treatment in oral squamous cell carcinoma (OSCC) patients. Patients with OSCC requiring adjuvant treatment following surgery were divided retrospectively into two groups based on the implementation of PET–CT. The study endpoints were disease-specific survival (DSS) and overall survival (OS). A total of 123 patients underwent PET–CT examination; 28 had abnormal images, but only seven were confirmed to be pathologically positive. A total of 145 patients underwent computed tomography/magnetic resonance imaging (CT/MRI) examination; 20 had abnormal images, but only one was confirmed to be pathologically positive. The median OS time was 5.4 years in the PET–CT group and 4.3 years in the CT/MRI group, demonstrating a significant difference (P = 0.024). Findings were similar for the median DSS time. In patients with positive PET–CT results, the median DSS was 4.3 years and median OS was 3.5 years, and in those with negative PET–CT results, the median survival time could not be calculated as fewer than 50% of patients reached these endpoints; both differences were significant (P = 0.007 and P < 0.001). Although the false-positive rate of postoperative PET–CT is high, it improves the chance of survival through early and more frequent detection of recurrence.

Embolization of Skull Base Meningiomas with Embosphere Microspheres: Factors Predicting Treatment Response and Evaluation of Complications

Preoperative embolization for intracranial meningiomas can cause tumor necrosis, reduce intraoperative blood loss, and facilitate surgery. This study aimed to evaluate the efficacy of tumor embolization using Embosphere microspheres for skull base meningiomas and analyze postembolization plain computed tomography (CT) and magnetic resonance imaging (MRI) scans to identify findings that could potentially predict treatment response. Between April 2014 and April 2020, 80 patients with skull base meningiomas presenting at our medical center underwent embolization with Embosphere microspheres. The effects of tumor embolization were evaluated through a comparison of postembolization plain CT and contrast-enhanced MRI. A total of 143 vessels (102 of 108 external carotid artery branches and 41 of 65 internal carotid artery branches) from 80 skull base meningiomas were embolized with Embosphere microspheres. Microspheres 100-300 μm in size were used in 2 cases, microspheres 300-500 μm in size were used in 12 cases, and microspheres 500-700 μm in size were used in 66 cases. Postembolization contrast-enhanced MRI showed reductions in enhancing lesions within the tumor in 55 of 80 cases. Postembolization plain CT scans showed high-density lesions within the tumor in 41 of 55 cases. Thus, reductions in enhancing lesions on postembolization contrast-enhanced MRI were statistically significantly associated with the presence of high-density lesions on postembolization plain CT (P < 0.001). Embolization-related neurological complications occurred in 3 cases. Embosphere microspheres are user friendly and effective embolic materials for the embolization of skull base meningiomas. Postembolization contrast-enhanced MRI and plain CT findings may be useful for evaluating the effects of tumor embolization.