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A knowledge of the complex phenomena that regulate T1 signal on Magnetic Resonance Imaging is essential in clinical practice for a more effective characterization of pathological processes. The authors review the physical basis of T1 Relaxation Time and the fundamental aspects of physics and chemistry that can influence this parameter. The main substances (water, fat, macromolecules, methemoglobin, melanin, Gadolinium, calcium) that influence T1 and the different MRI acquisition techniques that can be applied to enhance their presence in diagnostic images are then evaluated. An extensive case illustration of the different phenomena and techniques in the areas of CNS, abdomino-pelvic, and osteoarticular pathology is also proposed. CRITICAL RELEVANCE STATEMENT: T1 relaxation time is strongly influenced by numerous factors related to tissue characteristics and the presence in the context of the lesions of some specific substances. An examination of these phenomena with extensive MRI exemplification is reported. KEY POINTS: The purpose of the paper is to illustrate the chemical-physical basis of T1 Relaxation Time. MRI methods in accordance with the various clinical indications are listed. Several examples of clinical application in abdominopelvic and CNS pathology are reported.
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PURPOSE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI). MATERIALS AND METHODS: This retrospective study was conducted using a prototype algorithm that evaluated 502 NCCT head scans with ICH in context of TBI. Four board-certified radiologists evaluated in consensus the CT scans to establish the standard of reference for hemorrhage presence and type of ICH. Consequently, all CT scans were independently analyzed by the algorithm and a board-certified radiologist to assess the presence and type of ICH. Additionally, the time to diagnosis was measured for both methods. RESULTS: A total of 405/502 patients presented ICH classified in the following types: intraparenchymal (n = 172); intraventricular (n = 26); subarachnoid (n = 163); subdural (n = 178); and epidural (n = 15). The algorithm showed high diagnostic accuracy (91.24%) for the assessment of ICH with a sensitivity of 90.37% and specificity of 94.85%. To distinguish the different ICH types, the algorithm had a sensitivity of 93.47% and a specificity of 99.79%, with an accuracy of 98.54%. To detect midline shift, the algorithm had a sensitivity of 100%. In terms of processing time, the algorithm was significantly faster compared to the radiologist's time to first diagnosis (15.37 ± 1.85 vs 277 ± 14 s, p < 0.001). CONCLUSION: A novel deep learning algorithm can provide high diagnostic accuracy for the identification and classification of ICH from unenhanced CT scans, combined with short processing times. This has the potential to assist and improve radiologists' ICH assessment in NCCT scans, especially in emergency scenarios, when time efficiency is needed.
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PURPOSE: To determine the optimal window setting for virtual monoenergetic images (VMI) reconstructed from dual-layer spectral coronary computed tomography angiography (DE-CCTA) datasets. MATERIAL AND METHODS: 50 patients (30 males; mean age 61.1 ± 12.4 years who underwent DE-CCTA from May 2021 to June 2022 for suspected coronary artery disease, were retrospectively included. Image quality assessment was performed on conventional images and VMI reconstructions at 70 and 40 keV. Objective image quality was assessed using contrast-to-noise ratio (CNR). Two independent observers manually identified the best window settings (B-W/L) for VMI 70 and VMI 40 visualization. B-W/L were then normalized with aortic attenuation using linear regression analysis to obtain the optimized W/L (O-W/L) settings. Additionally, subjective image quality was evaluated using a 5-point Likert scale, and vessel diameters were measured to examine any potential impact of different W/L settings. RESULTS: VMI 40 demonstrated higher CNR values compared to conventional and VMI 70. B-W/L settings identified were 1180/280 HU for VMI 70 and 3290/900 HU for VMI 40. Subsequent linear regression analysis yielded O-W/L settings of 1155/270 HU for VMI 70 and 3230/880 HU for VMI 40. VMI 40 O-W/L received the highest scores for each parameter compared to conventional (all p < 0.0027). Using O-W/L settings for VMI 70 and VMI 40 did not result in significant differences in vessel measurements compared to conventional images. CONCLUSION: Optimization of VMI requires adjustments in W/L settings. Our results recommend W/L settings of 1155/270 HU for VMI 70 and 3230/880 HU for VMI 40.
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Computed Tomography Angiography , Coronary Angiography , Coronary Artery Disease , Humans , Male , Middle Aged , Female , Computed Tomography Angiography/methods , Retrospective Studies , Coronary Artery Disease/diagnostic imaging , Coronary Angiography/methods , Aged , Coronary Vessels/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted/methodsABSTRACT
PURPOSE: To evaluate the diagnostic performance of a dual-energy computed tomography (DECT)-based material decomposition algorithm for iodine quantification and fat fraction analysis to detect lymph node metastases in breast cancer patients. MATERIALS AND METHODS: 30 female patients (mean age, 63.12 ± 14.2 years) diagnosed with breast cancer who underwent pre-operative chest DECT were included. To establish a reference standard, the study correlated histologic repots after lymphadenectomy or confirming metastasis in previous/follow-up examinations. Iodine concentration and fat fraction were determined through region-of-interest measurements on venous DECT iodine maps. Receiver operating characteristic curve analysis was conducted to identify the optimal threshold for differentiating between metastatic and non-metastatic lymph nodes. RESULTS: A total of 168 lymph nodes were evaluated, divided into axillary (metastatic: 46, normal: 101) and intramammary (metastatic: 10, normal: 11). DECT-based fat fraction values exhibited significant differences between metastatic (9.56 ± 6.20%) and non-metastatic lymph nodes (41.52 ± 19.97%) (p < 0.0001). Absolute iodine concentrations showed no significant differences (2.25 ± 0.97 mg/mL vs. 2.08 ± 0.97 mg/mL) (p = 0.7999). The optimal fat fraction threshold for diagnosing metastatic lymph nodes was determined to be 17.75%, offering a sensitivity of 98% and a specificity of 94%. CONCLUSIONS: DECT fat fraction analysis emerges as a promising method for identifying metastatic lymph nodes, overcoming the morpho-volumetric limitations of conventional CT regarding lymph node assessment. This innovative approach holds potential for improving pre-operative lymph node evaluation in breast cancer patients, offering enhanced diagnostic accuracy.
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Background: To evaluate if coronary CT angiography (CCTA) monoenergetic reconstructions, obtained with a dual-layer spectral detector computed tomography (DLCT) system, offer improved image quality compared with 120 kVp conventional images without affecting the quantitative assessment of coronary stenoses. Methods: Fifty CCTA datasets (30 men; mean age: 61.6 ± 12.3 years) acquired with a DLCT system were reconstructed using virtual monoenergetic images (VMI) from 40 to 100 keV with 10 keV increment and compared with conventional images. An analysis of objective image quality was performed, evaluating the signal- and contrast-to-noise ratio. For the subjective assessment, two readers used a 5-point Likert scoring system to evaluate sharpness, noise, demarcation of coronary plaques, vascular contrast, and an overall score. Furthermore, coronary stenoses were analyzed for each vessel to describe the diagnostic agreement between monoenergetic images and conventional images. Results: The objective image analysis showed that all reconstructions from 70 keV to 40 keV show higher SNR (from 61.33 ± 12.46 to 154.22 ± 42.91, respectively) and CNR (from 51.45 ± 11.19 to 135.63 ± 39.38, respectively) compared with conventional images (all p < 0.001). The 40 keV monoenergetic images obtained the best average score for sharpness, vascular contrast, and for the overall impression (all with p < 0.001). The detection and grading of stenoses of the coronary arteries with conventional and monoenergetic images at 70 keV and 40 keV showed an overall excellent interobserver agreement (k= 0.81 [0.72-0.91]). Conclusions: The 40 keV virtual monoenergetic images obtained with a DLCT system allow the objective and subjective image quality of coronary CT angiography to be improved.
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BACKGROUND: Type 2 diabetes mellitus (DM) is the most common metabolic disorder in the world and an important risk factor for peripheral arterial disease (PAD). CT angiography represents the method of choice for the diagnosis, pre-operative planning, and follow-up of vascular disease. Low-energy dual-energy CT (DECT) virtual mono-energetic imaging (VMI) has been shown to improve image contrast, iodine signal, and may also lead to a reduction in contrast medium dose. In recent years, VMI has been improved with the use of a new algorithm called VMI+, able to obtain the best image contrast with the least possible image noise in low-keV reconstructions. PURPOSE: To evaluate the impact of VMI+ DECT reconstructions on quantitative and qualitative image quality in the evaluation of the lower extremity runoff. MATERIALS AND METHODS: We evaluated DECT angiography of lower extremities in patients suffering from diabetes who had undergone clinically indicated DECT examinations between January 2018 and January 2023. Images were reconstructed with standard linear blending (F_0.5) and low VMI+ series were generated from 40 to 100 keV, in an interval of 15 keV. Vascular attenuation, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for objective analysis. Subjective analysis was performed using five-point scales to evaluate image quality, image noise, and diagnostic assessability of vessel contrast. RESULTS: Our final study cohort consisted of 77 patients (41 males). Attenuation values, CNR, and SNR were higher in 40-keV VMI+ reconstructions compared to the remaining VMI+ and standard F_0.5 series (HU: 1180.41 ± 45.09; SNR: 29.91 ± 0.99; CNR: 28.60 ± 1.03 vs. HU 251.32 ± 7.13; SNR: 13.22 ± 0.44; CNR: 10.57 ± 0.39 in standard F_0.5 series) (p < 0.0001). Subjective image rating was significantly higher in 55-keV VMI+ images compared to the other VMI+ and standard F_0.5 series in terms of image quality (mean score: 4.77), image noise (mean score: 4.39), and assessability of vessel contrast (mean value: 4.57) (p < 0.001). CONCLUSIONS: DECT 40-keV and 55-keV VMI+ showed the highest objective and subjective parameters of image quality, respectively. These specific energy levels for VMI+ reconstructions could be recommended in clinical practice, providing high-quality images with greater diagnostic suitability for the evaluation of lower extremity runoff, and potentially needing a lower amount of contrast medium, which is particularly advantageous for diabetic patients.
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Barium inhalation usually relates to accidental aspiration during radiological procedures with an oral contrast agent. When present, barium lung deposits are visible as high-density opacities on chest X-ray or CT scan due to high atomic number, and they may be indistinguishable from calcifications. Dual-layer spectral CT has shown good material differentiation capabilities, due to its increased high-Z element range and smaller spectral separation between low- and high-energy spectral data. We present the case of a 17-year-old female with a history of tracheoesophageal fistula, who underwent chest CT angiography on a dual-layer spectral platform. Despite the close Z numbers and K-edge energy levels of the two different contrast materials, spectral CT was able to identify barium lung deposits from a previous swallowing study and to clearly distinguish them from calcium and the surrounding iodine-containing structures.
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Transcatheter heart valve (THV) embolization is a rare complication of transcatheter aortic valve implantation (TAVI) generally caused by malpositioning, sizing inaccuracies and pacing failures. The consequences are related to the site of embolization, ranging from a silent clinical picture when the device is stably anchored in the descending aorta to potentially fatal outcomes (e.g., obstruction of flow to vital organs, aortic dissection, thrombosis, etc.). Here, we present the case of a 65-year-old severely obese woman affected by severe aortic valve stenosis who underwent TAVI complicated by embolization of the device. The patient underwent spectral CT angiography that allowed for improved image quality by means of virtual monoenergetic reconstructions, permitting optimal pre-procedural planning. She was successfully re-treated with implantation of a second prosthetic valve a few weeks later.
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Due to its high morbidity and mortality, myocardial infarction is the leading cause of death worldwide. Against this background, rapid diagnosis is of immense importance. Especially in case of an atypical course, the correct diagnosis may be delayed and thus lead to increased mortality rates. In this report, we present a complex case of acute coronary syndrome. A triple-rule-out CT examination was performed in dual-energy CT (DECT) mode. While pulmonary artery embolism and aortic dissection could be ruled out with conventional CT series, the presence of anterior wall infarction was only detectable on DECT reconstructions. Subsequently, adequate and rapid therapy was then initiated leading to survival of the patient.
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The technological development of Artificial Intelligence (AI) has grown rapidly in recent years. The applications of AI to cardiovascular imaging are various and could improve the radiologists' workflow, speeding up acquisition and post-processing time, increasing image quality and diagnostic accuracy. Several studies have already proved AI applications in Coronary Computed Tomography Angiography and Cardiac Magnetic Resonance, including automatic evaluation of calcium score, quantification of coronary stenosis and plaque analysis, or the automatic quantification of heart volumes and myocardial tissue characterization. The aim of this review is to summarize the latest advances in the field of AI applied to cardiovascular CT and MR imaging.
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BACKGROUND: The aim of the study was to provide radiologists and clinicians a rapid tool for assessment of intestinal inflammation in Crohn's disease (CD) patients through quantification of diffusion-weighted imaging (DWI) signal intensity while performing magnetic resonance enterography (MRE). MATERIALS AND METHODS: A monocentric retrospective study was conducted between September 2018 and July 2021 on CD patients who underwent MRE. Two radiologists measured signal intensity on DWI scans at the highest b-value (800 s/mm2) within pathologic intestinal walls, lymph nodes, spleen and psoas muscle and calculated the relative ratios. Spearman, Mann-Whitney and Jonckheere-Terpstra tests were applied for estimating correlation among ratios, significant differences between the two patient groups and determining the trend in relation to endoscopic classes. Wilcoxon's and Cronbach's alpha tests were employed for comparison of DWI measurements and ratios between the two observers. RESULTS: Fifty-nine patients were enrolled in the study. In the non-surgical group, correlation has been found among Simple Endoscopic Score for Crohn's Disease (SES-CD) classes and the different ratios: bowel/spleen (p = 0.034), bowel/psoas (p = 0.008) and bowel/lymph node (p = 0.010). Within the surgical group, positive correlation was found only between bowel/lymph node ratio and bowel/psoas ratio (p = 0.014). The J-T test demonstrated an increasing monotonic trend for bowel/psoas ratio and bowel/lymph node ratio and SES-CD classes. Inter-reader evaluation demonstrated no statistical differences for DWI measurements and high degree of concordance for the final ratios. CONCLUSION: DWI ratios correlate with endoscopic classes in non-surgical patients and have inter-observer reproducibility.
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Crohn Disease , Humans , Crohn Disease/diagnostic imaging , Crohn Disease/pathology , Retrospective Studies , Reproducibility of Results , Diffusion Magnetic Resonance Imaging/methods , Magnetic Resonance Imaging/methods , Magnetic Resonance SpectroscopyABSTRACT
Breast cancer accounts for 30% of female cancers and is the second leading cause of cancerrelated deaths in women. The rate is rising at 0.4% per year. Early detection is crucial to improve treatment efficacy and overall survival of women diagnosed with breast cancer. Digital Mammography and Digital Breast Tomosynthesis have widely demonstrated their role as a screening tool. However, screening mammography is limited by radiologist's experience, unnecessarily high recalls, overdiagnosis, overtreatment and, in the case of Digital Breast Tomosynthesis, long reporting time. This is compounded by an increasing shortage of manpower and resources issue, especially among breast imaging specialists. Recent advances in image analysis with the use of artificial intelligence (AI) in breast imaging have the potential to overcome some of these needs and address the clinical challenges in cancer detection, assessment of treatment response, and monitoring disease progression. This article focuses on the most important clinical implication and future application of AI in the field of digital mammography and digital breast tomosynthesis, providing the readers with a comprehensive overview of AI impact in cancer detection, diagnosis, reduction of workload and breast cancer risk stratification.
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Breast Neoplasms , Mammography , Female , Humans , Mammography/methods , Breast Neoplasms/diagnostic imaging , Artificial Intelligence , Early Detection of Cancer/methods , Mass ScreeningABSTRACT
Constrictive pericarditis (CP) is a rare condition that can affect the pericardium after every pericardial disease process and has been described even after SARS-CoV-2 infection or vaccine. In CP, the affected pericardium, usually the inner layer, is noncompliant, constraining the heart to a fixed maximum volume and impairing the diastolic function. This leads to several clinical features, that, however, can be pleomorphic. In its difficult diagnostic workup, noninvasive multimodal imaging plays a central role, providing important morphological and functional data, like the enhanced ventricular interdependence and the dissociation between intrathoracic and intracardiac pressures. An early and proper diagnosis is crucial to set an appropriate therapy, changing the prognosis of patients affected by CP. In this review, we cover in detail the main elements of each imaging technique, after a reminder of pathophysiology useful for understanding the diagnostic findings.
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Coronary computed tomography angiography (CCTA) represents a common approach to the diagnostic workup of patients with suspected coronary artery disease. Technological development has recently allowed the integration of conventional CCTA information with spectral data. Spectral CCTA used in clinical routine may allow for improving CCTA diagnostic performance by measuring myocardial iodine distribution as a marker of first-pass perfusion, thus providing additional functional information about coronary artery disease.
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Coronary Artery Disease , Humans , Coronary Angiography , Coronary Artery Disease/diagnostic imaging , Tomography, X-Ray ComputedABSTRACT
Immunoglobulin G4-related disease (IgG4-RD) is a systemic immune-mediated fibro-inflammatory disorder. Coronary IgG4-RD has been scarcely reported and may present as "tumor-like" lesions. These pseudo-masses may be underdiagnosed mainly due to a vague clinical picture that can vary from complete lack of symptoms to acute coronary syndrome or sudden cardiac death. Early recognition of coronary IgG4-RD is essential to monitor disease activity and prevent life-threatening complications. We report a comprehensive non-invasive imaging evaluation of a patient affected by coronary IgG4-RD, which was diagnosed as an incidental finding during routine pre-laparoscopic cholecystectomy checkup. Non-invasive imaging revealed the presence of a peri-coronary soft-tissue mass that was stable at 12 months follow-up.
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Button battery ingestion (BBI) is common in children and its prevalence has increased in the last decades. BBI can be responsible for very severe and potentially fatal complications if not promptly detected. We describe the successful management of two cases of BBI that occurred in two previously healthy infants. Both patients presented with vague symptoms and no witness of foreign body ingestion. The prolonged time of exposure to the corrosive effects of disk batteries was responsible for the development of tracheo-esophageal fistula (TEF) and aorto-esophageal fistula (AEF). We demonstrate how prompt diagnosis and management are crucial for the infants' survival.
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Artificial intelligence is rapidly expanding in all technological fields. The medical field, and especially diagnostic imaging, has been showing the highest developmental potential. Artificial intelligence aims at human intelligence simulation through the management of complex problems. This review describes the technical background of artificial intelligence, machine learning, and deep learning. The first section illustrates the general potential of artificial intelligence applications in the context of request management, data acquisition, image reconstruction, archiving, and communication systems. In the second section, the prospective of dedicated tools for segmentation, lesion detection, automatic diagnosis, and classification of musculoskeletal disorders is discussed.
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Deep Learning , Musculoskeletal System , Humans , Artificial Intelligence , Machine Learning , Image Processing, Computer-Assisted , Musculoskeletal System/diagnostic imagingABSTRACT
[This corrects the article DOI: 10.1016/j.radcr.2022.02.079.].
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PURPOSE: To evaluate morphological and functional changes in the Bichat fat pad (BFP) after curative concurrent chemoradiotherapy in nasopharyngeal cancer (NPC) patients. METHODS: We retrospectively analyzed the volumetric, metabolic, and dosimetry parameters of BFPs in 7 NPC patients who underwent intensity-modulated radiotherapy (IMRT) between 2015 and 2020. Inclusion criteria were i) histologically confirmed diagnosis of NPC, ii) follow-up period of at least 12 months, iii) no history of previous irradiation or surgery in the maxillofacial area, and ìv) availability of pre- and posttreatment MRI and 18FFDG PET-CT performed in our Institution. All patients had stage III-IVA disease (nâ¯= 7) and received platinum-based chemotherapy. Planned doses in 30 daily fractions/5 days per week were 66â¯Gy (2.2â¯Gy/die 5 days/week) to the gross tumor volume, 66â¯Gy (2.1-2.2â¯Gy/die 5 days/week) to the gross nodal volume, 60â¯Gy (2â¯Gy/die 5 days week) to clinical target volume (CTV)1, and 54â¯Gy (1.8â¯Gy/die 5 days/week) to CTV2. All patients completed the planned radiotherapy course in a median time of 42 days (range 42-43). Relationships between BFP volumes and the following DVH parameters were evaluated: mean dose, maximum dose (Dmax), and percentage of BFP volume receiving more than 5 to 65â¯Gy (V5 to V65). RESULTS: The pre-RT volumes of the left and right BFPs were 12.24 cc (range 6.51-20.01 cc) and 11.55 cc (range 5.78-17.53 cc), respectively. The mean volumes of left BFPPRE and BFPPOST were 12.24 cc (range 6.51-20.01cc) and 13.85 cc (range 7.54-20.21â¯cc), respectively, with no significant statistical differences (Pâ¯> 0.05). No statistically significant correlations were found between dosimetry features and BFP volumetric changes (all Pâ¯> 0.05). CONCLUSION: Our original results showed that chemoradiotherapy does not induce significant volumetric changes of the BFP. Further investigations are needed to evaluate the effects of higher radiation doses on BFP. This is the first real-world study on this issue.
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Nasopharyngeal Neoplasms , Radiotherapy, Intensity-Modulated , Humans , Adipose Tissue , Fluorodeoxyglucose F18 , Nasopharyngeal Carcinoma , Nasopharyngeal Neoplasms/radiotherapy , Nasopharyngeal Neoplasms/pathology , Positron Emission Tomography Computed Tomography , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Intensity-Modulated/methods , Retrospective StudiesABSTRACT
The canal of Nuck is an abnormal patent pouch of the parietal peritoneum caused by the incomplete obliteration of the processus vaginalis in females. The most common disorders of the canal of Nuck are: hernia, hydrocele and endometriosis. Pseudomyxoma Peritonei (PMP) is a clinical condition characterized by the accumulation of mucinous material on the surfaces and in the recesses of the peritoneal cavity, resulting from the perforation of an appendiceal mucinous neoplasm. We report the case of a young woman with a clinical history of chronic pelvic pain and infertility who was referred to our center after being diagnosed with appendiceal mucinous neoplasm and PMP. MRI staging examination revealed the right canal of Nuck filled with mucinous material, which was confirmed at surgery. The involvement of canal of Nuck is extremely rare in PMP. MRI provides a sensitive imaging modality for appropriate preoperative planning of PMP and helps surgeons identify uncommon disease sites such such as the canal of Nuck in women, which, if missed, may prevent complete cytoreductive surgery.