CT Imaging Of Abdomen Research Articles

Sparse deep belief network coupled with extended local fuzzy active contour model-based liver cancer segmentation from abdomen CT images.

Liver cancer from abdominal CT images must be accurately segmented for the purpose of diagnosis with treatment planning. But, the similarity in gray values between the liver and the surrounding tissues poses a challenge. To address this, a novel sparse deep belief network coupled with extended local fuzzy active contour model-based liver cancer segmentation from abdomen CT images (SDBN-ELFAC-LCS-CT) is proposed. This method incorporates dynamic adaptive pooling and residual modules in SDBN to improve the feature selection and generalization ability. Additionally, the 3D reconstruction is performed to refine segmentation results. The proposed SDBN-ELFAC-LCS-CT approach is implemented in MATLAB. The performance of the proposed SDBN-ELFAC-LCS-CT achieves dice coefficients that were up to 96.16% higher and 75.88%, 88.75%, and 71.16% lower. Volumetric overlap error compared with existing models, like basic ensembles of vanilla-style deep learning modes, increases liver segmentation from CT imageries (BEVS-LCS-CT), an incorporated 3 dimensional sparse deep belief network along enriched seagull optimization approach for liver segmentation (3DBN-ESOA-LCS-CT) and iterative convolutional encoder-decoder network and multiple scale context learning for segmenting liver (ICEDN-LCS-CT), respectively.

Case 317: Adult-Onset Leukoencephalopathy with Axonal Spheroids and Pigmented Glia.

A 44-year-old previously healthy man with a 9-month history of progressive cognitive decline, depression, urinary incontinence, and inability to perform tasks of daily living presented to the emergency department with worsening cognitive and neuropsychiatric symptoms. He had become more distressed, and his family noticed him departing the house without closing doors, leaving water faucets running, and sending his children to school on Sundays. History taken from the patient's wife revealed that his brother had passed away in his late 30s after a slowly progressing functional and cognitive decline over the course of 5 years. No further detailed family history could be obtained. The review of systems was negative; he had no prior medical, psychiatric, or surgical history; and he denied any history of recent travel, camping, hiking, or vaccination. The patient was not taking any dietary supplements, nor was he taking any over-the-counter or prescription medication. Examination revealed vital signs were within normal limits. Neurocognitive assessment revealed a conscious, coherent, and alert patient with impaired memory and concentration. He showed poor attention, depressed mood, and restricted affect. He was unable to spell the word world forward, nor was he able to understand a request to spell it backward. The rest of the physical and neurologic examination revealed no abnormalities. Extensive laboratory work-up was conducted and included the following: toxicology screening; screening for HIV-1, HIV-2, and syphilis treponemal antibodies; COVID-19 polymerase chain reaction; and measurement of B1 and B12 levels. The results of screening were negative. Cerebrospinal fluid (CSF) assays, including CSF oligoclonal bands and CSF flow cytometry, revealed values within normal limits. CT of the brain without intravenous contrast material was performed in the emergency department to rule out acute intracranial abnormality. Multiplanar multisequence MRI of the brain without and with intravenous contrast material was ordered for further assessment. CT images of chest, abdomen, and pelvis were unremarkable (images not shown).

CORR Insights®: Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.

CORR Insights®: Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.

Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.

Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.

CT and MR imaging of the properitoneal fat pad: a pictorial essay.

The properitoneal fat pad is a distinctive anatomical structure located in the midline of anterior abdominal wall between the transversalis fascia and parietal peritoneum. It has variable size and configuration depending on the gender and nutritional status of individuals, but CT and MR images of the upper abdomen can readily depict its shape and adipose composition. The purpose of this essay is to illustrate the CT and MRI features of normal properitoneal fat pad, and the spectrum of pathological processes that affect it among patients. This information can be relevant to the practicing radiologists and clinicians for the correct diagnosis and management of such conditions because most lesions of this fat pad produce nonspecific symptoms.

Case 317

A 44-year-old previously healthy man with a 9-month history of progressive cognitive decline, depression, urinary incontinence, and inability to perform tasks of daily living presented to the emergency department with worsening cognitive and neuropsychiatric symptoms. He had become more distressed, and his family noticed him departing the house without closing doors, leaving water faucets running, and sending his children to school on Sundays. History taken from the patient's wife revealed that his brother had passed away in his late 30s after a slowly progressing functional and cognitive decline over the course of 5 years. No further detailed family history could be obtained. The review of systems was negative; he had no prior medical, psychiatric, or surgical history; and he denied any history of recent travel, camping, hiking, or vaccination. The patient was not taking any dietary supplements, nor was he taking any over-the-counter or prescription medication. Examination revealed vital signs were within normal limits. Neurocognitive assessment revealed a conscious, coherent, and alert patient with impaired memory and concentration. He showed poor attention, depressed mood, and restricted affect. He was unable to spell the word world forward, nor was he able to understand a request to spell it backward. The rest of the physical and neurologic examination revealed no abnormalities. Extensive laboratory work-up was conducted and included the following: toxicology screening; screening for HIV-1, HIV-2, and syphilis treponemal antibodies; COVID-19 polymerase chain reaction; and measurement of B1 and B12 levels. The results of screening were negative. Cerebrospinal fluid (CSF) assays, including CSF oligoclonal bands and CSF flow cytometry, revealed values within normal limits. CT of the brain without intravenous contrast material was performed in the emergency department to rule out acute intracranial abnormality (Fig 1). Multiplanar multisequence MRI of the brain without and with intravenous contrast material was ordered for further assessment (Figs 2-4). CT images of chest, abdomen, and pelvis were unremarkable (images not shown).

Hepatic lesion detectability in abdomen computed tomography: Investigation in low kVp single energy and low keV virtual monochromatic images generated from dual energy computed tomography using task-based image quality assessment in phantom

Background: Low tube potential single-energy (SE) and virtual monochromatic image (VMI) dual energy (DE) abdomen CT images both improve the hepatic lesion detection by increasing the liver lesion contrast on images. Objectives: To study the performance of low kVp single energy and low keV virtual monochromatic images (VMI) generated from dual energy acquisition to detect the hepatic lesion on abdominal CT imaging in phantom. Materials and methods: The anthropomorphic liver with nodule inserted phantom with extension rings simulating the small, medium, and large patient was scanned under the SECT acquisition by varying the kVp from 70-120 kVp and for DECT acquisitions, three kVp combinations (80/-,90/-, and 100/Sn150-kVp). The series of 40-,50-,60-, and 70-keV VMI were generated from DECT data set. All images were used to assess the task-based image quality; task transfer function (TTF), noise power spectrum (NPS), and detectability index (d’) with the diagnostic task to detect 15 mm diameter hyperattenuating hepatic lesion. Results: The result showed that the TTF was higher in low kVp SECT while the lesion contrast was higher at low keV VMI -DECT. The noise magnitude remained constant for all kVp values in SECT, but it was dramatically increased as decreased the energy level from 70- to 40-keV in VMI-DECT. The fav of NPS shifted to higher frequency when increasing the kVp and when increasing the energy level of VMI. The obtained d’ was highest in low kVp SECT at 70-or 80-kVp. Conclusion: The low kVp SECT provided the highest d’ than that in low keV VM image from DECT in all phantom sizes where the highest d’ was found at 70 kVp-SECT for small and medium phantom and at 80 kVp for large phantom. For SECT, reduced the kVp to 70- or 80-kVp improved the detectability index. The kVp combination in DECT impacts to the d’ of VMI; at small phantom, the highest d’ for each keV VMI was found at 80/Sn150 kVp acquisition and at larger phantom size, higher kVp on tube “A” is more favored.

PMON33 Non-Syndromic SRY Negative 46 XX Testicular Disorder of Sex Development (DSD): A Rare Cause of Infertility

Abstract Introduction Male infertility can be categorized as endocrine and systemic disorders, primary testicular defects in spermatogenesis, sperm transport disorders and idiopathic male infertility. Chromosomal abnormalities are one of the primary testicular defects. The overall incidence of chromosome abnormalities in infertile men is estimated to be around 5.8%. XX male is a rare sex chromosomal disorder in infertile men. We present case of a young patient with infertility, azoospermia, hypergonadotropic hypogonadism and classical (46, XX) karyotype with negative FISH and SRY gene. Case report: 28-Year-old gentleman was referred to adult endocrinology clinic as part of work up for infertility. Initial work up included 2 semen analyses which were consistent with azoospermia. Examination revealed height 180 cm, weight 77 kg, a body mass index 24 kg/m2, normal phenotypic male without gynecomastia and had normal male pattern hair distribution. Genital examination showed normal male phallus without hypospadias, a hypoplastic scrotum, bilateral firm testes, with no varicocele or hydrocele. Labs were suggestive of compensated primary hypogonadism (FSH 47.9 mIU/ml, LH 20.4 mIU/ml, total testosterone 397.9 ng/dl by LC/MS, free testosterone 15.76 ng/dl by equilibrium dialysis, Inhibin B < 10 pg/ml, and anti-Mullerian hormone 0.390 ng/ml. Given normal testosterone levels, he was not started on testosterone replacement. Karyotype analysis revealed 46 XX and FISH was negative for SRY gene. CT imaging of abdomen and pelvis did not reveal any Mullerian structures, prostrate and seminal vesicles reported as normal. Patient met with a Urologist and was informed that testicular sperm extraction will not be a possibility for him. Patient had a detailed consultation with a geneticist for genetic and family counseling. Chromosome microarray analysis was obtained and was normal. Invitae Disorders of sex development (DSD) panel obtained for genetic sequencing of 53 genes including SOX-9, DHH, WNT4, WT1, was found to be non-diagnostic. Conclusion and Discussion SRY negative 46 XX male is a DSD and a rare genetic cause of male factor infertility, with a discrepancy between genotype and phenotypic sex. In the case presented, genetic work up for potential etiologies has been unrevealing. Further studies are needed to identify the genetic causes of the SRY negative 46 XX male phenotype. Physicians involved in care of these patients should orient with clinical management and prognosis. For Classical 46 XX Males seeking fertility, the current options include invitro-fertilization with donor sperm or adoption only. Testosterone replacement should be considered to correct hypogonadism for physical and sexual well-being. Genetic consultation should be sought in all these cases. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

PMON33 Non-Syndromic SRY Negative 46 XX Testicular Disorder of Sex Development (DSD); A rare cause of Infertility

Abstract Introduction Male infertility can be categorized as endocrine and systemic disorders, primary testicular defects in spermatogenesis, sperm transport disorders and idiopathic male infertility. Chromosomal abnormalities are one of the primary testicular defects. The overall incidence of chromosome abnormalities in infertile men is estimated to be around 5.8%. XX male is a rare sex chromosomal disorder in infertile men. We present case of a young patient with infertility, azoospermia, hypergonadotropic hypogonadism and classical (46, XX) karyotype with negative FISH and SRY gene. Case report: 28-Year-old gentleman was referred to adult endocrinology clinic as part of work up for infertility. Initial work up included 2 semen analyses which were consistent with azoospermia. Examination revealed height 180 cm, weight 77 kg, a body mass index 24 kg/m2, normal phenotypic male without gynecomastia and had normal male pattern hair distribution. Genital examination showed normal male phallus without hypospadias, a hypoplastic scrotum, bilateral firm testes, with no varicocele or hydrocele. Labs were suggestive of compensated primary hypogonadism (FSH 47.9 mIU/ml, LH 20.4 mIU/ml, total testosterone 397.9 ng/dl by LC/MS, free testosterone 15.76 ng/dl by equilibrium dialysis, Inhibin B < 10 pg/ml, and anti-Mullerian hormone 0.390 ng/ml. Given normal testosterone levels, he was not started on testosterone replacement. Karyotype analysis revealed 46 XX and FISH was negative for SRY gene. CT imaging of abdomen and pelvis did not reveal any Mullerian structures, prostrate and seminal vesicles reported as normal. Patient met with a Urologist and was informed that testicular sperm extraction will not be a possibility for him. Patient had a detailed consultation with a geneticist for genetic and family counseling. Chromosome microarray analysis was obtained and was normal. Invitae Disorders of sex development (DSD) panel obtained for genetic sequencing of 53 genes including SOX-9, DHH, WNT4, WT1, was found to be non-diagnostic. Conclusion and Discussion SRY negative 46 XX male is a DSD and a rare genetic cause of male factor infertility, with a discrepancy between genotype and phenotypic sex. In the case presented, genetic work up for potential etiologies has been unrevealing. Further studies are needed to identify the genetic causes of the SRY negative 46 XX male phenotype. Physicians involved in care of these patients should orient with clinical management and prognosis. For Classical 46 XX Males seeking fertility, the current options include invitro-fertilization with donor sperm or adoption only. Testosterone replacement should be considered to correct hypogonadism for physical and sexual well-being. Genetic consultation should be sought in all these cases. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

Virtual cadaver facilitates abdominopelvic anatomy teaching

Purpose CT imaging of the upper abdomen has complex anatomy that can be difficult to parse given similar densities of multiple organs. Understanding of upper abdominal anatomy, limitations of CT imaging, and alternative methods for visualization are important for physicians in multiple surgical and non-surgical fields. We repurposed a novel, open-access resource to facilitate teaching upper abdominal anatomy. Methods This pilot study with medical students had three learning objectives: 1) identify abdominal organs and sub-structures on CT and 3D human cadaver imaging 2) justify why different types of contrast (e.g. oral or IV) are used or can be omitted based on region of interest. 3) Rationalize use of non-CT visualizations such as MRI, endoscopy, or laparotomy for select scenarios. Hybrid in-person and virtual attendance at sessions employing CT images linked with human cadaver image set serially sectioned from Visible Human Project (https://www.nlm.nih.gov/research/visible/visible_human.html). Students identified and outlined structures on CT using three orthogonal planes prior to blending in cadaver images. Facilitated discussion of challenging organ interfaces (e.g. pancreas and duodenum) and techniques to improve contrast or alternative visualization modalities (e.g. MRI or direct visualization). Post-session survey delivered via e-mail same day. Results Seven students attended the pilot session (3 virtually) with five of seven responding to survey (71% response rate). All respondents found the session to be moderately or very helpful and felt that after the session they were moderately or very confident in their ability to identify upper abdominal structures. Regarding the cadaver images, 1 student thought it was very helpful (20%), 3 students thought it was moderately helpful (60%), and 1 student thought it was not at all helpful (20%). Discussion Human cadaver imaging can help facilitate teaching of CT based anatomy in a pilot study of medical students. Additional sessions may better elucidate benefits and limitations. This resource could be adapted for residents identifying hepatobiliary structures, distinguishing prostate apex from genitourinary diaphragm, and differentiating mediastinal nodal levels from vascular spaces. CT imaging of the upper abdomen has complex anatomy that can be difficult to parse given similar densities of multiple organs. Understanding of upper abdominal anatomy, limitations of CT imaging, and alternative methods for visualization are important for physicians in multiple surgical and non-surgical fields. We repurposed a novel, open-access resource to facilitate teaching upper abdominal anatomy. This pilot study with medical students had three learning objectives: 1) identify abdominal organs and sub-structures on CT and 3D human cadaver imaging 2) justify why different types of contrast (e.g. oral or IV) are used or can be omitted based on region of interest. 3) Rationalize use of non-CT visualizations such as MRI, endoscopy, or laparotomy for select scenarios. Hybrid in-person and virtual attendance at sessions employing CT images linked with human cadaver image set serially sectioned from Visible Human Project (https://www.nlm.nih.gov/research/visible/visible_human.html). Students identified and outlined structures on CT using three orthogonal planes prior to blending in cadaver images. Facilitated discussion of challenging organ interfaces (e.g. pancreas and duodenum) and techniques to improve contrast or alternative visualization modalities (e.g. MRI or direct visualization). Post-session survey delivered via e-mail same day. Seven students attended the pilot session (3 virtually) with five of seven responding to survey (71% response rate). All respondents found the session to be moderately or very helpful and felt that after the session they were moderately or very confident in their ability to identify upper abdominal structures. Regarding the cadaver images, 1 student thought it was very helpful (20%), 3 students thought it was moderately helpful (60%), and 1 student thought it was not at all helpful (20%). Human cadaver imaging can help facilitate teaching of CT based anatomy in a pilot study of medical students. Additional sessions may better elucidate benefits and limitations. This resource could be adapted for residents identifying hepatobiliary structures, distinguishing prostate apex from genitourinary diaphragm, and differentiating mediastinal nodal levels from vascular spaces.

Role of CT Images in the Diagnosis of Common Acute Abdominal Diseases in General Surgery.

Acute abdomen is a clinical emergency disease with acute abdominal pain as the main prominent feature. Through severe disease changes in intra-abdominal, extrapelvic, and retroperitoneal tissues and organs, symptoms and clinical signs led by abdominal pain are formed. This article mainly explores the role of CT imaging diagnosis in common acute abdominal diseases in general surgery. In this paper, the use of computer-aided CT scan imaging technology in pulmonary nodules was firstly investigated, and the image segmentation algorithms based on CT images were given, including the spatial domain fuzzy C-mean clustering separation algorithm and the spatial domain fuzzy clustering level set semiautomatic separation algorithm, then the treatment of acute abdomen under the concept of ERAS was explored, and the treatment of ERAS under CT images of the acute abdomen was analyzed and studied. The empirical research results show that the ERAS's concept is guided by the undergoing national nutritional support with the traditional perioperative management. Compared to 12.9% of complications in traditional CPM groups, the recall rate of complications after ERAS group was only 6.01%, the improvement was obvious and the results were statistically significant (P < 0.05). Postoperative hospitalization time was also 4.62 days from 7.93 days, thus controlling the clinical risks of perioperative periods, providing a benefit to patient life.

A REVIEW OF TREATMENT, RISK FACTORS, AND INCIDENCE OF COLORECTAL CANCER

Colorectal cancer (CRC) is considered as the third most frequent cancer in the world and the incidence increases with increasing age. CRC accounts for nearly 9 % of all cancer incidence, with an estimated 1.4 million cases happening in 2012. The aim of this paper is to provide a review of incidence, risk factors, screening strategies, and treatment of colorectal cancer. We searched the studies in five English databases, including Web of Science, PubMed, Scopus, EMBASE, and Google Scholar with no limitation in publication time to find all papers regarding colorectal cancers. Papers with any language were included in the first step of search if they had an English abstract. We used the following words and terms including colorectal cancer, treatment, risk factor, diagnosis, chemotherapy, radiotherapy, surgery. Geographical variations and different time courses in the CRC incidence indicate that environmental factors and lifestyle are major factors in the development of this disease. The main preventable risk factors for CRC are nutrition, a high-fat diet, a low-fiber diet, obesity and physical inactivity, smoking and alcohol consumption, aspirin and nonsteroidal anti-inflammatory drugs, and some non-preventable risk factors such as age, gender, race, and diabetes mellitus. Colonoscopy remains the study of choice to diagnose colorectal cancer. Prior to any treatment, CT imaging of chest, abdomen and pelvis with contrast is needed for staging the patient’s CRC. The preferred option for localized colorectal cancer is surgery (etc, laparoscopic surgery, colostomy for rectal cancer); whereas the adjuvant chemotherapy is generally recommended for patients with lymph node metastases. Targeted treatment of colorectal cancer by monoclonal antibodies are important bioengineered proteins that can help the body's natural immune response to detect, attack, and kill cancer cells. Monoclonal antibodies may be used alone or in combination with other treatments such as chemotherapy. CRC accounts an important health problem worldwide that is estimated to increase because of the growth and aging of the population, and because of the adoption of at-risk manners and lifestyles, particularly in economically less developed countries. Screening has been confirmed to significantly decrease mortality and can prevent the onset of the disease. More international efforts are required to situate into practice targeted prevention approaches that might reduce the burden of CRC worldwide.

Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction

BackgroundEfforts to reduce the radiation dose have continued steadily, with new reconstruction techniques. Recently, image denoising algorithms using artificial neural networks, termed deep learning reconstruction (DLR), have been applied to CT image reconstruction to overcome the drawbacks of iterative reconstruction (IR). The purpose of our study was to compare the objective and subjective image quality of DLR and IR on pediatric abdomen and chest CT images.MethodsThis retrospective study included pediatric body CT images from February 2020 to October 2020, performed on 51 patients (34 boys and 17 girls; age 1–18 years). Non-contrast chest CT (n = 16), contrast-enhanced chest CT (n = 12), and contrast-enhanced abdomen CT (n = 23) images were included. Standard 50% adaptive statistical iterative reconstruction V (ASIR-V) images were compared to images with 100% ASIR-V and DLR at medium and high strengths. Attenuation, noise, contrast to noise ratio (CNR), and signal to noise (SNR) measurements were performed. Overall image quality, artifacts, and noise were subjectively assessed by two radiologists using a four-point scale (superior, average, suboptimal, and unacceptable). A phantom scan was performed including the dose range of the clinical images used in our study, and the noise power spectrum (NPS) was calculated. Quantitative and qualitative parameters were compared using repeated-measures analysis of variance (ANOVA) with Bonferroni correction and Wilcoxon signed-rank tests.ResultsDLR had better CNR and SNR than 50% ASIR-V in both pediatric chest and abdomen CT images. When compared with 50% ASIR-V, high strength DLR was associated with noise reduction in non-contrast chest CT (33.0%), contrast-enhanced chest CT (39.6%), and contrast-enhanced abdomen CT (38.7%) with increases in CNR at 149.1%, 105.8%, and 53.1% respectively. The subjective assessment of overall image quality and the noise was also better on DLR images (p < 0.001). However, there was no significant difference in artifacts between reconstruction methods. From NPS analysis, DLR methods showed a pattern of reducing the magnitude of noise while maintaining the texture.ConclusionCompared with 50% ASIR-V, DLR improved pediatric body CT images with significant noise reduction. However, artifacts were not improved by DLR, regardless of strength.

Validation of a Semiautomatic Image Analysis Software for the Quantification of Musculoskeletal Tissues.

Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed. Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n = 19), and CT images of hip and abdomen (n = 100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n = 100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson's correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland-Altman limits of agreement together with Bland-Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software. In the animal study, the agreement between Tissue Compass and commercial software was r > 0.93 and ICC > 0.93 for rat femur measurements. Bland-Altman limits of agreement was -720.89 (-1.5e+04, 13,074.00) for MAT, 4421.11 (-1.8e+04, 27,149.73) for HBM and -6073.32 (-2.9e+04, 16,388.37) for bone. The inter-observer agreement for QCT human study between two observers was r > 0.99 and ICC > 0.99. Bland-Altman limits of agreement was 0.01 (-0.07, 0.10) for MAT in hip, 0.02 (-0.08, 0.12) for HBM in hip, 0.05 (-0.15, 0.25) for bone in hip, 0.02 (-0.18, 0.22) for MAT in L1, 0.00 (-0.16, 0.16) for HBM in L1, and0.02 (-0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between thetwo applications was r > 0.997 and ICC > 0.99. Bland-Altman limits of agreement was 0.03 (-0.13, 0.20) for MAT in hip, 0.05 (-0.08, 0.18) for HBM in hip, 0.05 (-0.24, 0.34) for bone in hip, -0.02 (-0.34, 0.31) for MAT in L1, -0.14 (-0.44, 0.17) for HBM in L1, -0.29 (-0.62, 0.05) for bone in L1, 0.03 (-0.08, 0.15) for IMAT in psoas, and 0.02 (-0.35, 0.38) for muscle in psoas. Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.

Cardiobacterium Valvarum Bacteremia in a Left Ventricular Assist Device Recipient: Case Report and Review of the Literature

Introduction Cardiobacterium valvarum is a HACEK organism known for causing infective endocarditis (IE); there are no reported cases implicating this bacterium in left ventricular assist device (LVAD) infections in the English literature. Case Report A 59 year old gentleman with sarcoidosis, systolic heart failure (EF 15%), BiV-ICD (implanted 11/2015) and LVAD (Heartware implanted 10/2017) presented with fever and cough. He experienced worsening lower extremity edema and abdominal girth one week prior to admission. In the emergency room his temperature was 39.5°C and had mild erythema without drainage at his drive line exit site (DLES). Labs were notable for WBC of 15.5 × 103/μL and lactic acid of 2.2 mmol/L. Blood cultures were obtained and the patient received piperacillin-tazobactam and vancomycin. TTE and CT imaging of chest and abdomen demonstrated no significant findings. The initial blood culture became positive with gram-negative bacilli after 3.5 days and were identified as C. valvarum 28 days after initial presentation. He completed a two-week course of ertapenem and transitioned to cephalexin 500 mg BID as secondary prophylaxis. Erythema at the DLES improved and heart failure symptoms resolved. The patient remained on this regimen until transplant, 348 days from positive culture. The organisms classified in the HACEK (Haemophilus spp., Aggregatibacter spp., Cardiobacterium spp., Eikenella spp., and Kingella spp.) group are known for being fastidious causes of IE; they are not traditionally associated with pump, line, or pocket infections in VAD patients. The most common gram-negative bacterial infections associated with VADs and their components are P. aeruginosa and enteric organisms. This patient's case was treated as a VAD-related blood stream infection. Because Cardiobacterium spp. are oral commensals, DLES as the source was less likely. As noted in the IE guidelines, the presence of a HACEK organism without an identifiable source should be considered IE unless proven otherwise, even if there are no other stigmata of IE. Thus, despite only one culture growing C. valvarum, there was a high suspicion for the components of the VAD being seeded, resulting in antibiotic suppression until transplantation. Summary In the presence of a VAD, HACEK organism found in the bloodstream should be treated as a pump infection unless proven otherwise.

Case 290.

History A 26-year-old man presented with a 1-month history of chest pain, a palpable and painful right inguinal mass, and edema in the right lower extremity. One month earlier, he started to experience left chest pain with no cough. Pulmonary CT angiography (CTA) revealed a left lower lobe segmental pulmonary embolus. The local hospital made a diagnosis of pulmonary embolism (PE). He received anticoagulants, and his chest pain was gradually relieved. At the time of current presentation, the patient was experiencing right lower extremity swelling and pain. Physical examination revealed a 4 × 3 cm palpable right inguinal mass with no redness. His medical history and family history were negative. The results of laboratory work-up were normal, with a D-dimer level of 0.16 mg/L fibrinogen equivalent units (reference range, <0.46 mg/L) and an international normalized ratio of 2.45 (therapeutic range, 2.0-3.0 for a patient taking warfarin), except the prothrombin time was 28.2 seconds (reference range, 9.6-12.8 seconds) and the activated partial thromboplastin time was 52.2 seconds (reference range, 24.8-33.8 seconds). Echocardiography, chest radiography, chest CT, and contrast-enhanced CT revealed no abnormalities. The patient underwent right lower extremity vascular conventional US (Philips IU22; Philips) with an L9-3 probe (3-9 MHz, venous condition) and contrast-enhanced US (1.5-2.0 mL, SonoVue; Bracco) with an intravenous bolus injection at the initial evaluation. Two days later, noncontrast and contrast-enhanced CT images of the lower abdomen (1.5 mL per kilogram of body weight, 300 mg/mL iomeprol, Iomeron; Bracco) were acquired for further evaluation (Figs 1-3).

MDCT Evaluation Of Right Iliac Fossa Pathologies With Special Emphasis On Lymph Nodal Characteristics

Introduction:Right iliac fossa pathologies are one of the common reasons for right iliac fossa pain & patient presentation to the Emergency department. It may be related to either benign or malignant diseases. Radiological imaging plays a pivotal role in the differential diagnosis among these diseases. Lymphatic involvement of diseases helps us to learn about the nature of the disease and predict the way of progression, hence awareness with the normal lymph node radiological appearance and its suspicious criteria by radiologists is a crucial information for treatment preparation and execution.AIMS AND OBJECTIVES:To describe key imaging findings of various right iliac fossa pathologies.To assess the role of characteristics of lymph nodes in various right iliac fossa pathologies.METHODOLOGY:A total of 50 cases clinically suspected & diagnosed of having right iliac fossa pathology by CECT imaging of abdomen, at the department of Radiodiagnosis, AMC MET Medical college, Maninagar, Ahmedabad were included in this study.CECT was carried out on PHILIPS MX 16 slice CT machine after giving oral, rectal & iv contrast and axial, sagittal and coronal images were obtained.RESULTS:In our study, most common pathology found was acute appendicitis (16/50), followed by ileocaecal tuberculosis (12/50) and non-tuberculous infectious enterocolitis (11/50). The other pathologies encountered were epiploic appendagitis (3/50), caecal malignancy (2/50), diverticulitis (2/50), Crohn’s disease (2/50) and lymphoma (1/50).Discussion & CONCLUSION:CE CT images of abdomen are very helpful in diagnosis of various right iliac fossa pathologies. Demonstration of lymph nodal patterns of enhancement and their characteristics can further help in narrowing the diagnosis of right iliac fossa pathologies.

Gaussian Hermite polynomial based lossless medical image compression

The role of compression is inevitable in the storage and transmission of medical images. The polynomial based image compression is proposed in this work for the compression of abdomen CT medical images. The input images are preprocessed by min–max normalization; the pixels are scanned and subjected to polynomial approximation. The polynomial approximated coefficients are subjected to llyods quantization and encoded by arithmetic coder. The medical image compression using Gaussian Hermite polynomial gives superior results when compared with the legendre polynomial based image compression and JPEG lossless compression techniques in terms of Peak to signal noise ratio (PSNR), Mean square Error (MSE) and other picture quality metrics. The algorithms are tested on real-time DICOM abdomen CT image and can be used for data transfer in teleradiology application.

Accuracy of radiomics for differentiating diffuse liver diseases on non-contrast CT.

Radiomics help move cross-sectional imaging into the domain of quantitative imaging to assess the lesions, their stoma as well as in their temporal monitoring. We applied and assessed the accuracy of radiomics for differentiating healthy liver from diffuse liver diseases (cirrhosis, steatosis, amiodarone deposition, and iron overload) on non-contrast abdomen CT images in an institutional-reviewed board-approved, retrospective study. Our study included 300 adult patients (mean age 63 ± 16years; 171 men, 129 women) who underwent non-contrast abdomen CT and had either a healthy liver (n = 100 patients) or an evidence of diffuse liver disease (n = 200). The diffuse liver diseases included steatosis (n = 50), cirrhosis (n = 50), hyperdense liver due to amiodarone deposition (n = 50), or iron overload (n = 50). We manually segmented the liver in one section at the level of the porta hepatis (all 300 patients) and then over the entire liver volume (50 patients). Radiomics were estimated for the liver, and statistical comparison was performed with multiple logistic regression and random forest classifier. With random forest classifier, the AUC for radiomics ranged between 0.72 (iron overload vs. healthy liver) and 0.98 (hepatic steatosis vs. healthy liver) for differentiating diffuse liver disease from the healthy liver. Combined root mean square and gray-level co-occurrence matrix had the highest AUC (AUC:0.99, p < 0.01) for differentiating healthy liver from steatosis. Radiomics were more accurate for differentiating healthy liver from amiodarone (AUC:0.93) than from iron overload (AUC:0.79). Radiomics enable differentiation of healthy liver from hepatic steatosis, cirrhosis, amiodarone deposition, and iron overload from a single section of non-contrast abdominal CT. The high accuracy of radiomics coupled with rapid segmentation of the region of interest, radiomics estimation, and statistical analyses within the same prototype makes a compelling case for bringing radiomics to clinical use for improving reporting in evaluation of healthy liver and diffuse liver diseases.

Automatic Diagnosis of Liver Tumor in Ct Images

Medical Image Segmentation is the important tool for diagnosing tumor and for planning how to do treatment. The intention of this study is to detect tumor from CT liver images. Initially, liver is segmented from abdomen CT images. Then SVM Classification is included to classify the normal and abnormal liver structure. If it is abnormal then the tumor will be segmented from liver structure. This technique is computed using sensitivity, specificity and accuracy and is providing good result.