CT Density Research Articles

Impact of CT tube-voltage and bone density on the quantitative assessment of tracer uptake in Tc-99m bone SPECT/CT: A phantom study

PurposeTo evaluate the effect of computed tomography (CT) tube voltage and CT density for CT-based attenuation correction (CTAC) on quantification of tracer uptake in single photon emission computed tomography (SPECT)/CT. MethodsA cylindrical phantom contained 7 cylinders with diameter of 30 mm. The central cylinder and background part were filled with 17 kBq/ml of 99mTc-pertechnetate solution. Of the remaining 6 cylinders, one cylinder was filled with water and 5 cylinders were filled with each own different concentration of K2HPO4 solution (120, 275, 450, 666, and 960 mg/cm3) to simulate different bone densities. The 6 cylinders also contained 99mTc-pertechnetate solution with the same radioactivity concentration (207 kBq/ml). CT scans were performed with 4 different tube voltages of 80, 100, 120, and 140 kVp for CTAC. The radioactivity concentration in the 6 cylinders were measured on the SPECT images processed with 4 different attenuation coefficient maps derived from each tube voltage of CT images. ResultsCompared with the water cylinder without K2HPO4 solution, the measured radioactivity of the highest density cylinder (K2HPO4 solution concentration: 960 mg/cm3) was found to be overestimated by 3.3 % and 4.3 %, respectively, when the tube voltage was 120 kVp and 140 kVp (p = 0.022). The use of low-tube voltage, such as 80 kVp, has improved the quantitative accuracy of bone SPECT/CT. ConclusionsSPECT quantitative evaluation of tracers in high-density objects tends to overestimate as tube voltage for CTAC increases. However, the overestimation in quantitative SPECT/CT evaluation in simulated bone area is less than 5% at most.

Prediction of Patients at Risk of Pelvic Insufficiency Fractures Following Pelvic Radiotherapy

<h3>Purpose/Objective(s)</h3> Radiotherapy-induced pelvic insufficiency fractures (PIFs), historically under-reported, can lead to significant morbidity. Using deep-learning techniques, this study develops a fully automated predictive tool to identify patients who are at high-risk of developing PIFs following radiotherapy for gynecological cancer. <h3>Materials/Methods</h3> Retrospective clinical, dosimetry and imaging data from 330 patients receiving pelvic radiotherapy for any primary gynecological cancer between January 2012 and January 2021 was collected (study approved by local ethical committee). Patient electronic records were reviewed; PIFs were diagnosed radiologically using computed tomography (CT) and magnetic resonance imaging (MRI). An auto-segmentation model for the sacrum and whole pelvis on CT-imaging was developed using a UNETR architecture to aid evaluation of pelvic radiotherapy dose and CT density. The model was validated by comparing the derived dose-volume histograms (DVHs) with those derived from manual contours. Chi-squared and Mann-Whitney tests were performed to determine associations between derived potential risk factors and PIF. Using Elastic Net Logistic Regression modelling a predictive tool to identify patients at risk of developing PIF was developed and internally validated. <h3>Results</h3> Among the 330 patients, the median follow-up was 36.6 months, and median age was 65 years. The PIF incidence was 10.9% and median interval from radiotherapy to PIF was 16 months. 86% of fractures occurred in the sacrum, 56% of patients had multiple fractures and 64% of patients were symptomatic. The auto-contouring tool of the sacrum and whole pelvis was clinically validated and, against gold-standard contours, achieved a mean DICE coefficient of 0.94, Average Surface Distance (ASD) of 0.65, and maximum absolute error for DVH curves of 3.1%. Univariant analysis found that site of primary disease, body mass index, prior diagnosis of osteopenia or osteoporosis, use of concurrent chemotherapy, V_55Gy (volume of the sacrum and whole pelvis receiving 55 Gy), and lower CT density were statistically associated with the development of PIF (p<0.05). The fully automated predictive tool to identify patients at risk of PIF using solely imaging and dosimetry data had similar accuracy to models including additional clinical features; both had a receiver-operating-characteristic (ROC) area-under-the-curve (AUC) of 0.761. The prediction tool has a sensitivity of 66%, specificity of 72% and a negative predictive value of 95%. <h3>Conclusion</h3> PIF is not uncommon in this setting, often symptomatic and strongly associated with low bone density on CT. Prediction and prevention of PIF would have an immense impact on patients and healthcare systems. We propose an automated predictive tool to identify patients at high risk, for whom effective prophylactic treatments are needed.

Impact Of Sarcopenia on Survival in Patients with Advanced Hepatocellular Carcinoma

<h3>Purpose/Objective(s)</h3> Sarcopenia is defined as skeletal muscle depletion, and is associated with poor outcomes in patients suffering from either malignancy. This study aims to evaluate the significance of pre stereotactic body radiation therapy (SBRT) sarcopenia on survival in patients of advanced hepatocellular carcinoma (HCC) with underlying cirrhosis. <h3>Materials/Methods</h3> It is a retrospective observational study done between May 2020 and Nov 2021. The data was collected from 35 patients with Barcelona Clinic Liver Cancer C group (BCLC-C) HCC, who were unsuitable for other liver-directed therapies. Patients with Child-Pugh score A5-B7 along with normal liver reserve ≥ 700cc were included. Sarcopenia was assessed from radiation planning computed tomography (CT) scans using skeletal muscles at the level of the L3 (Lumbar) vertebra. The muscles were identified at a predefined CT density of29 to +150 Hounsfield Unit (HU). The sum of the area of six abdominal muscles (erector spinae, quadrates lumborum, psoas, transversus abdominis, interior/exterior oblique, and rectus abdominis) was defined as skeletal muscle area (SMA, in cm2). SMA was normalized for height in m2 and expressed as skeletal muscle index (SMI) in cm2/m2. Sarcopenia was defined as skeletal muscle index <36 cm²/m² for men and <29 cm²/m² for women as per institutional specific cutoffs. The overall survival rates were calculated according to Sarcopenia by using the Kaplan-Meier method and were compared using the log-rank test <h3>Results</h3> In the cohort, the median age was 61 years (range 39-83 yrs). Portal vein and IVC tumor thrombosis were present in 94.3% and 22.85% patients respectively. Lung and nodal metastasis were found in 31.4% and 60% of patients respectively. The median Tumor diameter was 11 cm (range 3-21) and the median GTV volume was 563cc (80-1925cc). The median SBRT dose prescription was 40Gy (25-45Gy) in 5 to 10 fractions. Median SMI was 40.55cm²/m² (range: 22.71 to 57.09) After normalization (sarcopenia: <36 cm²/m², female; <29cm²/m^2, male), 10 patients (28.6%) had sarcopenia. Pre-SBRT sarcopenia was associated with higher PIVKA-II values (5310.5 vs 13545). At a median follow up of 8 months, median overall survival (mOS) in sarcopenic patients was lower as compared to non-sarcopenic pts (6 vs 11 months, p <0.05). SMI had no association with PFS (p = 0.63). Increasing BMI was associated with improved OS (HR 1.06, 95% CI 0.45-2.5). <h3>Conclusion</h3> Sarcopenia in HCC patients receiving SBRT is an independent prognostic factor for poor survival outcomes. Increasing BMI is associated with improved OS. Future, prospective work is needed to define the impact of sarcopenia on cancer specific outcomes for HCC patients.

Optimum Parameters for Imaging and Dose Calculation in Lung SBRT

<h3>Purpose/Objective(s)</h3> Efficiency, set up accuracy, patient comfort and accurate dose calculations are critical requirements in radiation therapy especially in stereotactic body radiotherapy (SBRT). There are several CT imaging parameters such as kV, mAs, image reconstruction algorithm filters, field of view and pitch that affect image quality used for volume delineation and dose calculation. Modifying the imaging parameters may lead to variation in Hounsfield Units (HU) that may affect the dose calculations. We investigated the relationship between the image reconstruction algorithms (Body (B) and Lung filter (L)), HU and dose distribution. We hypothesize that variation in the imaging parameters may lead to better image quality with clinically insignificant dose to target and organs at risk (OARs). <h3>Materials/Methods</h3> Ten lung SBRT patients were imaged on a 16 slice CT scanner. The standard clinical scan (C) is a B- reconstruction filter-based scan with low pitch. For selected patients, in additional to standard scan, sharp scans were acquired using greater pitch and L-filter algorithm to see the effect of density and dose calculation. Clinical workflow includes fusing the images acquired with B and L filter. Clinically B filter images are used for planning and treatment. For this study purposes, an additional plan was generated on L filtered images using appropriate HU to density curve. CT density phantom was scanned on a 16 slice CT scanner with standard Body (B) filter as well as standard images of CT density phantom were reconstructed with lung (L) filter algorithm to generate HU to physical density table for a treatment planning system and used for dose calculation. Image qualities for the two filter were evaluated visually by an attending radiation oncologist. The dosimetric differences in the target coverages were evaluated using the HU curve generated for B and L filter. <h3>Results</h3> For clinical cases, using lung SBRT protocols, planning target volume (PTV) coverage V100% were recorded. In addition to the target coverage mean physical density was recorded for the B and L filter and C-clinical scans. Average difference in the PTV physical density was 2.4%, 0.3% and 2.1% for B-C, L-C and B-L, where B stands for – B Filter density curve on the sharp scan, L – L Filter density curve on the sharp scan, C – Clinical scan. No significant differences were noted in PTV coverages for B-C 1.7% (p < 0.0004), L-C 2.03% (p < 0.0007) and B-L -0.29% (p < 0.0005) based plans for V100%. <h3>Conclusion</h3> The L filter high pitch combination improved image contrast and thus helped in contouring. No significant difference in the PTV coverage was observed when B filter HU curve was applied to sharp quality scan used for dose calculation. Thus, images acquired with L filter can be used clinically with existing B filter HU curve. Overall Differences in dosimetric parameters are insignificant compared to the small uncertainties in HU numbers.

Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort.

The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman’s rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat.

Bone metastases in midgut neuroendocrine tumors: imaging characteristics, distribution, and risk factors.

Bone metastases (BM) affect 10-30% of patients with small intestine neuroendocrine tumors (siNET), but little descriptive data are available regarding their distribution throughout the skeleton or potential risk factors. Aim of the study is to better describe the imaging characteristics, distribution, and risk factors of siNET bone metastases using 18F-FDOPA PET/CT. All patients with well-differentiated siNET who underwent an 18F-DOPA PET/CT examination in our institution were retrospectively screened between October 2017 and February 2020. Location, SUVmax and CT density of each BM were collected. Sex, metabolic tumor volume (MTV) excluding bone, and metastatic sites other than bone were studied to determine risk factors of BM. Among the 69 patients included, 11 patients (15.9%) presented BM on 18F-FDOPA (65 metastases). The most frequently involved sites were: thoracic spine, pelvic bones and ribs. About 64% of patients presented multiple BM. On coupled CT scan, 63% of BM were not visible. Using an optimal threshold of 19.2 ml, MTV was an independent predictor of BM (p = 0.004) with a derived sensitivity of 100% [65.0-100.0] and a specificity of 70.9% [57.7-81.2]. Hepatic metastatic involvement was also a significant predictor of BM (p = 0.044). The development of BM in siNETs appears to be a late event, occurring in patients with a high tumor burden and hepatic involvement. They are often multiple and predominate in the axial skeleton.

Leukocoria in Children: Findings on CT and MRI of the Principal Causes

Leukocoria is the result of an alteration in the normal red reflex of the ocular fundus, secondary to an obstruction of the normal passage of light to the fundus of the eye that produces a white light reflex. There are many ocular pathologies that can present as leukocoria, among which retinoblastoma is the most frequent. Other causes include cataracts, Coats disease, persistent fetal vasculature, coloboma, retinopathy of prematurity, vitreous hemorrhage, astrocytic hamartoma, and ocular toxocariasis. Although in many situations the diagnosis of these pathologies is clinical or possible with the use of ocular sonography, in certain circumstances, CT or MR imaging may play a very important role in the differential diagnosis. In this review article, we propose that findings such as ocular size, the presence of calcifications, intravenous contrast enhancement, MR imaging signal intensity, CT density, and other pathology-specific findings, along with some clinical data, will guide us to the cause of leukocoria. Knowledge of the most prevalent ages of presentation of these pathologies assists with establishing the final diagnosis.Learning Objectives: To understand why leukocoria occurs, to list the major causes of leukocoria in children, and to recognize the imaging findings of the most frequent causes of leukocoria and apply them in the differential diagnosis

Brain re-expansion predict the recurrence of unilateral CSDH: A clinical grading system.

ObjectiveAssessing the risk of postoperative recurrence of chronic subdural hematoma (CSDH) is a clinical focus. To screen the main factors associated with the perioperative hematoma recurrence. The brain re-expansion is the core factor of recurrence. A clinical prognostic scoring system was also proposed.MethodsWe included 295 patients with unilateral CSDH as the training group for modeling. Factors predicting postoperative recurrence requiring reoperation (RrR) were determined using univariate and multivariate regression analyses, and bivariate Pearson correlation coefficient analysis was used to exclude related factors. Receiver operating characteristic curve analysis evaluates the ability of main factors to predict RrR and determines the cut-off value of brain re-expansion rate. We developed a prognostic scoring system and conducted preliminary verification. A verification group including 119 patients with unilateral CSDH was used to verify the grading systems.ResultsThe key factors for predicting unilateral CSDH recurrence were cerebral re-expansion rate (≤ 40%) at postoperative days 7–9 (OR 25.91, p < 0.001) and the preoperative CT density classification (isodense or hyperdense, or separated or laminar types) (OR 8.19, p = 0.007). Cerebral atrophy played a key role in brain re-expansion (OR 2.36, p = 0.002). The CSDH prognostic grading system ranged from 0 to 3. An increased score was associated with a more accurate progressive increase in the RrR rate (AUC = 0.856).ConclusionsOur prognostic grading system could screen clinically high-risk RrR patients with unilateral CSDH. However, increased attention should be paid to brain re-expansion rate after surgery in patients with CSDH.

Correlation between native CT density of thyroid parenchyma and thyroid function tests.

Correlation between native CT density of thyroid parenchyma and thyroid function tests.

Comparative Role of MDCT and FDG-PET/CT in the Diagnostic Evaluation of Mediastinal Mass Lesions: An Institutional Experience.

Background Mediastinal mass lesions span a wide histopathological and radiological spectrum. Partition of the mediastinum into specific compartments aids in differential diagnosis of mass lesions, assistance in biopsies, and other surgical procedures. Multidetector row computed tomography (MDCT) is a promising three-dimensional imaging tool allowing substantial anatomical volumes to be routinely covered with isotropic submillimeter spatial resolution to precisely localize lesions and biopsy needles for both benign and malignant disease lesions of the mediastinum. Objective The aim of this study was to categorize mass lesions according to the mediastinal compartments to study their MDCT characteristics and to provide a comparative role of fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in the diagnostic evaluation of mediastinal mass lesions. Materials and Methods Patients with clinical or radiological suspicion of mediastinal lesions on the basis of an abnormal chest radiograph were referred to the department of radiodiagnosis at a tertiary care center between April 2015 and December 2019 for MDCT evaluation. A total of 80 cases were correlated with the histopathological diagnosis excluding aneurysms. Size, CT density (Hounsfield unit [HU] mean), and maximum standardized uptake value (SUV max ) of mediastinal and chest wall lesions were determined on FDG-PET/CT. Results This study included a total of 102 cases, 72 males and 29 females. Mediastinal mass lesions were most common in the age group 46 to 60 years. Anterior mediastinum ( n = 43, 42.2%) is the most commonly involved compartment followed by posterior mediastinum ( n = 37, 35.9%) and middle mediastinum ( n = 22, 21.8%). Transcompartmental involvement is more commonly seen involving the anterior and middle mediastinum. The SUV max , HU mean, and size were higher in malignant cases ( p = 0.001, p = 0.003, and p = 0.004, respectively). The current study found a cutoff value of 4.61 for SUV max to discriminate benign lesions from malignant ones with a sensitivity and specificity of 73.7 and 75.9%, respectively (area under the curve: 0.841, 95% confidence interval: 0.793–0.965, p = 0.0001). The values of SUV max and HU mean were higher in solid benign lesions than those of cystic benign lesions ( p = 0.007 and p = 0.003, respectively). Conclusion In the current study, MDCT has high diagnostic accuracy of ∼94% overall as compared with histopathology, and 97 and 92% for benign and malignant lesions, respectively, in the evaluation of mediastinal mass lesions. FDG-PET/CT may be complementary to conventional imaging methods for the evaluation of mediastinal and chest wall mass lesions. However, confirmatory tissue sampling is required to confirm PET positive findings for the definite diagnosis.

Dosimetric Evaluation of Dose Calculation Uncertainties for MR-Only Approaches in Prostate MR-Guided Radiotherapy

Purpose: Magnetic resonance imaging guided radiotherapy (MRgRT) allows treatment plan adaptation on the MRI of the day. For dose calculations, a structure-specific bulk relative electron density (RED) overwrite derived from a planning computed tomography (CT) poses as one possible treatment workflow. However, this approach introduces uncertainties due to assignment of mean densities and requires a planning CT. The aim of this study was to investigate the uncertainty of the used patient-specific (PSCT) dose calculation in contrast to the correct calculation on a CT and compare to MR-only workflows using population-based bulk ED (PBCT) and artificial intelligence–based pseudo-CTs (AICT).Methods: Twenty primary prostate cancer patients treated on the 1.5 T MR-Linac were chosen from the clinical database, based on best visual congruence between the planning CT and daily MRI. CT-based reference dose distribution was compared to different pseudo-CT approaches. 1) For PSCT, mean REDs for the femur, pelvis, sacrum, rectum, bladder, and patient were assigned based on individual mean CT densities. 2) Population-based mean REDs were derived based on 50 previous, independent patients and assigned to the structures for the PBCT approach. 3) An AI model for pseudo-CT generation was trained using end-to-end ensembled self-supervised GANs and used to create AICTs from T2w-MRIs. For comparison, the CT was registered to the MRI, structures rigidly propagated, and treatment plans recalculated. Differences of DVH parameters were analyzed, and dose distributions were compared using gamma analysis.Results: All approaches were able to reproduce the dose distribution accurately, according to a gamma criterion of 3%/3 mm, with pass rates greater than 98%. Applying a 2%/2 mm criterion, the median gamma pass rates for PSCT, PBCT, and AICT resulted in 98.6%, 98.2%, and 99.0%, respectively. The median differences for PTV D98% resulted in 0.13 Gy for AICT, −0.31 Gy for PBCT, and −0.32 Gy for PSCT. The OAR-related DVH parameter showed similar results between the three investigated methods.Conclusion: In this study, a detailed analysis of uncertainties of MR-only treatment planning concepts for pelvic MRgRT was performed. Both a PBCT and an AICT approach, which bypass the need for a planning CT, may be considered clinically acceptable while reducing imaging dose and registration issues.

High Actin Expression in Thrombus of Acute Ischemic Stroke Can Be a Biomarker of Atherothrombotic Origin Stroke.

BackgroundAs the treatment target, the imaging information and histologic characteristics of the thrombus may differ according to the stroke subtype. This study aimed to provide the correlative study of stroke etiology with the non-contrast CT, and histological composition of retrieved clots in acute ischemic stroke (AIS).Materials and MethodsA total of 94 patients with AIS who underwent the endovascular treatment with successfully retrieved clots from January 2017 to October 2020 were enrolled in the present study. Histological analysis was performed using hematoxylin and eosin (H&E) staining and immunostaining with CD3, CD20, CD105, and actin antibodies. CT obtained at the patients' admission was to measure the attenuation and volume of all thrombus.ResultsA total of 94 subjects were included in this study. Fifty-six patients were classified as cardioembolic (CE), and 38 were classified with large-artery atherosclerosis (LAA). The subjects with LAA tend to exhibit higher actin and CD105 levels, and lower Hounsfield Unit (HU) values than subjects with CE. After adjusting for confounders, the actin was positively correlated with CD105 but not with HU values. Logistics regression shows actin was valuable for the prediction of LAA (OR, 1.148; 95% CI, 1.075–1.227; p < 0.001), even adjusted for age, sex, and intervention type (OR, 1.129; 95% CI, 1.048–1.216; p = 0.001), CT density and CD105 (OR, 1.161; 95% CI, 1.056–1.277; p = 0.002). Actin levels have a strong accuracy in differentiating LAA from CE, especially combined with CT density and CD105, which yielded a sensitivity of 63.2%, a specificity of 89.3%, with the area under the curve (AUC) at 0.821 (95% CI, 0.731–0.912).ConclusionOur findings suggest that actin's level was a major factor differentiating atherothrombotic origin strokes from the cardioembolic stroke.Clinical Trial RegistrationChiCTR2100051173.

Investigation on the incidence and risk factors of lung cancer among Chinese hospital employees.

ObjectiveIn recent years, the lung cancer incidence has grown and the population is younger. We intend to find out the true detection rate of pulmonary nodules and the incidence of lung cancer in the population and search for the risk factors.MethodHospital employees ≥40 years old who underwent low‐dose computed tomography (CT) lung cancer screening from January 2019 to March 2022 were selected to record CT‐imaging characteristics, pathology, staging, and questionnaires to investigate past history, smoking history, diet, mental health, etc. PM2.5 and radiation intake in radiation‐related occupation received monitoring in hospital.ResultThe detection rate of suspicious pulmonary nodules was 9.1% (233/2552), and the incidence rate of lung cancer (including adenocarcinoma in situ) was 4.0% (103/2552). Morbidity among doctors, nurses, technicians, administers, and logistics was no difference (p = 0.184), but higher in women than in men (4.7% vs 2.4% p = 0.002). The invasiveness increased with age and CT density of nodules (p = 0.018). The relationship between lung cancer morbidity and PM2.5 was not clear (p = 0.543); and no lung cancer has been found in employees related ionizing radiation.ConclusionThe high screening rate has brought about a high incidence of lung cancer. At present, the risk factor analysis of lung cancer based on small samples cannot find the direct cause. Most of the ground glass opacity (GGO)s detected by LDCT screening are indolent, but there are also rapidly progressive lung cancer. A predictive model to identify active and indolent GGO is necessary.

Computed Tomography Density as a Bio-marker for Histologic Grade of Otosclerosis: A Human Temporal Bone Pathology Study.

Computed tomography (CT) density measurement can be used to objectively distinguish otosclerosis from normal bone and to determine histologic grades of otosclerosis. Otosclerosis can be seen on CT as subtle radiolucent areas. An objective radiologic measurement that corresponds to known otosclerosis pathology may improve diagnostic accuracy, and could be used as a radiologic biomarker for otosclerosis grade. A blinded, randomized evaluation of both histologic grade on histopathology slides and CT density measurement was performed on 78 human temporal bone specimens (31 with otosclerosis and 47 controls) that had undergone high-resolution multi-detector CT before histologic processing. Assessments were performed at 11 regions of interest (ROIs) in the otic capsule for each specimen. The CT density measurement mean (Hounsfield Units) ± standard deviation for all ROIs (Nos. 1-9) was 2245 ± 854 for grade 0 (no otosclerosis, n = 711), 1896 ± 317 for grade 1 (inactive otosclerosis, n = 109), and 1632 ± 255 for grades 2 and 3 combined (mixed/active otosclerosis, n 35). There was a strong inverse correlation of CT density to histologic grade at ROIs Nos. 1-5 (ANOVA, p < 0.0001). The inter-rater reliability for CT density was very good (correlation coefficient 0.87, p < 0.05). ROC curves suggested a cut-off of 2,150HU to distinguish otosclerosis from normal bone, and 1,811HU to distinguish low grade from mixed/high grade otosclerosis. In human temporal bone specimens, CT density may be used to distinguish normal bone from bone involved by otosclerosis. A higher histologic grade (i.e., indicating a more active otosclerotic focus) correlated with lower density.

Microbiological quality of the water in collection areas and the tissue of Mytella falcata-Cananéia (SP, Brazil).

Changes in fauna and abiotic factors in estuaries are a consequence of their exploitation; thus, bivalve mollusks, as they filter, are widely used as environmental bioindicators. The aim of this study was to analyze the existence of seasonal variation in the concentration of total coliforms (TC) and thermotolerant coliforms (Ct), in addition to correlating the data obtained with the salinity and temperature in collection areas of Mytella falcata and the soft tissue cultivated in the Estuarine Complex of Cananéia. Two biweekly samples of water and tissue were taken, for 12 consecutive months, in nine cultivation areas of M.falcata. The analysis of the water samples showed that the Fisheries Institute, Mosquiteiro, and Itapitangui have high TC densities, with respective annual averages of 772.22, 592.67, and 563.75 most probable number (MPN).100 ml-1 . The highest concentrations of TC and Ct occurred in the summer, in most areas. There was a decrease in both TC and Ct with increasing salinity. However, there was an increase in Ct with increasing temperature. The soft tissue showed TC densities from 9 to 26 MPN.100 ml-1 and Ct densities from 6 to 14 MPN.100 ml-1 , displaying the highest counts in the summer. Places where coliforms were found in high concentrations could indicate contamination, because Ct do not support higher salinities for a long time. PRACTITIONER POINTS: The general mean was 77.64 (total coliforms) and 39.35 (thermotolerant) MPN.100 ml-1 . Annual average (thermotolerant) exceeded the permitted Brazilian limit in five points. Higher concentrations of total and thermotolerant coliforms occurred in the summer. In mollusk's tissue, concentrations of thermotolerant were 6.30 to 26.16 MPN.100 g-1 . Coliforms' MPN varied with increasing salinity and temperature.

Clinical CT densitometry for wooden cultural heritage analysis validated by FTIR and Raman spectroscopies

The identification and characterization of wood material represent an ongoing challenge for artefacts of interest in cultural heritage. Fourier transforms infrared spectroscopy (FTIR) and micro-Raman (MRS) spectroscopies and more recently Surface-Enhanced Raman Scattering (SERS), being non-destructive techniques, have been largely used for the analysis of painted wood. In this work, for the first time, the X-ray Computed Tomography (CT), using a CT medical scanner, was adopted to discriminate three types of wood, usually used in the construction of heritage objects. Wood interior features have been identified in CT images processed through the volumetric rendering technique (VRT), without the need to destructively “take out” a piece of the sample. The information at the macroscopic level collected by CT (density, volumes, morphology, etc.) was enriched by the evidence, at the microscopic level, obtained by the Raman and FTIR spectroscopic techniques. So, the samples have been classified in softwood and hardwood, with the advantage with respect to the conventional analytical methods to be able to distinguish specific structures within the cell walls only through the CT diagnostic technique. Ultimately, a new non-destructive approach is proposed to analyze wood-based heritage objects, but which can be also extended to other materials (i.e., pigments, glues, consolidants).

What is the “washout” of hepatocellular carcinoma as observed on the equilibrium phase CT?: consideration based on the concept of extracellular volume fraction

PurposeTo verify the hypothesis that extracellular volume fraction (ECV) and precontrast CT density are the main determinants of washout of hepatocellular carcinoma (HCC) at the equilibrium phase CT.Materials and methodsBetween 2018 and 2020, patients with surgically resected HCC were recruited who had undergone preoperative 4-phase CT. Those larger than 6 cm were excluded to minimize the possibility of intratumoral hemorrhage or degeneration. Two radiologists reviewed the whole images in consensus and divided cases into washout positive and negative groups. Washout positive group at the equilibrium phase was defined as “HCC showing relatively low density as compared to the surrounding background liver (BGL), irrespective of the presence of early enhancement or fibrous capsule”. Several clinico-pathological and radiological features, including ECV and precontrast CT density, were correlated to the presence of washout, using uni- and multi-variable analyses.Results27 HCC in 24 patients met the inclusion criteria. 22 (82%) and five HCC belonged to washout positive and negative groups, respectively. Univariable analysis revealed ECV of HCC and BGL, ECV difference between HCC and BGL, and presence of fibrous capsule on the equilibrium phase CT were the significant factors. Multivariable analysis showed ECV of HCC and BGL, and precontrast CT density of BGL, were the independently significant factors related to washout, suggesting washout is more likely observed with lower HCC ECV, higher BGL ECV, and higher BGL precontrast CT density.ConclusionMajor determinants of washout of HCC may be ECV of HCC and BGL, and precontrast CT density of BGL.

Correlation Analysis between Tamoxifen and Lumbar Intervertebral Disc Degeneration: A Retrospective Case-Control Study.

Objectives To investigate the correlation between tamoxifen (TAM) and lumbar intervertebral disc (IVD) degeneration (IVDD). Methods The patients who visited the department of spine surgery from January 2015 to December 2020 were retrospectively reviewed. Those with a history of breast cancer surgery were identified and their data were collected. These data included patients' age, body mass index (BMI), menstrual history, postoperative history, drug treatment plan, and imaging data. The participants were divided into the TAM group and the non-TAM group. Lumbar IVDD was assessed by lumbar lordosis (LL), vertebral CT density, lumbar disc height index (DHI), Modic changes, and modified Pfirrmann grading score. SPSS 20 was used for statistical analysis. Results A total of 75 patients were included in this study, 46 patients in the TAM group and 29 patients in the non-TAM group. No significant differences were present in age, BMI, postoperative history, LL, and vertebral CT density between the two groups. The DHI of L1/2 and L2/3 in the TAM group was lower compared to the non-TAM group (P=0.038 and P=0.034, respectively), while comparisons regarding the DHI of L3/4, L4/5, and L5/S1, and the average DHI between TAM and non-TAM groups were not significant. The modified Pfirrmann grading scores of the L1/2 and L2/3 IVDs in the TAM group were higher than those in the non-TAM group (P=0.004 and P=0.025, respectively). Comparisons of L3/4, L4/5, and L5/S1 between the two groups were not significant. The comparisons regarding the occurrence of Modic changes did not show a significant difference between the TAM and non-TAM groups. Conclusions This study indicates that there might be some positive correlation between TAM use and lumbar IVDD. In particular, the degeneration of L1/2 and L2/3 has shown a correlation with TAM use.

Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients

The aim of this study was to compare whole lung CT density histograms to predict critical illness outcome and hospital length of stay in a cohort of 80 COVID-19 patients. CT chest images on segmented lungs were retrospectively analyzed. Functional Principal Component Analysis (FPCA) was used to find the main modes of variations on CT density histograms. CT density features, the CT severity score, the COVID-GRAM score and the patient clinical data were assessed for predicting the patient outcome using logistic regression models and survival analysis. ROC analysis predictors of critically ill status: 87.5th percentile CT density (Q875)—AUC 0.88 95% CI (0.79 0.94), F1-CT—AUC 0.87 (0.77 0.93) Standard Deviation (SD-CT)—AUC 0.86 (0.73, 0.93). Multivariate models combining CT-density predictors and Neutrophil–Lymphocyte Ratio showed the highest accuracy. SD-CT, Q875 and F1 score were significant predictors of hospital length of stay (LOS) while controlling for hospital death using competing risks models. Moreover, two multivariate Fine-Gray regression models combining the clinical variables: age, NLR, Contrast CT factor with either Q875 or F1 CT-density predictors revealed significant effects for the prediction of LOS incidence in presence of a competing risk (death) and acceptable predictive performances (Bootstrapped C-index 0.74 [0.70 0.78]).

Virtual non-contrast detector-based spectral CT predictably overestimates tissue density for the characterisation of adrenal lesions compared to true non-contrast CT.

To establish if virtual non-contrast (VNC) images generated from contrast-enhanced detector-based spectral CT could replace true non-contrast (TNC) imaging for the characterisation of adrenal masses. TNC and VNC images were retrospectively reviewed for 39 patients with one or more adrenal lesions who underwent contrast-enhanced spectral CT of the upper abdomen. Lesions were categorised as either 'adenoma' or 'indeterminate/other lesion' based on current reference standards. The CT density of each lesion was measured on both image sets by two readers and compared using Wilcoxon signed-rank test. ROC analysis with Youden's J index method was performed to determine the optimal attenuation cut-off for diagnosing benign adenoma on VNC images. Forty-four lesions were included, 37 of which were diagnosed as adenomas. There were significant differences between TNC and VNC measurements for both readers (mean difference 9.1 HU for reader 1; 9.8 HU for reader 2; p < 0.01). Optimal attenuation thresholds for diagnosing adenomas on VNC were 25.3 HU (reader 1) and 23.9 HU (reader 2) for the entire population, and 18.3 HU (reader 1) and 19.7 HU (reader 2) for lipid-rich adenomas < 10 HU on TNC imaging. There is insufficient evidence to support the use of VNC as a substitute for TNC images in the characterisation of adrenal lesions. VNC using a detector-based spectral CT scanner shows a predictable increase in attenuation values compared to TNC. Thus, future studies might be better directed towards finding a new threshold value for diagnosing benign adrenal adenomas on VNC imaging.