Potential of high dimensional radiomic features to assess blood components in intraaortic vessels in non-contrast CT scans

Anemia detection and quantification in contrast-enhanced CT scans on a novel photon-counting detector CT: A prospective proof-of-concept study

PURPOSE

To correlate CT values of the blood pool on VNC series with serum hemoglobin values for the detection of anemia in oncologic patients undergoing contrast-enhanced PCD-CT scans.

METHODS

This prospective study (NCT04989192) included consecutive oncologic patients undergoing contrast-enhanced CT on a novel PCD-CT system between 08/2021 and 01/2022. The interval between complete blood count (CBC) and CT scan acquisition had to be no more than seven days. CT-values of the blood pool were measured on 70 keV VMI series (CT-values(BP)70keV) and on VNC series (CT-values(BP)VNC) at five anatomic positions (left atrium, left ventricle, main pulmonary artery, ascending and descending aorta) and averaged per patient. Pearson correlation analyses and ROC analyses were performed to identify relations between CT-values(BP)VNC, CBC parameters, and degrees of anemia as defined by the WHO (no anemia, mild, moderate, severe anemia).

RESULTS

A total of 329 patients (age 68 ± 12 years; 200 men) were included. CT-values(BP)VNC showed a strong linear correlation to serum hemoglobin (r2 = 0.80, p <.001) and hematocrit (r2 = 0.76, p <.001) and were significantly different between anemia subgroups in both women and men (ΔHU: 3.5-11.4; all p <.01). ROC analyses yielded high diagnostic performance for the identification of patients without anemia, patients without and with mild anemia, and patients with severe anemia using gender-specific cutoffs for CT-value(BP)VNC (all AUC's > 0.90).

CONCLUSIONS

The spectral information inherent in PCD-CT acquisitions allows the detection and quantification of anemia in contrast-enhanced CT acquisitions of oncologic patients with high diagnostic accuracy.

Feasibility of thoracic CT in assessing anemia for aplastic anemia patients undergoing allogeneic hematopoietic stem cell transplantation

BACKGROUND

Anemia is an important clinical symptom for aplastic anemia (AA) patients who are suffered with peripheral pancytopenia.

OBJECTIVE

To evaluate the accuracy of diagnosing anemia with non-invasive chest computed tomography (CT) for AA patients.

METHODS

The CT attenuation of left ventricular (LV) cavity and interventricular septum (IVS) on unenhanced thoracic CT images of AA patients are retrospectively analyzed, including 84 AA patients in pre-transplant and 1-month (n = 82), 2-month (n = 72), 3-month (n = 75), 6-month (n = 74) and 12-month (n = 70) followed patients in post-transplant. The difference (IVS-LV) and ratio (LV/IVS) of the CT attenuation between LV cavity and interventricular septum are calculated. Serum hemoglobin is estimated within 24 hours of CT imaging. The CT attenuations of IVS-LV and LV/IVS are correlated with hemoglobin, and their variation tendency is analyzed during the treatment of a-HSCT. A receiver operating characteristic (ROC) curve analysis is then performed for the diagnosis of anemia.

RESULTS

The CT attenuations of IVS-LV and LV/IVS well correlate with hemoglobin (r = -0.618 and 0.628, respectively, P <  0.001). The variation tendency of IVS-LV and LV/IVS is similar to that of hemoglobin with opposite directions during one-year follow-up of a-HSCT. When a threshold of CT attenuation of IVS-LV and LV/IVS is set at 11.5HU and 0.77, respectively, both the sensitivity and specificity in diagnosing anemia are good (74.7% and 73.8% in CT attenuation of IVS-LV; 77.4% and 70.4% in LV/LVS, respectively).

CONCLUSIONS

Both CT attenuation of LV/IVS and IVS-LV had similar accuracy in diagnosing anemia for AA patients. The non-invasive chest CT can offer a new possibility to complementarily evaluate anemia for AA patients in the diagnostic radiology reports.

An Intelli MVC: An intelligent majority voting and heuristic-based hybrid classifier to predict high blood pressure

High Blood Pressure (HBP) is one of the major significant medical concerns of many people around the globe today. HBP is so common symptom many people across the globe are experiencing, irrespective of age, gender, region, and religion. HBP prediction ahead of time can help the person to avoid the consequences such as heart stroke, kidney failure, eye damage, sexual dysfunction, and even death. HBP prediction in advance is a challenging issue as it is associated with many biopsychosocial factors. Heuristic and meta-heuristic-based Machine Learning Models (MLM) exclusively supervised machine learning techniques are becoming part and parcel of medical data diagnosis. However, the reliability of outcome, usability, and understandability of such stand-alone models in processing medical data in real-time are not up to the mark. To overcome such limitations, in this paper we proposed an intelligent majority voting and heuristic-based user-friendly hybrid classifier to predict HBP (An Intelli MOC). The model considers AA-AOC (Anger level, Anxiety level-Age, Obesity level, and Cholesterol level) of a person to predict the HBP of a person. The proposed model is said to be majority vote-based and hybrid as it considers the output of three classifiers and assigns the count for each decision class. The model is said to be heuristic-based as it uses a mathematical and Fuzzy approach in obtaining the fuzzified values of each attribute in AA-AOC. The experiments are conducted on real-time data set collected from a medical diagnostic center Doctor C, Hyderabad, India. The model is executed on 1200 data records, 65% of data is used to train the model and 35% of data is used to test the model. The output of the model proved that the proposed model outperformed in terms of accuracy, precision, recall, and F-measure compared with all available state-of-the-art, existing MLM.

Quantitative analysis of in-TIPS thrombosis in abdominal CT

Purpose

To identify transjugular intrahepatic portosystemic shunt (TIPS) thrombosis in abdominal CT scans applying quantitative image analysis.

Materials and methods

We retrospectively screened 184 patients to include 20 patients (male, 8; female, 12; mean age, 60.7 ± 8.87 years) with (case, n = 10) and without (control, n = 10) in-TIPS thrombosis who underwent clinically indicated contrast-enhanced and unenhanced abdominal CT followed by conventional TIPS-angiography between 08/2014 and 06/2020. First, images were scored visually. Second, region of interest (ROI) based quantitative measurements of CT attenuation were performed in the inferior vena cava (IVC), portal vein and in four TIPS locations. Minimum, maximum and average Hounsfield unit (HU) values were used as absolute and relative quantitative features. We analyzed the features with univariate testing.

Results

Subjective scores identified in-TIPS thrombosis in contrast-enhanced scans with an accuracy of 0.667 – 0.833. Patients with in-TIPS thrombosis had significantly lower average (p < 0.001), minimum (p < 0.001) and maximum HU (p = 0.043) in contrast-enhanced images. The in-TIPS / IVC ratio in contrast-enhanced images was significantly lower in patients with in-TIPS thrombosis (p < 0.001). No significant differences were found for unenhanced images. Analyzing the visually most suspicious ROI with consecutive calculation of its ratio to the IVC, all patients with a ratio < 1 suffered from in-TIPS thrombosis (p < 0.001, sensitivity and specificity = 100%).

Conclusion

Quantitative analysis of abdominal CT scans facilitates the stratification of in-TIPS thrombosis. In contrast-enhanced scans, an in-TIPS / IVC ratio < 1 could non-invasively stratify all patients with in-TIPS thrombosis.

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Quantitative image analyses of CT scans allow the diagnosis of in-TIPS thrombosis.

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Negative quantitative image analysis may reduce the necessity of an angiography.

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Unenhanced CT scans have no additional benefit for diagnosis of in-TIPS thrombosis.