Diagnostic accuracy of third-generation dual-source dual-energy CT: a prospective trial and protocol for clinical implementation

Automated Kidney Stone Composition Analysis with Photon-Counting Detector CT, a Performance Study-A Phantom Study

BACKGROUND

For treatment of urolithiasis, the stone composition is of particular interest, as uric acid (UA) stones can be treated by chemolitholysis. In this ex vivo study, we employed an advanced composition analysis approach for urolithiasis utilizing spectral data obtained from a photon-counting detector CT (PCDCT) to differentiate UA and non-UA stones. Our primary objective was to assess the accuracy of this analysis method.

METHODS

A total of 148 urinary stones with a known composition that was measured by the standard reference method infrared spectroscopy (reference) were placed in an abdomen phantom and scanned in the PCDCT. Our objectives were to assess the stone detection rates of PCDCT and the accuracy of the prediction of the stone composition in UA vs non-UA compared to the reference.

RESULTS

Automated detection recognized 86.5% of all stones, with best detection rate for stones larger > 5 mm in diameter (95.4%, 88.8% for stones larger than 3 mm, 94.7% for stones larger than 4 mm). Depending on the volume, we found a recognition rate of 92.8% for stones larger than 20 mm3 and 94.0% for stones with more than 30 mm3. Prediction of UA composition showed an overall sensitivity and a positive predictive value of 66.7% and a specificity and negative predictive value of 94.5%. Best diagnostic values volume wise were found by only including stones with a larger volume than 30 mm3, there we found a sensitivity of 91.7%, and a specificity of 92.4%. Sensitivity in dependance of the largest diameter was best for stones larger than 5 mm (85.7%), but specificity decreased with increasing diameter (to 91.3%).

CONCLUSION

Automated urinary stone composition analysis with PCDCT showed a good automated detection rate of 86.5% up to 95.4% depending on stone diameter. The differentiation between non-UA and UA stones is performed with an NPV of 94.5% and a PPV of 66.7%. The prediction probability of non-UA stones was very good. This means the automatic detection and differentiation algorithm can identify the patients which will not profit from chemolitholysis.

Demonstrating the Efficacy of Dual Energy Computer Tomography with Gemstone Spectral Imaging Software to Determine Mixed and Single Composition ex vivo Urolithiasis

Objective

To assess the capability of determining the mixed chemical composition of urinary stones using spectral imaging properties of Dual Energy Computed Tomography (DECT) Gemstone Spectral Imaging (GSI) software.

Material and Methods

Twenty-six single and 24 mixed composition ex vivo urinary stones with known chemical composition determined by Fourier-transform infrared spectroscopy (FTIR) prior to this project were scanned with DECT imaging and GSI in vitro. The major components of the stones included Uric Acid (UA), Calcium Oxalate (CaOx), Calcium Phosphate (CaP), Magnesium Ammonium Phosphate (MAP), and Cystine (Cys). A histogram to display the distribution of the effective atomic number (Z-eff) of each pixel of the tested area, spectral curve (40-140 keV, with 10 keV interval) and Hounsfield Units (HU) of each stone scanned was provided with analysis of monochromatic images at 140 keV in the axial plane.

Results

The overall pooled sensitivity, specificity, and accuracy of DECT for identifying major stone composition were 0.802, 0.831, and 0.807, respectively, with a 95% confidence interval. Accuracy was 100% for identifying UA and Cys stones.

Conclusion

DECT is a superior imaging modality when compared to low dose computed tomography kidney ureter bladder scans. It allows for improved characterization of major components of urinary stones, in an accurate, non-invasive approach to pre-treatment. This can translate to urologists having greater confidence in determining patient suitability for medical or surgical management of their renal stones, in clinical practice.

Diagnostic performance and feasibility of dual-layer detector dual-energy CT for characterization of urinary stones in patients of different sizes

BACKGROUND

Urinary stones are frequently encountered in urology and are typically identified using non-contrast CT scans. Dual-energy CT (DECT) is a valuable imaging technique that produces material-specific images and allows for precise assessment of stone composition by estimating the effective atomic number (Zeff), a capability not achievable with the conventional single-energy CT's attenuation measurement method.

PURPOSE

To investigate the diagnostic performance and image quality of dual-layer detector DECT (dlDECT) in characterizing urinary stones in patients of different sizes.

METHODS

All consecutive dlDECT examinations with stone protocol and presence of urinary stones between July 2018 and November 2019 were retrospectively evaluated. Two radiologists independently reviewed 120 kVp and color-overlay Zeff images to determine stone composition (reference standard = crystallography) and image quality. The objective analysis included image noise and Zeff values measurement.

RESULTS

A total of 739 urinary stones (median size 3.7 mm, range 1-35 mm) were identified on 177 CT examinations from 155 adults (mean age, 57 ± 15 years, 80 men, median weight 82.6 kg, range 42.6-186.9 kg). Using color-overlay Zeff images, the radiologists could subjectively interpret the composition in all stones ≥ 3 mm (n = 491). For stones with available reference standards (n = 74), dlDECT yielded a sensitivity of 80% (95%CI 44-98%) and a specificity of 98% (95%CI 92-100%) in visually discriminating uric acid from non-uric acid stones. Patients weighing > 90 kg and ≤ 90 kg had similar stone characterizability (p = 0.20), with 86% of stones characterized in the > 90 kg group and 87% in the ≤ 90 kg group. All examinations throughout various patients' weights revealed acceptable image quality. A Zeff cutoff of 7.66 accurately distinguished uric acid from non-uric acid stones (AUC = 1.00). Zeff analysis revealed AUCs of 0.78 and 0.91 for differentiating calcium-based stones from other non-uric stones and all stone types, respectively.

CONCLUSION

dlDECT allowed accurate differentiation of uric acid and non-uric acid stones among patients with different body sizes with acceptable image quality.

CLINICAL IMPACT

The ability to accurately differentiate uric acid stones from non-uric acid stones using color-overlay Zeff images allows for better tailored treatment strategies, helping to choose appropriate interventions and prevent potential complications related to urinary stones in patient care.

[Diagnostic values of urinary citrate for kidney stones in patients with primary gout]

OBJECTIVE

To evaluate the relationship between 24 h urinary ion content and kidney stones, and to explore the diagnostic values of kidney stone in primary gout patients.

METHODS

Patients diagnosed with primary gout had ultrasound scanning of both feet and kidneys in Peking University First Hospital from Jan. 2020 to May 2021. Their clinical characteristics were compared between the positive and negative kidney stone groups, and the relationship between kidney stone and urinary ion composition were analyzed. Risk factors of kidney stone were analyzed. The explored diagnostic values were evaluated for urinary oxalate and citrate according with uric acid kidney stones by dual-energy computed tomography (DECT).

RESULTS

Among the 100 gouty patients, 80 patients had uric acid crystal deposition in lower joints of extremity by ultrasonography, 61 patients had kidney stone, and 34 had kidney uric acid stones by DECT. All the multiple kidney stones were proved as uric acid kidney stones by DECT. Compared with patients without kidney stone group proved by ultrasonography, patients with kidney stone had longer gouty duration [(48.7±26.6) months vs. (84.0±30.6) months, P=0.01], higher 24 h urinary oxalate [(20.1±9.6) mg vs. (28.6±20.7) mg, P=0.001] and lower 24 h urinary citrate [(506.3±315.4) mg vs. (355.7±219.6) mg, P=0.001]. Compared with the patients without kidney stone by DECT, the patients with uric acid kidney stone also had longer disease duration [(49.1±28.4) months vs. (108.3±72.2) months, P=0.001], higher 24 h urinary oxalate [(23.6±16.9) mg vs. (28.5±18.8) mg, P < 0.05], lower 24 h urinary citrate [(556.0±316.3) mg vs. (391.7±261.2) mg, P < 0.05], higher serum uric acid [(466.2±134.5) μmol/L vs. (517.2±18.1) μmol/L, P < 0.05] and higher 24 h urinary uric acid [(1 518.1±893.4) mg vs. (1 684.2±812.1) mg, P < 0.05]. Logistic regression analysis showed long gout disease duration (OR=1.229, 95%CI: 1.062-1.522, P < 0.05), high serum uric acid level (OR=1.137, 95%CI: 1.001-1.213, P=0.01), low 24 h urinary citrate (OR=0.821, 95%CI: 0.659-0.952, P=0.01) were all risk factors of kidney stones by ultrasonography. Also, long gout disease duration (OR=1.201, 95%CI: 1.101-1.437, P=0.005), high serum creatine uric level (OR=1.145, 95%CI: 1.001-1.182, P=0.04), low 24 h urinary citrate (OR=0.837, 95%CI: 0.739-0.931, P=0.02) were all risk factors of kidney uric acid stones by DECT.

CONCLUSION

Long disease duration and low 24 h urinary citrate were risk factors for kidney stones.

Imaging in stone diagnosis and surgical planning

PURPOSE OF REVIEW

Radiological imaging techniques and applications are constantly advancing. This review will examine modern imaging techniques in the diagnosis of urolithiasis and applications for surgical planning.

RECENT FINDINGS

The diagnosis of urolithiasis may be done via plain film X-ray, ultrasound (US), or contrast tomography (CT) scan. US should be applied in the workup of flank pain in emergency rooms and may reduce unnecessary radiation exposure. Low dose and ultra-low-dose CT remain the diagnostic standard for most populations but remain underutilized. Single and dual-energy CT provide three-dimensional imaging that can predict stone-specific parameters that help clinicians predict stone passage likelihood, identify ideal management techniques, and possibly reduce complications. Machine learning has been increasingly applied to 3-D imaging to support clinicians in these prognostications and treatment selection.

SUMMARY

The diagnosis and management of urolithiasis are increasingly personalized. Patient and stone characteristics will support clinicians in treatment decision, surgical planning, and counseling.

Clinical Low Dose Photon Counting CT for the Detection of Urolithiasis: Evaluation of Image Quality and Radiation Dose

The purpose of this study was the evaluation of image quality and radiation dose parameters of the novel photon counting CT (PCCT, Naeotom Alpha, Siemens Healthineers) using low-dose scan protocols for the detection of urolithiasis. Standard CT scans were used as a reference (S40, Somatom Sensation 40, Siemens Healthineers). Sixty-three patients, who underwent CT scans between August and December 2021, were retrospectively enrolled. Thirty-one patients were examined with the PCCT and 32 patients were examined with the S40. Radiation dose parameters, as well as quantitative and qualitative image parameters, were analyzed. The presence of urolithiasis, image quality, and diagnostic certainty were rated on a 5-point-scale by 3 blinded readers. Both patient groups (PCCT and S40) did not differ significantly in terms of body mass index. Radiation dose was significantly lower for examinations with the PCCT compared to the S40 (2.4 ± 1.0 mSv vs. 3.4 ± 1.0 mSv; p < 0.001). The SNR was significantly better on images acquired with the PCCT (13.3 ± 3.3 vs. 8.2 ± 1.9; p < 0.001). The image quality of the PCCT was rated significantly better (4.3 ± 0.7 vs. 2.8 ± 0.6; p < 0.001). The detection rate of kidney or ureter calculi was excellent with both CT scanners (PCCT 97.8% and S40 99%, p = 0.611). In high contrast imaging, such as the depiction of stones of the kidney and the ureter, PCCT allows a significant reduction of radiation dose, while maintaining excellent diagnostic confidence and image quality. Given this image quality with our current protocol, further adjustments towards ultra-low-dose CT scans appear feasible.

The combination of mean and maximum Hounsfield Unit allows more accurate prediction of uric acid stones

Based on mean Hounsfield Unit (HuMean), we aimed to evaluate the additional use of standard deviation of Hounsfield Unit (HuStd), minimum Hounsfield Unit (HuMin), and maximum Hounsfield Unit (HuMax) in noncontrast computed tomography (NCCT) to evaluate uric acid (UA) stones more accurately. The data of patients who underwent the NCCT examination and infrared spectroscopy in our hospital from August 2017 to December 2021 were analyzed retrospectively. Based on CT scans, the HuMean, HuStd, HuMin, and HuMax of all patients were measured. The patients were divided into groups according to the stone composition. The attenuation value of mixed stones was in the middle of their pure stones. Except for Str, statistically significant differences between UA stones and other pure stones were observed for HuMean, HuStd, HuMin, and HuMax. A moderate correlation was found between HuMean, HuStd, HuMin, and HuMax and UA stones (r_s showed -0.585, -0.409, -0.492, and -0.577, respectively). Receiver operator characteristic (ROC) curve showed that the area under the curve (AUC) of HuMean and HuMax were higher than those of HuStd and HuMin (AUC = 0.896, AUC = 0.891 vs. AUC = 0.777, AUC = 0.833). Higher AUC (0.904), specificity (0.899) and positive predictive value (PPV) (0.712) can be obtained by combining HuMean and HuMax in the diagnosis of UA stones. In conclusion, HuMean and HuMax can better predict UA stones than HuStd and HuMin. The combined use of HuMean and HuMax can lead to higher accuracy.

Prevalence of Monosodium Urate (MSU) Deposits in Cadavers Detected by Dual-Energy Computed Tomography (DECT)

Background: Dual-energy computed tomography (DECT) allows direct visualization of monosodium urate (MSU) deposits in joints and soft tissues. Purpose: To describe the distribution of MSU deposits in cadavers using DECT in the head, body trunk, and feet. Materials and Methods: A total of 49 cadavers (41 embalmed and 8 fresh cadavers; 20 male, 29 female; mean age, 79.5 years; SD ± 11.3; range 52–95) of unknown clinical history underwent DECT to assess MSU deposits in the head, body trunk, and feet. Lens, thoracic aorta, and foot tendon dissections of fresh cadavers were used to verify MSU deposits by polarizing light microscopy. Results: 33/41 embalmed cadavers (80.5%) showed MSU deposits within the thoracic aorta. 11/41 cadavers (26.8%) showed MSU deposits within the metatarsophalangeal (MTP) joints and 46.3% of cadavers demonstrated MSU deposits within foot tendons, larger than and equal to 5 mm. No MSU deposits were detected in the cranium/intracerebral vessels, or the coronary arteries. Microscopy used as a gold standard could verify the presence of MSU deposits within the lens, thoracic aorta, or foot tendons in eight fresh cadavers. Conclusions: Microscopy confirmed the presence of MSU deposits in fresh cadavers within the lens, thoracic aorta, and foot tendons, whereas no MSU deposits could be detected in cranium/intracerebral vessels or coronary arteries. DECT may offer great potential as a screening tool to detect MSU deposits and measure the total uric acid burden in the body. The clinical impact of this cadaver study in terms of assessment of MSU burden should be further proven.

In Vivo Comparison of Radiation Exposure in Third Generation versus Second Generation Dual-Source Dual-Energy CT for Imaging Urinary Calculi

PURPOSE

To investigate the potential for decreasing radiation dose when utilizing a third generation versus second generation dual-source dual-energy CT scanner, while maintaining diagnostic image quality and acceptable image noise.

MATERIALS AND METHODS

Retrospective analysis of patients who underwent dual-source dual-energy CT (dsDECT) for clinical suspicion of urolithiasis from 10/2/2017 - 9/5/2018. Patient demographics, body mass index, abdominal diameter, scanning parameters, and CT dose index volume (CTDIvol) were recorded. Image quality was assessed by measuring the attenuation and standard deviation (SD) regions of interest in the aorta and in the bladder. Image noise was determined by averaging the SD at both levels. Patients were excluded if they had not undergone both 3rd and 2nd generation DECT, time between DECT was more than 2 years, or scan parameters were outside standard protocol.

RESULTS

117 patients met inclusion criteria. Examinations performed on a 3rd generation DECT had an average CTDIvol 12.3 mGy, while examinations performed on a 2nd generation DECT had an average CTDIvol 13.3 mGy (p<0.001). Average image noise was significantly lower for the 3rd generation DECT (SD=10.3) as compared to the 2nd generation DECT (SD=13.9) (p<0.001).

CONCLUSIONS

The third generation dsDECT scanners can simultaneously decrease patient radiation dose and decrease image noise as compared to second generation DECT. These reductions in radiation exposure can be particularly important in patients with urinary stone disease who often require repeated imaging to evaluate for stone development and recurrence as well as treatment assessment.

Single-energy CT predicts uric acid stones with accuracy comparable to dual-energy CT-prospective validation of a quantitative method

OBJECTIVES

To prospectively validate three quantitative single-energy CT (SE-CT) methods for classifying uric acid (UA) and non-uric acid (non-UA) stones.

METHODS

Between September 2018 and September 2019, 116 study participants were prospectively included in the study if they had at least one 3-20-mm urinary stone on an initial urinary tract SE-CT scan. An additional dual-energy CT (DE-CT) scan was performed, limited to the stone of interest. Additionally, to include a sufficient number of UA stones, eight participants with confirmed UA stone on DE-CT were retrospectively included. The SE-CT stone features used in the prediction models were (1) maximum attenuation (maxHU) and (2) the peak point Laplacian (ppLapl) calculated at the position in the stone with maxHU. Two prediction models were previously published methods (ppLapl-maxHU and maxHU) and the third was derived from the previous results based on the k-nearest neighbors (kNN) algorithm (kNN-ppLapl-maxHU). The three methods were evaluated on this new independent stone dataset. The reference standard was the CT vendor's DE-CT application for kidney stones.

RESULTS

Altogether 124 participants (59 ± 14 years, 91 men) with 106 non-UA and 37 UA stones were evaluated. For classification of UA and non-UA stones, the sensitivity, specificity, and accuracy were 100% (37/37), 97% (103/106), and 98% (140/143), respectively, for kNN-ppLapl-maxHU; 95% (35/37), 98% (104/106), and 97% (139/143) for ppLapl-maxHU; and 92% (34/37), 94% (100/106), and 94% (134/143) for maxHU.

CONCLUSION

A quantitative SE-CT method (kNN-ppLapl-maxHU) can classify UA stones with accuracy comparable to DE-CT.

KEY POINTS

• Single-energy CT is the first-line diagnostic tool for suspected renal colic. • A single-energy CT method based on the internal urinary stone attenuation distribution can classify urinary stones into uric acid and non-uric acid stones with high accuracy. • This immensely increases the availability of in vivo stone analysis.

Revolution spectral CT for urinary stone with a single/mixed composition in vivo: a large sample analysis

PURPOSE

To analyze various compositions of urinary stones using revolution spectral CT (rapid kV switching dual-energy CT) in vivo.

METHODS

202 patients with urinary stones underwent spectral CT before surgery. Zeff peak, overall scope and CT values were detected. Moreover, water/iodine attenuating material images were obtained. Removed stones were subjected to infrared spectroscopy after surgery. The results of infrared spectroscopy were compared with CT.

RESULTS

28 stones (14.08%) with single composition, 165 stones with two mixed compositions (81.68%), and 9 stones with three mixed compositions (4.46%) were observed. When Zeff peaks of stones with single/mixed compositions were summarized together, 146 peaks of calcium oxalate monohydrate, 119 peaks of calcium oxalate dihydrate, 55 peaks of carbapatite, 38 peaks of urate, 16 peaks of struvite, and 11 peaks of brushite were totally observed. 93.8% of calcium oxalate monohydrate had Zeff peaks between 13.3 and 14.0. 91.6% of calcium oxalate dihydrate had peaks between 12.0 and 13.3. For carbapatite, 90.9% of stones had peaks from 14.0 to 15.0. A total of 94.8% of urate had peaks between 7.0 and 11.0. 93.8% of struvite had peaks between 11.0 and 13.0, and 90.9% of brushite had peaks between 12.0 and 14.0. Moreover, densities of urate, struvite and brushite were low density in iodine-based images and high-density in water-based images.

CONCLUSION

The in-vivo analysis of spectral CT in urinary stone revealed characteristics of different compositions, especially mixed compositions. An in-vivo predictive model may be constructed to distinguish stone compositions.

Dual-Energy CT for Urinary Stone Evaluation

PURPOSE OF REVIEW

Conventional CT imaging is an excellent tool for the diagnosis of nephrolithiasis however is limited in its ability to detect stone composition. Dual-energy CT (DECT) scans have demonstrated promise in overcoming this limitation. We review the current utility of DECT in nephrolithiasis.

RECENT FINDINGS

DECT is superior to conventional CT in differentiating uric acid stones from non-uric acid stones, with numerous studies reporting sensitivities and specificities approaching > 95%. Dose reduction protocols incorporating low-dose CT scans are commonly used, providing significantly lower effective radiation doses compared to conventional CT. DECT remains an effective diagnostic tool in patients with large body habitus. DECT can accurately detect uric acid stones, which can help guide which stones may be suitable to medical dissolution. Further studies evaluating the effectiveness of DECT in guiding management of patients with nephrolithiasis can help to promote its widespread use.

Pre-operative Percutaneous Nephrolithotripsy Characterisation of Kidney Stones with Second-Generation Dual-Source Dual-Energy Computed Tomography

Background: The current clinical practice to manage kidney stone requires knowledge of the stone composition. However, it is often difficult to determine the actual stone composition before a stone is operatively removed from the patient. Dual-energy computed tomography (DECT) can predict urinary stone composition, but it is not widely adopted. The purpose of the study was to investigate the use of a second-generation DECT with tin or stannum (Sn) filter for characterising the kidney stones composition. Methods: Thirty-three kidney stones were scanned ex vivo using a dual-source (DS)DECT scanner with dual-energy (DE) mode of 80/140 kVp with and without 4 mm Sn filtration. DE ratio was calculated to determine the kidney stones composition (uric acid, calcium oxalate, calcium phosphate and cystine). The median DE ratio of the stones was compared using Wilcoxon signed rank test and the results were further correlated with semi-quantitative Fourier transform infrared (FTIR) spectroscopy analysis using Kendall’s Tau test with P < 0.05 deemed to be statistically significant. Results: Second-generation DS-DECT could significantly discriminate the stones composition with and without Sn filtration (P < 0.001). The median DE ratio of uric acid, calcium oxalate and cystine stones were significantly higher with Sn filtration than those without filtration (P < 0.05). DECT results revealed significant correlation with FTIR spectroscopy analysis (r = 0.716, P < 0.001). DECT with Sn filtration showed increased performance (100% sensitivity, 0% specificity) than those without filtration (48.5% sensitivity, 0% specificity) in the detection of the kidney stone subtypes. Conclusion: In the second-generation DECT with additional Sn filtration, DECT has shown a significant performance in characterising and discriminating the kidney stone composition. This may improve diagnostic and therapy management in kidney stones cases.

Dose independent characterization of renal stones by means of dual energy computed tomography and machine learning: an ex-vivo study

OBJECTIVES

To predict the main component of pure and mixed kidney stones using dual-energy computed tomography and machine learning.

METHODS

200 kidney stones with a known composition as determined by infrared spectroscopy were examined using a non-anthropomorphic phantom on a spectral detector computed tomography scanner. Stones were of either pure (monocrystalline, n = 116) or compound (dicrystalline, n = 84) composition. Image acquisition was repeated twice using both, normal and low-dose protocols, respectively (ND/LD). Conventional images and low and high keV virtual monoenergetic images were reconstructed. Stones were semi-automatically segmented. A shallow neural network was trained using data from ND1 acquisition split into training (70%), testing (15%) and validation-datasets (15%). Performance for ND2 and both LD acquisitions was tested. Accuracy on a per-voxel and a per-stone basis was calculated.

RESULTS

Main components were: Whewellite (n = 80), weddellite (n = 21), Ca-phosphate (n = 39), cysteine (n = 20), struvite (n = 13), uric acid (n = 18) and xanthine stones (n = 9). Stone size ranged from 3 to 18 mm. Overall accuracy for predicting the main component on a per-voxel basis attained by ND testing dataset was 91.1%. On independently tested acquisitions, accuracy was 87.1-90.4%.

CONCLUSIONS

Even in compound stones, the main component can be reliably determined using dual energy CT and machine learning, irrespective of dose protocol.

KEY POINTS

• Spectral Detector Dual Energy CT and Machine Learning allow for an accurate prediction of stone composition. • Ex-vivo study demonstrates the dose independent assessment of pure and compound stones. • Lowest accuracy is reported for compound stones with struvite as main component.

Changes in the Selected Antioxidant Defense Parameters in the Blood of Patients after High Resolution Computed Tomography

Ionizing radiation generated during high resolution computed tomography (HRCT) scanning may have an indirect effect on the mechanisms regulating the oxidative-antioxidant balance in the human body, which is one of the necessary factors ensuring the maintenance of its homeostasis. The aim of the study was to analyze the response of antioxidant systems through the determination of the antioxidant markers in the blood of patients exposed to oxidative stress resulting from the routine HRCT examination of the chest. Blood of 35 people aged 60.77 ± 10.81 taken before and at four time points after the examination constituted the test material. The determination of the total antioxidant capacity expressed as ferric reducing ability of plasma (FRAP) and ferric reducing antioxidant activity and ascorbic acid concentration (FRASC) were performed together with an examination of catalase activity and the concentration of the reduced glutathione. The organism’s response to ionizing radiation was associated with a significant decrease in the antioxidant markers’ levels at all time-points and showed a significant negative correlation depending on the radiation dose. Visible down-regulation of these markers is a response to increased oxidative stress. In light of the obtained results, the measurement of the selected markers of antioxidant defense may be a useful parameter of oxidative stress caused by ionizing radiation.