Dosimetric and radiation cancer risk evaluation of high resolution thorax CT during COVID-19 outbreak

Evaluation of organ dose using size-specific dose estimation (SSDE) and related cancer risk due to chest CT scan during the COVID-19 pandemic

This study aimed to estimate lung and breast doses for individual patients using the size-specific dose estimate (SSDE) method, as well as calculating effective doses, in patients who underwent chest CT scans during the COVID-19 pandemic. Cancer risk incidence was estimated using excess relative risk (ERR), excess absolute risk (EAR), and lifetime attributable risk (LAR) models from the Biological Effects of Ionizing Radiation Report VII (BEIR-VII). Data from about 570 patients who underwent CT scans for COVID-19 screening were utilized for this study. Using the header of the CT images in a Python script, SSDE and effective dose were calculated for each patient. The SSDE obtained by water equivalent effective diameter (wSSDE) was considered as lung and breast dose, and applied in organ-specific cancer risk estimation. The mean wSSDE value for females (13.3 mGy) was slightly higher than that for males (13.1 mGy), but the difference was not statistically significant (P value = 0.41). No significant differences were observed between males and females in terms of calculated EAR and ERR for lung cancer at 5 and 30 years after exposure (P value = 0.47, 0.46, respectively). Similarly, there was no significant difference in lung cancer LAR values between females and males (P value = 0.48). The results also indicated a decrease in LAR values for both lung and breast cancers with increasing exposure age. In accordance with the ALARA (as low as reasonably achievable) principle, it is important for medical staff and the general public to consider the benefits of CT imaging in detecting such infections. Additionally, imaging medical physicists and CT scan experts should optimize imaging protocols and strike a balance between image quality for detecting abnormalities and radiation dose, all while adhering to the ALARA principle.

A closer look at the utilized radiation doses during computed tomography pulmonary angiography (CTPA) for COVID-19 patients

Introduction

CTPA stands for computed tomography pulmonary angiography. CTPA is an X-ray imaging that combines X-rays and computer technology to create detailed images of the pulmonary arteries and veins in the lungs. This test diagnoses and monitors conditions like pulmonary embolism, arterial blockages, and hypertension. Coronavirus (COVID-19) has threatened world health over the last three years. The number of (CT) scans increased and played a vital role in diagnosing COVID-19 patients, including life-threatening pulmonary embolism (PE). This study aimed to assess the radiation dose resulted from CTPA for COVID-19 patients.

Methods

Data were collected retrospectively from CTPA examinations on a single scanner in 84 symptomatic patients. The data collected included the dose length product (DLP), volumetric computed tomography dose index (CTDIvol), and size-specific dose estimate (SSDE). The organ dose and effective dose were estimated using VirtualDose software.

Results

The study population included 84 patients, 52% male and 48% female, with an average age of 62. The average DLP, CTDIvol, and SSDE were 404.2 mGy cm, 13.5 mGy, and 11.6 mGy\, respectively. The mean effective doses (mSv) for males and females were 3.01 and 3.29, respectively. The maximum to minimum organ doses (mGy) between patients was 0.8 for the male bladder and 7.33 for the female lung.

Conclusions

The increase in CT scans during the COVID-19 pandemic required close dose monitoring and optimization. The protocol used during CTPA should guarantee a minimum radiation dose with maximum patient benefits.

Estimation of cancer risks due to chest radiotherapy treatment planning computed tomography (CT) simulations

The objective of our study was to determine organ doses to estimate the lifetime attributable risk (LAR) of cancer incidence related to chest tomography simulations for Radiotherapy Treatment Planning (RTTP) using patient-specific information. Patient data were used to calculate organ doses and effective dose. The effective dose (E) was calculated by two methods. First, to calculate effective dose in a standard phantom, the collected dosimetric parameters were used with the ImPACT CT Patient Dosimetry Calculator and E was calculated by applying related correction factors. Second, using the scanner-derived Dose Length Product, LARs were computed using the US National Academy of Sciences (BEIR VII) model for age- and sex-specific risks at each exposure. DLP, CTDI_vol, and scan length were 507 ± 143 mGy.cm, 11 ± 4 mGy, and 47 ± 7 cm, respectively. The effective dose was 10 ± 3 mSv using ImPACT patient dosimetry calculator software and 9 ± 2 mSv using the scanner-derived Dose Length Product. The LAR of cancer incidence for all cancers, all solid cancers and leukemia were 65 ± 29, 62 ± 27, 7 ± 2 cases per 100,000 individuals, respectively. Radiation exposure from the usage of CT for radiotherapy treatment planning (RTTP) causes non-negligible increases in lifetime attributable risk. The results of this study can be used as a guide by physicians to implement strategies based on the As Low As Reasonably Achievable (ALARA) principle that lead to a reduction dose without sacrificing diagnostic information.

Evaluation of clinical outcomes, laboratory and imaging data of patients with solid tumor infected with COVID-19 infection

BACKGROUND

COVID-19 is associated with higher mortality rates in patients with cancer. In this study, we aimed to evaluate the clinical outcomes, and laboratory and imaging data of patients with solid tumor infected with COVID-19 infection.

METHODS

This is a cross-sectional retrospective study performed in 2020-2022 on 85 patients with a previous diagnosis of solid tumors infected with COVID-19. We included all patients with tumors of solid organs that were diagnosed with COVID-19 infection and required hospitalization those patients previously hospitalized for treatments and were infected with COVID-19 during hospitalization. Demographic data of patients were collected using a checklist. We collected data regarding clinical outcome (discharge, hospitalization or death), duration of hospitalization, requiring ICU admission, duration of hospitalization divided by received drugs and type of tumor and mean survival time. Furthermore, we collected laboratory data from all patients. The radiologic characteristics of patients were also extracted from their data.

RESULTS

Breast cancer was the most common solid tumor (34.9%), followed by lung cancer (19.3%). The mortality rate was 24.1% (20 patients). The highest mortality rate in this study was for metastatic intestinal cancer to the lung (100%, one patient), followed by metastatic prostatic cancer to lung (50%, three patients). The highest hospitalization duration was for patients with glioblastoma multiform (GBM) (30 days). The mean survival time among patients with mortality was 19.15±1.80 days. The mean CT severity score of all patients was 27.53±22.90. Patient's most common radiologic sign was air space consolidation (89.1%). The highest CT severity score was found in patients with stomach cancer (46.67±5.77).

CONCLUSION

The mortality rate in this study was 24.1%. Based on the results of our study and previous research, special care should be provided to patients with solid tumors during the COVID-19 pandemic and in infected cases.

Radiation Exposure and Lifetime Attributable Risk of Cancer Incidence and Mortality from Low- and Standard-Dose CT Chest: Implications for COVID-19 Pneumonia Subjects

Since the novel coronavirus disease 2019 (COVID-19) outbreak, there has been an unprecedented increase in the acquisition of chest computed tomography (CT) scans. Nearly 616 million people have been infected by COVID-19 worldwide to date, of whom many were subjected to CT scanning. CT exposes the patients to hazardous ionizing radiation, which can damage the genetic material in the cells, leading to stochastic health effects in the form of heritable genetic mutations and increased cancer risk. These probabilistic, long-term carcinogenic effects of radiation can be seen over a lifetime and may sometimes take several decades to manifest. This review briefly describes what is known about the health effects of radiation, the lowest dose for which there exists compelling evidence about increased radiation-induced cancer risk and the evidence regarding this risk at typical CT doses. The lifetime attributable risk (LAR) of cancer from low- and standard-dose chest CT scans performed in COVID-19 subjects is also discussed along with the projected number of future cancers that could be related to chest CT scans performed during the COVID-19 pandemic. The LAR of cancer Incidence from chest CT has also been compared with those from other radiation sources, daily life risks and lifetime baseline risk.

Investigation of radiation dose around C-arm fluoroscopy and relevant cancer risk to operating room staff

This study aimed to evaluate the ambient dose equivalent around a C-arm device during spinal surgeries and determine the optimum locations for the surgeon and staff to keep radiation exposure as low as reasonably achievable. Furthermore, cancer risk incidence was estimated using the excess relative risk (ERR) concept of the biologic effects of ionizing radiation VII report for operating room (OR) staff. A lateral projection of the C-arm setup was considered in the current study. The ambient dose equivalent rate was measured using an electronic dosimeter in 30° steps all around for 1, and 1.6-m heights as well as 1, and 2-m distances away from a water tank (scattering medium). By assuming a typical workload, the annual ambient dose and a maximum number of permissible operations were determined. For a worst-case scenario, the dose was used to estimate the ERR for various organs including prostate, ovary, breast, lung, thyroid, and colon for attained ages of 35, 40, and 50 years. The maximum ambient dose equivalent rate was seen at 330° and 30° (about 600 µSv/h at 1 m height and a distance of 1 m from the scattering medium). The corresponding permissible workload for an OR staff was about 30,660 operations. Based on the obtained results, 60° next to the image intensifier was the optimum position for the surgeon, while 30° next to the tube was the worst position because of backscattered radiation. The ERR results showed that the lung and colon have the highest cancer risk incidence among the considered organs for both males and females, respectively.

Cancer Occurrence as the Upcoming Complications of COVID-19

Previous studies suggested that patients with comorbidities including cancer had a higher risk of mortality or developing more severe forms of COVID-19. The interaction of cancer and COVID-19 is unrecognized and potential long-term effects of COVID-19 on cancer outcome remain to be explored. Furthermore, whether COVID‐19 increases the risk of cancer in those without previous history of malignancies, has not yet been studied. Cancer progression, recurrence and metastasis depend on the complex interaction between the tumor and the host inflammatory response. Extreme proinflammatory cytokine release (cytokine storm) and multi‐organ failure are hallmarks of severe COVID‐19. Besides impaired T-Cell response, elevated levels of cytokines, growth factors and also chemokines in the plasma of patients in the acute phase of COVID-19 as well as tissue damage and chronic low‐grade inflammation in “long COVID‐19” syndrome may facilitate cancer progression and recurrence. Following a systemic inflammatory response syndrome, some counterbalancing compensatory anti-inflammatory mechanisms will be activated to restore immune homeostasis. On the other hand, there remains the possibility of the integration of SARS- CoV-2 into the host genome, which potentially may cause cancer. These mechanisms have also been shown to be implicated in both tumorigenesis and metastasis. In this review, we are going to focus on potential mechanisms and the molecular interplay, which connect COVID-19, inflammation, and immune-mediated tumor progression that may propose a framework to understand the possible role of COVID-19 infection in tumorgenesis and cancer progression.

Determine Cumulative Radiation Dose and Lifetime Cancer Risk in Marfan Syndrome Patients Who Underwent Computed Tomography Angiography of the Aorta in Northeast Thailand: A 5-Year Retrospective Cohort Study

Objective: To evaluate computed tomography angiography (CTA) data focusing on radiation dose parameters in Thais with Marfan syndrome (MFS) and estimate the distribution of cumulative radiation exposure from CTA surveillance and the risk of cancers. Methods: Between 1st January 2015 and 31st December 2020, we retrospectively evaluated the cumulative CTA radiation doses of MFS patients who underwent CTA at Khon Kaen University Hospital, a leading teaching hospital and advanced tertiary care institution in northeastern Thailand. We utilized the Radiation Risk Assessment Tool (RadRAT) established at the National Cancer Institute in Bethesda, Maryland, to evaluate the risk of cancer-related CTA radiation. Results: The study recruited 29 adult MFS patients who had CTA of the aorta during a 5-year study period with 89 CTA studies. The mean cumulative CTDI vol is 21.5 ± 14.68 mGy, mean cumulative DLP is 682.2 ± 466.7 mGy.cm, the mean baseline future risk for all cancer is 26,134 ± 7601 per 100,000, and the excess lifetime risk for all cancer is 2080.3 ± 1330 per 100,000. The excess lifetime risk of radiation-induced cancer associated with the CTA surveillance study is significantly lower than the risk of aortic dissection or rupture and lower than the baseline future cancer risk. Conclusions: We attempted to quantify the radiation-induced cancer risk from CTA surveillance imaging performed for MFS patients in this study, with all patients receiving a low-risk cumulative radiation dose (less than 1 Gy) and all patients having a low excessive lifetime risk of cancer as a result of CTA. The risk–benefit decision must be made at the point of care, and it entails balancing the benefits of surveillance imaging in anticipating rupture and providing practical, safe treatment, therefore avoiding morbidity and mortality.

A patient-specific approach for quantitative and automatic analysis of computed tomography images in lung disease: Application to COVID-19 patients

PURPOSE

Quantitative metrics in lung computed tomography (CT) images have been widely used, often without a clear connection with physiology. This work proposes a patient-independent model for the estimation of well-aerated volume of lungs in CT images (WAVE).

METHODS

A Gaussian fit, with mean (Mu.f) and width (Sigma.f) values, was applied to the lower CT histogram data points of the lung to provide the estimation of the well-aerated lung volume (WAVE.f). Independence from CT reconstruction parameters and respiratory cycle was analysed using healthy lung CT images and 4DCT acquisitions. The Gaussian metrics and first order radiomic features calculated for a third cohort of COVID-19 patients were compared with those relative to healthy lungs. Each lung was further segmented in 24 subregions and a new biomarker derived from Gaussian fit parameter Mu.f was proposed to represent the local density changes.

RESULTS

WAVE.f resulted independent from the respiratory motion in 80% of the cases. Differences of 1%, 2% and up to 14% resulted comparing a moderate iterative strength and FBP algorithm, 1 and 3 mm of slice thickness and different reconstruction kernel. Healthy subjects were significantly different from COVID-19 patients for all the metrics calculated. Graphical representation of the local biomarker provides spatial and quantitative information in a single 2D picture.

CONCLUSIONS

Unlike other metrics based on fixed histogram thresholds, this model is able to consider the inter- and intra-subject variability. In addition, it defines a local biomarker to quantify the severity of the disease, independently of the observer.