Routine Chest CT Research Articles

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography

BackgroundAutomatically detecting and quantifying pneumothorax on chest computed tomography (CT) may impact clinical decision-making. Machine learning methods published so far struggle with the heterogeneity of technical parameters and the presence of additional pathologies, highlighting the importance of stable algorithms.MethodsA deep residual UNet was developed and evaluated for automated, volume-level pneumothorax grading (i.e., labelling a volume whether a pneumothorax was present or not), and pixel-level classification (i.e., segmentation and quantification of pneumothorax), on a retrospective series of routine chest CT data. Ground truth annotations were provided by radiologists. The fully automated pixel-level pneumothorax segmentation method was trained using 43 chest CT scans and evaluated on 9 chest CT scans with pixel-level annotation basis and 567 chest CT scans on a volume-level basis.ResultsThis method achieved a receiver operating characteristic area under the curve (AUC) of 0.98, an average precision of 0.97, and a Dice similarity coefficient (DSC) of 0.94. This segmentation performance resulted to be similar to the inter-rater segmentation accuracy of two radiologists, who achieved a DSC of 0.92. The comparison of manual and automated pneumothorax quantification yielded a Pearson correlation coefficient of 0.996. The volume-level pneumothorax grading accuracy was evaluated on 567 chest CT scans and yielded an AUC of 0.98 and an average precision of 0.95.ConclusionsWe proposed a deep learning method for the detection and quantification of pneumothorax in heterogeneous routine clinical data that may facilitate the automated triage of urgent examinations and enable treatment decision support.

Routine Chest Computed Tomography for Staging of Pancreatic Head Carcinoma.

The diagnostic value of routine chest computed tomography (CT) in addition to abdominal CT in workup for pancreatic head carcinoma is unclear. The aim of this study was to determine if routine chest CT revealed significant lesions that altered the management of patients with suspected pancreatic head carcinoma. All Dutch pancreatic cancer centers were surveyed on the use of chest CT in preoperative staging. In addition, a single-center retrospective cohort study was performed including all patients referred with suspected pancreatic head malignancy without chest CT between 2005 and 2016. The primary end point was the proportion of patients in which chest CT revealed clinically significant lesions, leading to a change in management. In 7 of 18 Dutch pancreatic cancer centers (39%), a preoperative chest CT is not routinely performed. In the study cohort, 170 of 848 patients (20%) were referred without chest CT and underwent one by local protocol. Chest CT revealed new suspicious lesions in 17 patients (10%), of whom 6 had metastatic disease (3.5%). Routine use of chest CT in diagnostic workup for pancreatic head carcinoma reveals clinically significant lesions in 10% of patients, being metastases in up to 4%.

CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction

Use of adjuvant chemotherapy in patients with early-stage lung cancer is controversial because no definite biomarker exists to identify patients who would receive added benefit from it. We aimed to develop and validate a quantitative radiomic risk score (QuRiS) and associated nomogram (QuRNom) for early-stage non-small cell lung cancer (NSCLC) that is prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy following surgery. We did a retrospective multicohort study of individuals with early-stage NSCLC (stage I and II) who either received surgery alone or surgery plus adjuvant chemotherapy. We selected patients for whom we had available pre-treatment diagnostic CT scans and corresponding survival information. We used radiomic texture features derived from within and outside the primary lung nodule on chest CT scans of patients from the Cleveland Clinic Foundation (Cleveland, OH, USA; cohort D1) to develop QuRiS. A least absolute shrinkage and selection operator-Cox regularisation model was used for data dimension reduction, feature selection, and QuRiS construction. QuRiS was independently validated on a cohort of patients from the University of Pennsylvania (Philadephia, PA, USA; cohort D2) and a cohort of patients whose CT scans were derived from The Cancer Imaging Archive (cohort D3). QuRNom was constructed by integrating QuRiS with tumour and node descriptors (according to the tumour, node, metastasis staging system) and lymphovascular invasion. The primary endpoint of the study was the assessment of the performance of QuRiS and QuRNom in predicting disease-free survival. The added benefit of adjuvant chemotherapy estimated using QuRiS and QuRNom was validated by comparing patients who received adjuvant chemotherapy versus patients who underwent surgery alone in cohorts D1-D3. We included: 329 patients in cohort D1 (73 [22%] had surgery plus adjuvant chemotherapy and 256 (78%) had surgery alone); 114 patients in cohort D2 (33 [29%] had surgery plus adjuvant chemotherapy and 81 (71%) had surgery alone); and 82 patients in cohort D3 (24 [29%] had surgery plus adjuvant chemotherapy and 58 (71%) had surgery alone). QuRiS comprised three intratumoral and 10 peritumoral CT-radiomic features and was found to be significantly associated with disease-free survival (ie, prognostic validation of QuRiS; hazard ratio for predicted high-risk vs predicted low-risk groups 1·56, 95% CI 1·08-2·23, p=0·016 for cohort D1; 2·66, 1·24-5·68, p=0·011 for cohort D2; and 2·67, 1·39-5·11, p=0·0029 for cohort D3). To validate the predictive performance of QuRiS, patients were partitioned into three risk groups (high, intermediate, and low risk) on the basis of their corresponding QuRiS. Patients in the high-risk group were observed to have significantly longer survival with adjuvant chemotherapy than patients who underwent surgery alone (0·27, 0·08-0·95, p=0·042, for cohort D1; 0·08, 0·01-0·42, p=0·0029, for cohorts D2 and D3 combined). As concerns QuRNom, the nomogram-estimated survival benefit was predictive of the actual efficacy of adjuvant chemotherapy (0·25, 0·12-0·55, p<0·0001, for cohort D1; 0·13, <0·01-0·99, p=0·0019 for cohort D3). QuRiS and QuRNom were validated as being prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy, especially in clinically defined low-risk groups. Since QuRiS is based on routine chest CT imaging, with additional multisite independent validation it could potentially be employed for decision management in non-invasive treatment of resectable lung cancer. National Cancer Institute of the US National Institutes of Health, National Center for Research Resources, US Department of Veterans Affairs Biomedical Laboratory Research and Development Service, Department of Defence, National Institute of Diabetes and Digestive and Kidney Diseases, Wallace H Coulter Foundation, Case Western Reserve University, and Dana Foundation.

Application of high-resolution CT local augmentation reconstruction to improve the accurate diagnosis of small pulmonary nodule structure

Objective To explore the accurate display method of the local structure of small CT nodules in lung. Methods Close the automatic radiation dose adjustment technique. Keep the thickness of the phantom was 2 mm, the interval between the phantom layers was 2 mm, the pitch was 1, and the reconstructed convoluted nucleus was B80s. Group A controlled the scanning matrix FOV to be 500 mm×500 mm, 400 mm×400 mm, 300 mm×300 mm, 200 mm×200 mm and 100 mm×100 mm, while group B controlled the scanning matrix FOV to be 500 mm×500 mm. Use these parameters to scan the catphan 500 phantom, a routine chest CT conditioned scanning quality control model. The original data raw data were used to reconstruct the FOV to be 400 mm×400 mm, 300 mm×300 mm, 200 mm×200 mm and 100 mm×100 mm under the scanning FOV to be 500 mm×500 mm. All other conditions are consistent. Observe the high contrast resolution module of Catphan 500 phantom, and compare the line logarithms of two groups of images under different scanning FOV or different reconstruction FOV. Thirty-five patients with small pulmonary nodules from February 2018 to March 2018 of the Second Affiliated Hospital of Zhejiang University Medical College were retrospectively collected. The raw data were used to reconstruct the images. The FOV was 320 mm×320 mm in the conventional reconstruction group and 100 mm×100 mm in the local magnification reconstruction group. The subjective score data of the two groups were compared by using rank-sum test. Results When catphan 500 phantom was used, the number of lines in group A and group B increased gradually with the decreasing of FOV. The subjective score of local magnification reconstruction group (4.77±0.35) was higher than that of conventional reconstruction group (3.86±0.50) and the difference was statistically significant (Z=-5.763, P<0.05). Conclusion Local magnification and reconstruction of high-resolution CT images can achieve the same image quality as local magnification, local magnification and reconstruction of image quality is significantly better than simple image magnification. Key words: Tomography,X-ray computed; Radiation dosage; Imaging quality; Comparative study

Use of Multiphase CT Protocols in 18 Countries: Appropriateness and Radiation Doses.

To assess the frequency, appropriateness, and radiation doses associated with multiphase computed tomography (CT) protocols for routine chest and abdomen-pelvis examinations in 18 countries. In collaboration with the International Atomic Energy Agency, multi-institutional data on clinical indications, number of scan phases, scan parameters, and radiation dose descriptors (CT dose-index volume; dose-length product [DLP]) were collected for routine chest (n = 1706 patients) and abdomen-pelvis (n = 426 patients) CT from 18 institutions in Asia, Africa, and Europe. Two radiologists scored the need for each phase based on clinical indications (1 = not indicated, 2 = probably indicated, 3 = indicated). We surveyed 11 institutions for their practice regarding single-phase and multiphase CT examinations. Data were analyzed with the Student t test. Most institutions use multiphase protocols for routine chest (10/18 institutions) and routine abdomen-pelvis (10/11 institutions that supplied data for abdomen-pelvis) CT examinations. Most institutions (10/11) do not modify scan parameters between different scan phases. Respective total DLP for 1-, 2-, and 3-phase routine chest CT was 272, 518, and 820 mGy·cm, respectively. Corresponding values for 1- to 5-phase routine abdomen-pelvis CT were 400, 726, 1218, 1214, and 1458 mGy cm, respectively. For multiphase CT protocols, there were no differences in scan parameters and radiation doses between different phases for either chest or abdomen-pelvis CT (P = 0.40-0.99). Multiphase CT examinations were unnecessary in 100% of routine chest CT and in 63% of routine abdomen-pelvis CT examinations. Multiphase scan protocols for the routine chest and abdomen-pelvis CT examinations are unnecessary, and their use increases radiation dose.

Evidence-based follow-up in non-small cell lung cancer

Structured follow-up is an integral part of efficient care in non-small cell lung cancer (NSCLC). However, since randomized prospective clinical trials giving clear indications for an optimal follow-up algorithm are still missing, it is necessary to seek currently available evidence to determine which follow-up strategy is advisable. For this purpose, a review of the current literature has been undertaken. There is controversy in the literature about intensity, duration and modalities of follow-up in NSCLC. While some propose a higher intensity routine follow-up during the first 4 years after treatment, followed by yearly visits up to 5 years after treatment, others prefer a high-intensity follow-up for only the first 2 years, and yearly visits thereafter life-long. Most papers insist on measuring efficiency of routine follow-up upon its impact on overall survival. Routine chest CT should be integral part of the follow-up, while PET or PET/CT only in selected situations. The 2017 European Society for Medical Oncology guidelines formulate a consensus between all these positions by recommending visits every 6 months for the first 2 years, followed by life-long yearly surveillance, while for selected high-risk patients more frequent visits should be offered. Current evidence from the literature supports a more intense routine follow-up in NSCLC during the first 2 years after treatment, followed by less frequent regular visits life-long.

Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.

OBJECTIVE. The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. MATERIALS AND METHODS. Our prospective multiinstitutional study included 59 adult patients (33 women, 26 men; mean age ± SD, 65 ± 12 years old; mean body mass index [weight in kilograms divided by the square of height in meters] = 27 ± 5) who underwent routine chest (n = 22; 16 women, six men) and abdominopelvic (n = 37; 17 women, 20 men) CT on a 640-MDCT scanner (Aquilion ONE, Canon Medical Systems). All patients gave written informed consent for the acquisition of low-dose (LD) CT (LDCT) after a clinically indicated standard-dose (SD) CT (SDCT). The SDCT series (120 kVp, 164-644 mA) were reconstructed with interactive reconstruction (IR) (adaptive iterative dose reduction [AIDR] 3D, Canon Medical Systems), and the LDCT (100 kVp, 120 kVp; 30-50 mA) were reconstructed with filtered back-projection (FBP), IR (AIDR 3D and forward-projected model-based iterative reconstruction solution [FIRST], Canon Medical Systems), and deep learning reconstruction (DLR) (Advanced Intelligent Clear-IQ Engine [AiCE], Canon Medical Systems). Four subspecialty-trained radiologists first read all LD image sets and then compared them side-by-side with SD AIDR 3D images in an independent, randomized, and blinded fashion. Subspecialty radiologists assessed image quality of LDCT images on a 3-point scale (1 = unacceptable, 2 = suboptimal, 3 = optimal). Descriptive statistics were obtained, and the Wilcoxon sign rank test was performed. RESULTS. Mean volume CT dose index and dose-length product for LDCT (2.1 ± 0.8 mGy, 49 ± 13mGy·cm) were lower than those for SDCT (13 ± 4.4 mGy, 567 ± 249 mGy·cm) (p < 0.0001). All 31 clinically significant abdominal lesions were seen on SD AIDR 3D and LD DLR images. Twenty-five, 18, and seven lesions were detected on LD AIDR 3D, LD FIRST, and LD FBP images, respectively. All 39 pulmonary nodules detected on SD AIDR 3D images were also noted on LD DLR images. LD DLR images were deemed acceptable for interpretation in 97% (35/37) of abdominal and 95-100% (21-22/22) of chest LDCT studies (p = 0.2-0.99). The LD FIRST, LD AIDR 3D, and LD FBP images had inferior image quality compared with SD AIDR 3D images (p < 0.0001). CONCLUSION. At submillisievert chest and abdominopelvic CT doses, DLR enables image quality and lesion detection superior to commercial IR and FBP images.

Left Atrial Volume as a Biomarker of Atrial Fibrillation at Routine Chest CT: Deep Learning Approach.

To test the performance of a deep learning (DL) model in predicting atrial fibrillation (AF) at routine nongated chest CT. A retrospective derivation cohort (mean age, 64 years; 51% female) consisting of 500 consecutive patients who underwent routine chest CT served as the training set for a DL model that was used to measure left atrial volume. The model was then used to measure atrial size for a separate 500-patient validation cohort (mean age, 61 years; 46% female), in which the AF status was determined by performing a chart review. The performance of automated atrial size as a predictor of AF was evaluated by using a receiver operating characteristic analysis. There was good agreement between manual and model-generated segmentation maps by all measures of overlap and surface distance (mean Dice = 0.87, intersection over union = 0.77, Hausdorff distance = 4.36 mm, average symmetric surface distance = 0.96 mm), and agreement was slightly but significantly greater than that between human observers (mean Dice = 0.85 [automated] vs 0.84 [manual]; P = .004). Atrial volume was a good predictor of AF in the validation cohort (area under the receiver operating characteristic curve = 0.768) and was an independent predictor of AF, with an age-adjusted relative risk of 2.9. Left atrial volume is an independent predictor of the AF status as measured at routine nongated chest CT. Deep learning is a suitable tool for automated measurement.© RSNA, 2019See also the commentary by de Roos and Tao in this issue.

Predicting Atrial Fibrillation from Automated Measurements of Left Atrial Volume Using Routine Chest CT Examination: Overlooked and Underrecognized Risk Factors.

Predicting Atrial Fibrillation from Automated Measurements of Left Atrial Volume Using Routine Chest CT Examination: Overlooked and Underrecognized Risk Factors.

Evaluation Artificial Intelligent (AI) Assists Radiologist in Radiographic Chest Interpretation

Artificial Intelligence (AI) is integrated in the medical field especially in imaging. Routine chest radiography, mammography, CT and magnetic resonance imaging (MRI) are commonly used in the radiology department1, AI images are available to assist radiologists as an imaging companion, to increase quality and decrease time in interpretations. The use of Lunit INSIGHT2 for chest radiography is evaluated to ascertain the probability of its usefulness and the advantage and disadvantage of this tool. Furthermore, the AI image is an advance in assisting in the upgrade of more crucial diagnosis and it will reduce costs of unnecessary investigations in the near future.

Abdominal visceral adipose tissue is associated with unsuspected pulmonary embolism on routine CT scans in patients with gastrointestinal cancer.

Unsuspected pulmonary embolism (UPE) has been increasingly diagnosed as an incidental finding on CT scans for routine staging in cancer patients. Previous studies suggest that obesity is an independent risk factor for venous thromboembolism in patients with malignant tumors. In this study, we aimed to investigate the association between abdominal adipose tissue, especially visceral adipose tissue (VAT) and the occurrence of UPE in hospitalized patients with gastrointestinal cancer. Routine contrast-enhanced chest and abdominal CT scans of 1974 patients were retrospectively assessed for the presence of UPE, of which 58 patients were identified with UPE and 108 non-UPE patients were selected as the non-UPE control group based on several matching criteria. Abdominal adipose tissue was measured by volumes of VAT and subcutaneous adipose tissue (SAT) at the navel level. VAT, SAT, indwelling venous catheters, surgery, chemotherapy, and bed rest or immobilization were associated with the occurrence of UPE. Higher VAT volumes were associated with increased risk of UPE (odds ratio: 1.96; 95% confidence interval: 1.25, 3.06; p = 0.003) adjusting body mass index (BMI), bed rest or immobilization, surgery, chemotherapy and smoking, while SAT was not associated with UPE adjusting the same confounders (p = 0.117). No statistical association was found between BMI and UPE (p = 0.102). Higher VAT rather than SAT is associated with an increased risk of unsuspected pulmonary embolism on routine CT scans in hospitalized gastrointestinal cancer patients. Our findings indicate that VAT is a stronger risk factor for unsuspected pulmonary embolism than BMI and SAT in hospitalized patients with gastrointestinal cancer.

Machine Learning for Automatic Paraspinous Muscle Area and Attenuation Measures on Low-Dose Chest CT Scans

To develop and evaluate an automated machine learning (ML) algorithm for segmenting the paraspinous muscles on chest computed tomography (CT) scans to evaluate for presence of sarcopenia. A convolutional neural network based on the U-Net architecture was trained to perform muscle segmentation on a dataset of 1875 single slice CT images and was tested on 209 CT images of participants in the National Lung Screening Trial. Low-dose, noncontrast CT examinations were obtained at 33 clinical sites, using scanners from four manufacturers. The study participants had a mean age of 71.6 years (range, 70-74 years). Ground truth was obtained by manually segmenting the left paraspinous muscle at the level of the T12 vertebra. Muscle cross-sectional area (CSA) and muscle attenuation (MA) were recorded. Comparison between the ML algorithm and ground truth measures of muscle CSA and MA were obtained using Dice similarity coefficients and Pearson correlations. Compared to ground truth segmentation, the ML algorithm achieved median (standard deviation) Dice scores of 0.94 (0.04) in the test set. Mean (SD) muscle CSA was 14.3 (3.6) cm2 for ground truth and 13.7 (3.5) cm2 for ML segmentation. Mean (SD) MA was 41.6 (7.6) Hounsfield units (HU) for ground truth and 43.5 (7.9) HU for ML segmentation. There was high correlation between ML algorithm and ground truth for muscle CSA (r2 = 0.86; p < 0.0001) and MA (r2 = 0.95; p < 0.0001). The ML algorithm for measurement of paraspinous muscles compared favorably to manual ground truth measurements in the NLST. The algorithm generalized well to a heterogeneous set of low-dose CT images and may be capable of automated quantification of muscle metrics to screen for sarcopenia on routine chest CT examinations.

The Relevance of Family History Taking in the Detection and Management of Birt-Hogg-Dubé Syndrome

Background: Birt-Hogg-Dubé syndrome (BHDS) is a rare autosomal-dominant inherited disorder characterized by inactivation of the gene Folliculin (FLCN), pulmonary cysts with recurrent spontaneous pneumothorax, dermatological lesions, and an increased risk of developing renal malignancies. Objectives: We aimed to investigate the real prevalence of BHDS and its prevalence among patients with a familial history of pneumothorax. Methods: From July 2014 to December 2016, we consecutively studied all patients with spontaneous pneumothorax and a positive family history for the same condition referring to our Institution. The suspicious cases underwent genetic analysis of the BHDS-causative gene FLCN. FLCN-positive cases were further evaluated with routine blood tests, chest radiography, chest CT, abdominal MRI, and dermatological evaluation. Results: Among 114 patients admitted with spontaneous pneumothorax, 7 patients had a family history of pneumothorax, and 6/7 (85.7%) patients had positive genetic test for FLCN as well as 7/13 family members. Pulmonary cysts were found in all patients with a FLCN-positive genetic test. Most patients (10/13, 76.9%) had tiny pulmonary cysts less than 1 cm in diameter. The vast majority of cysts were intraparenchymal (12/13, 92.3%) and located in lower lobes. Dermatological lesions were found in 7/13 (54%) patients, renal cysts in 4/13 (31%) patients, and renal cancer in 1 (1/13, 7.7%) patient. Conclusions: Although BHDS is considered a rare disease, BHDS underlies spontaneous pneumothorax more often than usually believed, especially whenever a family history of pneumothorax is present. Diagnosis of BHDS is essential to start monitoring patients for the risk of developing renal malignancies.

Routine chest CT for staging of gastric cancer.

BackgroundInternational guidelines on clinical staging of gastric cancer recommend the use of chest CT for the detection of pulmonary metastases. This study assessed the clinical value of routine chest CT in the staging of gastric cancer.MethodsThis retrospective study included patients identified from the gastric cancer registry of Chang Gung Memorial Hospital, Linkou, Taiwan. All patients who underwent clinical staging between 2008 and 2014 were included. The pattern, site and number of metastases at initial presentation and after surgery with curative intent were evaluated. Pulmonary metastases were defined as multiple small round pulmonary nodules with a random distribution or of variable size.ResultsSome 1669 patients were included, of whom 478 (28·6 per cent) had metastatic disease at clinical presentation. The majority of metastases were to the peritoneum (75·7 per cent of patients) or liver (30·5 per cent), and only 27 patients (5·6 per cent) had pulmonary metastases at presentation, none of which were isolated to the lung. Of these 27 patients, 11 had primary lesions located at the cardia/fundus. In 19 patients the lung metastases were also detected on the staging chest X‐ray. After surgery there were 196 cancer recurrences. Some 15 patients (7·6 per cent) had lung metastasis and this was not the only site of metastases in any patient. The prevalence of lung metastasis at presentation of the disease and after surgery was 1·6 and 1·5 per cent respectively.ConclusionThis study does not support the routine use of chest CT for staging of gastric cancer as isolated pulmonary metastasis in the absence of other metastatic sites could not be detected.

Hypoxic condition monitoring and treatment evaluation for non-small cell lung cancer before and after radiotherapy by 18F-FMISO PET/CT

Objective To evaluate the changes of hypoxic conditions in non-small cell lung cancer (NSCLC) patients before and after radiotherapy and assess the value of 18F-fluoromisonidzaole (FMISO) PET/CT for radiotherapy efficacy evaluation. Methods A total of 21 NSCLC patients (15 males, 6 females, age 30-74 years) from January 2014 to October 2016 were prospectively enrolled. 18F-FMISO PET/CT was performed before and after radiotherapy, and all patients underwent 18F-fluorodeoxyglucose (FDG) PET/CT before radiotherapy. Routine chest CT was performed at the 3rd and 6th month after radiotherapy. The maximum standardized uptake value (SUVmax) of tumor and muscle, tumor volume and hypoxic volume (HV) were measured. Tumor-to-muscle (T/M) value of 18F-FMISO was calculated, and T/M ≥1.3 was considered as the hypoxia cut-off value. Data were analyzed using Pearson correlation, paired t test, signed rank sum test and Wilcoxon rank sum test. Results Totally 81.0%(17/21) of NSCLC patients had hypoxia. There were significant positive correlations between 18F-FMISO T/M value and tumor volume or 18F-FDG SUVmax (r: 0.72, 0.60, both P<0.05). The T/M value after radiotherapy was significantly lower than that before radiotherapy (1.42±1.12 vs 2.08±0.71; t=3.62, P<0.05), and median HV was also significantly lower than that before radiotherapy (6.53 vs 12.41 cm3;z=-3.83, P<0.05). The median T/M values of effective group (n=14) and ineffective group (n=7) before radiotherapy were significantly different (2.14 vs 2.87; z=-2.27, P<0.05), and the median HV of 2 groups before radiotherapy was also significantly different (6.43 vs 10.20 cm3;z=-2.14, P<0.05). Conclusions Most NSCLC patients have hypoxia before radiotherapy. The larger tumor volume, the higher degree of hypoxia. Radiotherapy can alleviate the hypoxia of tumors. 18F-FMISO PET/CT imaging before radiotherapy can be used to predict the efficacy of patients with NSCLC. Key words: Carcinoma, non-small lung; Radiotherapy; Cell hypoxia; Positron-emission tomography; Tomography, X-ray computed; Nitroimidazoles

Thorax CT Dose Reduction Based on Patient Features: Effect of Patient Characteristics on Image Quality and Effective Dose.

Computed tomography (CT) radiation dose reduction is vital without compromising image quality. The aim was to determine the effects of patient characteristics on the received radiation dose and image quality in chest CT examinations and to be able to predict dose and image quality prior to scanning. Consecutive 230 patients underwent routine chest CT examinations were included. CT examination and patients input parameters were recorded for each patient. The effect of patients' demographics/anthropometrics on received dose and image quality was investigated by linear regression analysis. All parameters were evaluated using an artificial neural network (ANN). Of all parameters, patient demographics/anthropometrics were found to be 98% effective in calculating dose reduction. Using ANN on 60 new patients was more than 90% accurate for output parameters and 91% for image quality. Patient characteristics have a significant impact on radiation dose and image quality. Dose and image quality can be determined before CT. This will allow setting the most appropriate scanning parameters before the CT scan.

Ultralow Dose Dynamic Expiratory Computed Tomography for Evaluation of Tracheomalacia.

The aim of this study was to determine the average effective radiation dose and feasibility of ultralow dose dynamic expiratory computed tomography (CT) for evaluation of tracheomalacia (ULD) and to evaluate factors that impact image quality. This is a retrospective study of 64 consecutive patients from September to October 2016 for the evaluation of tracheomalacia. All studies were performed with routine inspiration chest CT followed by ULD z(kilovoltage peak (kVp) 80, 100, or 120 and fixed milliamperage 10) or typical dose CT (TD) (kVp 100 or 120 with automated milliamperage) dynamic expiration CT. Image quality was considered diagnostic if the trachea area could be accurately measured for tracheomalacia assessment, and diagnostic studies were graded fair, good, or excellent. Scan length, image quality, and effective radiation dose were compared for ULD versus TD and ULD at 100 kVp versus ULD at 80 kVp. For ULD studies, patient factors were compared across image quality. The ULD had a mean effective radiation dose of 0.08 mSv, with all studies of diagnostic image quality. The ULD showed 95% reduction in effective radiation dose (P < 0.001), 14% significant reduction in scan length (P = 0.029), and qualitatively decreased image quality compared w2 ith TD (P < 0.001). The ULD at 100 kVp had significantly better image quality compared with ULD at 80 kVp (P = 0.041) with higher effective radiation dose (0.09 vs 0.05 mSv) (P < 0.001). Body mass index significantly impacted image quality for all ULD studies but not for ULD at 80 or 100 kVp. For evaluation of tracheomalacia, ULD showed low effective radiation dose less than 0.1 mSv and maintained diagnostic image quality.

Technique, pitfalls, quality, radiation dose and findings of dynamic 4-dimensional computed tomography for airway imaging in infants and children

This retrospective review of 33 children’s dynamic 4-dimensional (4-D) computed tomography (CT) images of the airways, performed using volume scanning on a 320-detector array without anaesthesia (free-breathing) and 1.4-s continuous scanning, was undertaken to report technique, pitfalls, quality, radiation doses and findings. Tracheobronchomalacia (airway diameter collapse >28%) was recorded. Age-matched routine chest CT scans and bronchograms acted as benchmarks for comparing effective dose. Pitfalls included failure to administer intravenous contrast, pull back endotracheal tubes and/or remove nasogastric tubes. Twenty-two studies (67%) were diagnostic. Motion artefact was present in 16 (48%). Mean effective dose: dynamic 4-D CT 1.0 mSv; routine CT chest, 1.0 mSv, and bronchograms, 1.4 mSv. Dynamic 4-D CT showed tracheobronchomalacia in 20 patients (61%) and cardiovascular abnormalities in 12 (36%). Fourteen children (70%) with tracheobronchomalacia were managed successfully by optimising conservative management, 5 (25%) underwent surgical interventions and 1 (5%) died from the presenting disorder.

Organ doses evaluation for chest computed tomography procedures with TL dosimeters: Comparison with Monte Carlo simulations.

PurposeTo evaluate organ doses in routine and low‐dose chest computed tomography (CT) protocols using an experimental methodology. To compare experimental results with results obtained by the National Cancer Institute dosimetry system for CT (NCICT) organ dose calculator. To address the differences on organ dose measurements using tube current modulation (TCM) and fixed tube current protocols.MethodsAn experimental approach to evaluate organ doses in pediatric and adult anthropomorphic phantoms using thermoluminescent dosimeters (TLDs) was employed in this study. Several analyses were performed in order to establish the best way to achieve the main results in this investigation. The protocols used in this study were selected after an analysis of patient data collected from the Institute of Radiology of the School of Medicine of the University of São Paulo (InRad). The image quality was evaluated by a radiologist from this institution. Six chest adult protocols and four chest pediatric protocols were evaluated. Lung doses were evaluated for the adult phantom and lung and thyroid doses were evaluated for the pediatric phantom. The irradiations were performed using both a GE and a Philips CT scanner. Finally, organ doses measured with dosimeters were compared with Monte Carlo simulations performed with NCICT.ResultsAfter analyzing the data collected from all CT examinations performed during a period of 3 yr, the authors identified that adult and pediatric chest CT are among the most applied protocol in patients in that clinical institution, demonstrating the relevance on evaluating organ doses due to these examinations. With regards to the scan parameters adopted, the authors identified that using 80 kV instead of 120 kV for a pediatric chest routine CT, with TCM in both situations, can lead up to a 28.7% decrease on the absorbed dose. Moreover, in comparison to the standard adult protocol, which is performed with fixed mAs, TCM, and ultra low‐dose protocols resulted in dose reductions of up to 35.0% and 90.0%, respectively. Finally, the percent differences found between experimental and Monte Carlo simulated organ doses were within a 20% interval.ConclusionsThe results obtained in this study measured the impact on the absorbed dose in routine chest CT by changing several scan parameters while the image quality could be potentially preserved.

Routine CT scanning of patients retrieved to a tertiary centre on veno-venous extracorporeal membrane oxygenation: a retrospective risk benefit analysis.

Comprehensive clinical examination can be compromised in patients on veno-venous extracorporeal membrane oxygenation (VV-ECMO). Adjunctive diagnostic imaging strategies range from bedside imaging only to routine computed tomography (CT). The risk-benefit of either approach remains to be evaluated. Patients retrieved to the Royal Brompton Hospital (RBH) on VV-ECMO routinely undergo admission CT imaging of head, chest, abdomen and pelvis. This study aimed to identify how frequently changes in therapy or adverse events could be attributed to routine CT scanning. Demographic and clinical data were gathered retrospectively from patients retrieved to RBH on VV-ECMO (January 2014-2016). Scans were categorized as 'routine' or requested to clarify a specific clinical uncertainty. Clinical records were reviewed to identify attributable management changes and CT- related adverse events. Seventy-two patients were retrieved on VV-ECMO (median age 44 years) and 65 scanned on admission (mean radiation dose 2344mGy-cm). Routine head CT head yielded novel clinical information in 11 patients, 10 of whom had unexpected intracranial haemorrhage and, subsequently, had their anticoagulation withheld. Routine thoracic CT identified unexpected positive findings in three patients (early fibrosis, pulmonary vasculitis, pneumomediastinum), eliciting management variation in one (steroid administration). Routine abdomen/pelvis CT identified new information in three patients (adrenal haemorrhage, hepatosteatosis, splenic infarction), changing the management in one (withholding anticoagulation). CT scanning was not associated with consequential adverse events (e.g. accidental decannulation, gas entrainment into the circuit, hypoxia, hypotension). Median transfer/scan time was 78 minutes, requiring five ITU staff-members. In our cohort, a policy of routine head CT changed the management in 17% of patients; the yield from routine chest, abdomen and pelvis CT was modest. CT transfer was safe, but resource intensive. Prospective studies should evaluate whether routine CT impacts outcome.