Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT

Whole-body low-dose CT can be of value in prostate cancer decision-making: a retrospective study on 601 patients

OBJECTIVES

To evaluate the diagnostic value of whole-body low-dose computed tomography (CT) to detect bone metastasis in prostate cancer (PCa) patients and its possible utility in therapeutic decision-making. Also, to determine the valuable CT features for lesion characterisation.

METHODS

This IRB-approved retrospective study reviewed PCa patients who underwent ⁶⁸Ga-PSMA PET/CT in our centre from March 2017 to August 2022. Two board-certified radiologists and one nuclear medicine specialist reported all whole-body low-dose CT scans separately, unaware of the ⁶⁸Ga-PSMA-PET results. The per-lesion and per-patient diagnostic performances were calculated. Also, the significance of CT features was evaluated. Moreover, the inter-observer agreement was analysed. A two-tailed p value < 0.05 was considered significant.

RESULTS

From 727 reviewed PCa patients, 601 (mean age = 68.7 ± 8.1) were found to be eligible, including 211 (35.1%) referrals for initial staging and 390 (64.9%) for evaluating the extent of the disease after biochemical recurrence. Per-patient diagnostic analysis for three reviewers showed 81.0-89.4% sensitivity and 96.6-98.5% specificity in detecting osteo-metastasis. It was able to correctly detect high-burden disease based on both CHAARTED and LATITUDE criteria. Regarding the value of underlying CT features, size > 1 cm, ill-defined borders, presence of soft-tissue component, and cortical destruction were statistically in favour of metastasis. Also, Hu > 900 was in favour of benign entities with 93% specificity.

CONCLUSIONS

Although not as accurate as ⁶⁸Ga-PSMA PET/CT, whole-body low-dose CT might precisely classify PCa patients considering therapeutic decision-making. Additionally, we proposed diagnostic CT features that could help radiologists with better characterisation of the detected lesions.

CRITICAL RELEVANCE STATEMENT

The whole-body low-dose CT can be considered valuable in the clinical decision-making of prostate cancer patients. This modality may obviate performing multiple imaging sessions and high-cost scans in patients diagnosed with the high-burden disease.

Artificial Intelligence Assisted Computational Tomographic Detection of Lung Nodules for Prognostic Cancer Examination: A Large-Scale Clinical Trial

Low-dose computed tomography (LDCT) has emerged as a standard method for detecting early-stage lung cancer. However, the tedious computer tomography (CT) slide reading, patient-by-patient check, and lack of standard criteria to determine the vague but possible nodule leads to variable outcomes of CT slide interpretation. To determine the artificial intelligence (AI)-assisted CT examination, AI algorithm-assisted CT screening was embedded in the hospital picture archiving and communication system, and a 200 person-scaled clinical trial was conducted at two medical centers. With AI algorithm-assisted CT screening, the sensitivity of detecting nodules sized 4−5 mm, 6~10 mm, 11~20 mm, and >20 mm increased by 41%, 11.2%, 10.3%, and 18.7%, respectively. Remarkably, the overall sensitivity of detecting varied nodules increased by 20.7% from 67.7% to 88.4%. Furthermore, the sensitivity increased by 18.5% from 72.5% to 91% for detecting ground glass nodules (GGN), which is challenging for radiologists and physicians. The free-response operating characteristic (FROC) AI score was ≥0.4, and the AI algorithm standalone CT screening sensitivity reached >95% with an area under the localization receiver operating characteristic curve (LROC-AUC) of >0.88. Our study demonstrates that AI algorithm-embedded CT screening significantly ameliorates tedious LDCT practices for doctors.

Necessity of Thin Section CT in the Detection of Pulmonary Metastases: Comparison between 5 mm and 1 mm Sections of CT

Background: The aim of this study was to evaluate the difference in the ability of 1-mm and 5-mm section Computed Tomography(CT) to detect pulmonary metastases in patients with pulmonary metastases.

Methods: We retrospectively analyzed the CT findings of 106 patients with pulmonary metastases due to malignancies treated at Toho University Omori Medical Center between 2013 and 2020.

Results: Cases with only one nodule evaluated by 5-mm section CT had significantly lower discordance with 1-mm section CT than cases with two or more nodules detected by a 5 mm section (p = 0.0161). After reference to a 1 mm section, cases with only one nodule reevaluated by 5-mm section CT had significantly lower discordance than cases with two or more nodules reevaluated using 5-mm section CT. In cases with only one nodule, reevaluation using a 5 mm section was consistent with evaluation using a 1 mm section. However, this was not observed in cases with two or more nodules, with a significant difference between one nodule and two or more nodules.

Conclusions: If there are two or more nodules observed in 5-mm section CT it may be necessary to reevaluate using 1-mm section CT to determine the exact number of pulmonary metastases.

Consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography

Background

To study the consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography (LDCT), and to analyze factors that affect the consistency.

Methods

A total of 750 LDCT cases were collected randomly from three medical centers. Three experienced chest radiologists independently evaluated and detected the pulmonary nodules on 625 cases of LDCT images. The detected nodules were classified into 3 groups: group I (detected by all radiologists); group II (detected by two radiologists); group III (detected by only one radiologist). The consistency with respect to the image features of individual nodules was assessed.

Results

A total of 1,206 nodules were identified by the three radiologists. There were 234 (19.4%) nodules in group I, 377 (31.3%) nodules in group II, and 595 (49.3%) nodules in group III. Logistic regression showed that the size, density, and location of the nodules correlated with the detection of nodules. Nodules sized great than or equal to 4 mm were more consistently identified than nodules sized less than 4 mm. Solid and calcified nodules were more consistently identified than sub-solid nodules. Nodules located in the outer zone were more consistently identified than hilar nodules.

Conclusions

There was considerable inter-reader variability with respect to identification of pulmonary nodules in LDCT. Larger nodules, solid or calcified nodules, and nodules located in the outer zone were more consistently identified.

Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies

Lung cancer is one of the major causes of cancer-related deaths due to its aggressive nature and delayed detections at advanced stages. Early detection of lung cancer is very important for the survival of an individual, and is a significant challenging problem. Generally, chest radiographs (X-ray) and computed tomography (CT) scans are used initially for the diagnosis of the malignant nodules; however, the possible existence of benign nodules leads to erroneous decisions. At early stages, the benign and the malignant nodules show very close resemblance to each other. In this paper, a novel deep learning-based model with multiple strategies is proposed for the precise diagnosis of the malignant nodules. Due to the recent achievements of deep convolutional neural networks (CNN) in image analysis, we have used two deep three-dimensional (3D) customized mixed link network (CMixNet) architectures for lung nodule detection and classification, respectively. Nodule detections were performed through faster R-CNN on efficiently-learned features from CMixNet and U-Net like encoder-decoder architecture. Classification of the nodules was performed through a gradient boosting machine (GBM) on the learned features from the designed 3D CMixNet structure. To reduce false positives and misdiagnosis results due to different types of errors, the final decision was performed in connection with physiological symptoms and clinical biomarkers. With the advent of the internet of things (IoT) and electro-medical technology, wireless body area networks (WBANs) provide continuous monitoring of patients, which helps in diagnosis of chronic diseases-especially metastatic cancers. The deep learning model for nodules' detection and classification, combined with clinical factors, helps in the reduction of misdiagnosis and false positive (FP) results in early-stage lung cancer diagnosis. The proposed system was evaluated on LIDC-IDRI datasets in the form of sensitivity (94%) and specificity (91%), and better results were obatined compared to the existing methods.

Radiologist performance in the detection of lung cancer using CT

AIM

To measure the level of radiologists' performance in lung cancer detection, and to explore radiologists' performance in cancer specialised and non-specialised centres.

MATERIALS AND METHODS

Thirty radiologists read 60 chest computed tomography (CT) examinations. Thirty cases had surgically or biopsy-proven lung cancer and 30 were cancer-free cases. The cancer cases were validated by four expert radiologists who located the malignant lung nodules. Reader performance was evaluated by calculating sensitivity, location sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC). In addition, sensitivity at fixed specificity (0.794) was computed from each reader's estimated ROC curve.

RESULTS

The radiologists had a mean sensitivity of 0.749, sensitivity at fixed specificity of 0.744, location sensitivity of 0.666, specificity of 0.81 and AUC of 0.846. Radiologists in the specialised and non-specialised cancer centres had the following (specialised, non-specialised) pairs of values: sensitivity=(0.80, 0.719); sensitivity for fixed 0.794 specificity=(0.752, 0.740); location sensitivity=(0.712, 0.637); specificity=(0.794, 0.82) and AUC=(0.846, 0.846).

CONCLUSION

The efficacy of radiologists was comparable to other studies. Furthermore, AUC outcomes were similar for specialised and non-specialised cancer centre radiologists, suggesting they have similar discriminatory ability and that the higher sensitivity and lower specificity for specialised-centre radiologists can be attributed to them being less conservative in interpreting case images.

Lung cancer screening: nodule identification and characterization

The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.

Added value of double reading in diagnostic radiology,a systematic review

Objectives

Double reading in diagnostic radiology can find discrepancies in the original report, but a systematic program of double reading is resource consuming. There are conflicting opinions on the value of double reading. The purpose of the current study was to perform a systematic review on the value of double reading.

Methods

A systematic review was performed to find studies calculating the rate of misses and overcalls with the aim of establishing the added value of double reading by human observers.

Results

The literature search resulted in 1610 hits. After abstract and full-text reading, 46 articles were selected for analysis. The rate of discrepancy varied from 0.4 to 22% depending on study setting. Double reading by a sub-specialist, in general, led to high rates of changed reports.

Conclusions

The systematic review found rather low discrepancy rates. The benefit of double reading must be balanced by the considerable number of working hours a systematic double-reading scheme requires. A more profitable scheme might be to use systematic double reading for selected, high-risk examination types. A second conclusion is that there seems to be a value of sub-specialisation for increased report quality. A consequent implementation of this would have far-reaching organisational effects.

Key Points

• In double reading, two or more radiologists read the same images.

• A systematic literature review was performed.

• The discrepancy rates varied from 0.4 to 22% in various studies.

• Double reading by sub-specialists found high discrepancy rates.

Electronic supplementary material

The online version of this article (10.1007/s13244-018-0599-0) contains supplementary material, which is available to authorised users.

Low-dose attenuation correction in diagnosis of non-alcoholic fatty liver disease

BACKGROUND

Non-enhanced computed tomography (CT) is a valuable modality in the diagnosis of non-alcoholic fatty liver disease (NAFLD). However, it is not clear if low-dose CT attenuation correction (CTAC) scans have the same accuracy to diagnose NAFLD. Our aim is to evaluate the diagnostic accuracy of low-dose CTAC in the diagnosis of NAFLD using non-enhanced CT as a gold standard.

METHODS

A total of 864 patients who underwent a clinically indicated hybrid nuclear imaging scanning between May 2011 and April 2014 were included in the study. Diagnosis of fatty liver was established if an absolute liver attenuation was <40 Hounsfield units and/or a liver-to-spleen ratio was <1.1. The diagnostic accuracy parameters were calculated to detect NAFLD by low-dose CTAC using unenhanced CT as a gold standard.

RESULTS

The prevalence of fatty liver by diagnostic CT and low-dose attenuation correction were 9.9 and 12.9% (using liver attenuation <40HU and liver-to-spleen ratio <1.1), respectively, with 32.9 and 34.9% (using absolute liver attenuation or ratio-to-spleen criteria), correspondingly. Low-dose CTAC had sensitivity (81.3%), specificity (94.0%), positive predictive value (60.2%), and negative predictive value (97.8%) using both diagnostic criteria. Using either of the diagnostic criteria resulted in sensitivity (76.8%), specificity (83.5%), PPV (66.3%), and NPV (89.5%).

CONCLUSION

Low-dose CT could be used as a tool to rule out the presence of fatty liver if neither liver attenuation of less than 40 HU nor liver-to-spleen below 1.1 is present.

The impact of trained radiographers as concurrent readers on performance and reading time of experienced radiologists in the UK Lung Cancer Screening (UKLS) trial

Objectives

To compare radiologists’ performance reading CTs independently with their performance using radiographers as concurrent readers in lung cancer screening.

Methods

369 consecutive baseline CTs performed for the UK Lung Cancer Screening (UKLS) trial were double-read by radiologists reading either independently or concurrently with a radiographer. In concurrent reading, the radiologist reviewed radiographer-identified nodules and then detected any additional nodules. Radiologists recorded their independent and concurrent reading times. For each radiologist, sensitivity, average false-positive detections (FPs) per case and mean reading times for each method were calculated.

Results

694 nodules in 246/369 (66.7%) studies comprised the reference standard. Radiologists’ mean sensitivity and average FPs per case both increased with concurrent reading compared to independent reading (90.8 ± 5.6% vs. 77.5 ± 11.2%, and 0.60 ± 0.53 vs. 0.33 ± 0.20, respectively; p < 0.05 for 3/4 and 2/4 radiologists, respectively). The mean reading times per case decreased from 9.1 ± 2.3 min with independent reading to 7.2 ± 1.0 min with concurrent reading, decreasing significantly for 3/4 radiologists (p < 0.05).

Conclusions

The majority of radiologists demonstrated improved sensitivity, a small increase in FP detections and a statistically significantly reduced reading time using radiographers as concurrent readers.

Key Points

• Radiographers as concurrent readers could improve radiologists’ sensitivity in lung nodule detection.

• An increase in false-positive detections with radiographer-assisted concurrent reading occurred.

• The false-positive detection rate was still lower than reported for computer-aided detection.

• Concurrent reading with radiographers was also faster than single reading.

• The time saved per case using concurrently reading radiographers was relatively modest.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4903-z) contains supplementary material, which is available to authorized users.

Role of Computer Aided Diagnosis (CAD) in the detection of pulmonary nodules on 64 row multi detector computed tomography

AIMS AND OBJECTIVES

To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT) in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location.

MATERIALS AND METHODS

A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD) and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP) rate of CAD software was calculated.

OBSERVATIONS AND RESULTS

Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2%) and 202 (91.4%) by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4-10 mm (93.4%) and nodules in hilar (100%) and central (96.5%) location when compared to RAD's performance.

CONCLUSION

CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD's performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time.

Comparing the performance of trained radiographers against experienced radiologists in the UK lung cancer screening (UKLS) trial

OBJECTIVE

To compare the performance of radiographers against that of radiologists for CT lung nodule detection in the UK Lung Cancer Screening (UKLS) pilot trial.

METHODS

Four radiographers, trained in CT nodule detection, and three radiologists were prospectively evaluated. 290 CTs performed for the UKLS were independently read by 2 radiologists and 2 radiographers. The reference standard comprised all radiologist-identified positive nodules after arbitration of discrepancies. For each radiographer and radiologist, relative sensitivity and average false positives (FPs) per case were compared for all cases read, as well as for subsets of cases read by each radiographer-radiologist combination (10 combinations).

RESULTS

599 nodules in 209/290 (72.1%) CT studies comprised the reference standard. The relative mean (±standard deviation) sensitivity of the four radiographers was 71.6 ± 8.5% compared with 83.3 ± 8.1% for the three radiologists. Radiographers were less sensitive and detected more FPs per case than radiologists in 7/10 and 8/10 radiographer-radiologist combinations, respectively (ranges of difference 11.2-33.8% and 0.4-2.6; p < 0.05). In 3/10 and 2/10 combinations, there was no difference in sensitivity and FPs per case between radiographers and radiologists. For nodules ≥100 mm(3) in volume or ≥5 mm in maximum diameter, radiographers were relatively less sensitive than radiologists in only 5/10 radiographer-radiologist combinations (range of difference 16.1-30.6%; p < 0.05) and not significantly different in the remaining 5/10 combinations.

CONCLUSION

Although overall radiographer performance was lower than that of experienced radiologists in this study, some radiographer performances were comparable with that of radiologists.

ADVANCES IN KNOWLEDGE

Overall, radiographers were less sensitive than radiologists reading the same CTs and also displayed higher average FP detections per case when compared with a reference standard derived from radiologist readings. However, some radiographers compared favourably with radiologists, especially when considering larger potentially clinically relevant nodules. Thus, while probably not sensitive enough to function as first readers, radiographers may still be able to fulfil the role of an assistant reader-that is, as a first or concurrent reader, who presents detected nodules for verification to a reading radiologist.

The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer

BACKGROUND

Lung cancer kills more people than any other cancer in the UK (5-year survival < 13%). Early diagnosis can save lives. The USA-based National Lung Cancer Screening Trial reported a 20% relative reduction in lung cancer mortality and 6.7% all-cause mortality in low-dose computed tomography (LDCT)-screened subjects.

OBJECTIVES

To (1) analyse LDCT lung cancer screening in a high-risk UK population, determine optimum recruitment, screening, reading and care pathway strategies; and (2) assess the psychological consequences and the health-economic implications of screening.

DESIGN

A pilot randomised controlled trial comparing intervention with usual care. A population-based risk questionnaire identified individuals who were at high risk of developing lung cancer (≥ 5% over 5 years).

SETTING

Thoracic centres with expertise in lung cancer imaging, respiratory medicine, pathology and surgery: Liverpool Heart & Chest Hospital, Merseyside, and Papworth Hospital, Cambridgeshire.

PARTICIPANTS

Individuals aged 50-75 years, at high risk of lung cancer, in the primary care trusts adjacent to the centres.

INTERVENTIONS

A thoracic LDCT scan. Follow-up computed tomography (CT) scans as per protocol. Referral to multidisciplinary team clinics was determined by nodule size criteria.

MAIN OUTCOME MEASURES

Population-based recruitment based on risk stratification; management of the trial through web-based database; optimal characteristics of CT scan readers (radiologists vs. radiographers); characterisation of CT-detected nodules utilising volumetric analysis; prevalence of lung cancer at baseline; sociodemographic factors affecting participation; psychosocial measures (cancer distress, anxiety, depression, decision satisfaction); and cost-effectiveness modelling.

RESULTS

A total of 247,354 individuals were approached to take part in the trial; 30.7% responded positively to the screening invitation. Recruitment of participants resulted in 2028 in the CT arm and 2027 in the control arm. A total of 1994 participants underwent CT scanning: 42 participants (2.1%) were diagnosed with lung cancer; 36 out of 42 (85.7%) of the screen-detected cancers were identified as stage 1 or 2, and 35 (83.3%) underwent surgical resection as their primary treatment. Lung cancer was more common in the lowest socioeconomic group. Short-term adverse psychosocial consequences were observed in participants who were randomised to the intervention arm and in those who had a major lung abnormality detected, but these differences were modest and temporary. Rollout of screening as a service or design of a full trial would need to address issues of outreach. The health-economic analysis suggests that the intervention could be cost-effective but this needs to be confirmed using data on actual lung cancer mortality.

CONCLUSIONS

The UK Lung Cancer Screening (UKLS) pilot was successfully undertaken with 4055 randomised individuals. The data from the UKLS provide evidence that adds to existing data to suggest that lung cancer screening in the UK could potentially be implemented in the 60-75 years age group, selected via the Liverpool Lung Project risk model version 2 and using CT volumetry-based management protocols.

FUTURE WORK

The UKLS data will be pooled with the NELSON (Nederlands Leuvens Longkanker Screenings Onderzoek: Dutch-Belgian Randomised Lung Cancer Screening Trial) and other European Union trials in 2017 which will provide European mortality and cost-effectiveness data. For now, there is a clear need for mortality results from other trials and further research to identify optimal methods of implementation and delivery. Strategies for increasing uptake and providing support for underserved groups will be key to implementation.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN78513845.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 40. See the NIHR Journals Library website for further project information.

An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information

Lack of human resources and radiological interpretation expertise impair tuberculosis (TB) screening programmes in TB-endemic countries. Computer-aided detection (CAD) constitutes a viable alternative for chest radiograph (CXR) reading. However, no automated techniques that exploit the additional clinical information typically available during screening exist. To address this issue and optimally exploit this information, a machine learning-based combination framework is introduced. We have evaluated this framework on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa. Each record comprised a CAD score, automatically computed from a CXR, and 12 clinical features. Comparisons with strategies relying on either CAD scores or clinical information alone were performed. Our results indicate that the combination framework outperforms the individual strategies in terms of the area under the receiving operating characteristic curve (0.84 versus 0.78 and 0.72), specificity at 95% sensitivity (49% versus 24% and 31%) and negative predictive value (98% versus 95% and 96%). Thus, it is believed that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

Objective

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules.

Materials and Methods

Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically.

Results

Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00).

Conclusion

Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Screening for lung cancer with low-dose computed tomography: a review of current status

Screening using low-dose computed tomography (CT) represents an exciting new development in the struggle to improve outcomes for people with lung cancer. Randomised controlled evidence demonstrating a 20% relative lung cancer mortality benefit has led to endorsement of screening by several expert bodies in the US and funding by healthcare providers. Despite this pivotal result, many questions remain regarding technical and logistical aspects of screening, cost-effectiveness and generalizability to other settings. This review discusses the rationale behind screening, the results of on-going trials, potential harms of screening and current knowledge gaps.

[Pharmacological therapy of urogenital cancer: rational routine diagnostic imaging]

BACKGROUND

Imaging studies are an integral and important diagnostic modality to stage, monitor, and follow-up patients with metastatic urogenital cancer. The currently available guidelines on diagnosis and treatment of urogenital cancer do not provide the clinician with evidence-based recommendations for daily routine. It is the aim of the current manuscript to develop scientifically valid recommendations with regard to the most appropriate imaging technique and the most useful time interval in metastatic urogenital cancer patients undergoing systemic therapy.

RESULTS

Therapeutic response of soft tissue metastases is evaluated with the use of the RECIST criteria. In skeletal metastases, bone scans with validated algorithms must be performed to assess response. In patients with testicular germ cell tumors, computed tomography (CT) of the chest, the retroperitoneum, and the abdomen represents the standard imaging technique of choice usually performed prior to and at the end of systemic chemotherapy. Only in seminomas with residual tumors > 3 cm in diameter should FDG-PET/CT be performed about 6 weeks after chemotherapy. Metastatic renal cell carcinomas treated with molecular targeted therapies are routinely evaluated by CT scans at 3 month intervals. In specific cases, FDG-PET/CT is able to predict responses as early as 8 weeks after initiation of treatment. In patients with metastatic urothelial carcinomas, imaging studies should be performed after every second cycle of cytotoxic therapy. In patients with metastatic prostate cancer, the modality and the frequency of imaging studies depends on the type of the treatment. In men undergoing androgen deprivation therapy, no routine imaging studies are recommended except for patients with new onset symptoms or significant PSA progression prior to change of treatment. In men with metastatic castration-resistant PCA who are treated with cytotoxic regimes, routine imaging studies in the presence of decreasing or stable PSA serum concentrations are not indicated. In men treated with lyase inhibitor or inhibitors of the androgen receptor signaling cascade, imaging studies should be performed at 3 month intervals due to the low correlation of PSA serum concentrations with clinical response.

CONCLUSIONS

Imaging studies to assess therapeutic response to systemic treatment in metastatic cancers of the urogenital tract must be chosen depending on the treatment regime, primary organ, and potential consequences of the findings. Routine imaging studies without specific clinical or therapeutic relevance are not justified.

Queensland Lung Cancer Screening Study: rationale, design and methods

BACKGROUND

Lung cancer is the leading cause of cancer-related mortality in Australia. Screening using low-dose computed tomography (LDCT) can reduce lung cancer mortality. The feasibility of screening in Australia is unknown. This paper describes the rationale, design and methods of the Queensland Lung Cancer Screening Study.

AIMS

The aim of the study is to describe the methodology for a feasibility study of lung cancer screening by LDCT in Australia.

METHODS

The Queensland Lung Cancer Screening Study is an ongoing, prospective observational study of screening by LDCT at a single tertiary institution. Healthy volunteers at high risk of lung cancer (age 60-74 years; smoking history ≥30 pack years, current or quit within 15 years; forced expiratory volume in 1s ≥50% predicted) are recruited from the general public through newspaper advertisement and press release. Participants receive a LDCT scan of the chest at baseline, year 1 and year 2 using a multidetector helical computed tomography scanner and are followed up for a total of 5 years. Feasibility of screening will be assessed by cancer detection rates, lung nodule prevalence, optimal management strategies for lung nodules, economic costs, healthcare utilisation and participant quality of life.

CONCLUSIONS

Studying LDCT screening in the Australian setting will help us understand how differences in populations, background diseases and healthcare structures modulate screening effectiveness. This information, together with results from overseas randomised studies, will inform and facilitate local policymaking.

Non-solid lung nodules on low-dose computed tomography: comparison of detection rate between 3 visualization techniques

Objective: To compare various visualization techniques for the detection of non-solid nodules in low-dose lung cancer screening computed tomography (CT) scans. Methods: An enriched sample of 216 male lung cancer screening subjects aged 60.4 ± 6.0 years was used. Two blinded independent readers searched for non-solid nodules on 5-mm multiplanar reconstructions, 1-mm slices and 7-mm maximum intensity projections (trial protocol). The reference standard was a consensus diagnosis of all non-solid nodules reported at least once. Results: Twenty-three individuals (10.6%) had in total 34 non-solid nodules. Interobserver agreement was good (Cohen kappa 0.89–0.95). For both observers, we found no differences between the 3 viewing techniques (P > 0.13). Conclusion: In low-dose lung cancer screening CT scans, we were unable to find a viewing technique superior to that used in the trial by experienced observers who focused on non-solid nodule detection.

Low-dose CT: technique, reading methods and image interpretation

The National Lung Cancer Screening Trial has recently demonstrated that screening of high-risk populations with the use of low-dose computed tomography (LDCT) reduces lung cancer mortality^[1]. Based on this encouraging result, the National Comprehensive Cancer Network guidelines recommended LDCT for selected patients at high risk of lung cancer^[2]. This suggests that an increasing number of CT screening examinations will be performed. The LDCT technique is relatively simple but some CT parameters are important and should be accurately defined in order to achieve good diagnostic quality and minimize the delivered dose. In addition, LDCT examinations are not as easy to read as they may initially appear; different approaches and tools are available for nodule detection and measurement. Moreover, the management of positive results can be a complex process and can differ significantly from routine clinical practice. Therefore this paper deals with the LDCT technique, reading methods and interpretation in lung cancer screening, particularly for those radiologists who have little experience of the technique.

From randomized trials to the clinic: is it time to implement individual lung-cancer screening in clinical practice? A multidisciplinary statement from French experts on behalf of the French intergroup (IFCT) and the groupe d'Oncologie de langue francaise (GOLF)

Background

Despite advances in cancer therapy, mortality is still high except in early-stage tumors, and screening remains a challenge. The randomized National Lung Screening Trial (NLST), comparing annual low-dose computed tomography (LDCT) and chest X-rays, revealed a 20% decrease in lung-cancer-specific mortality. These results raised numerous questions. The French intergroup for thoracic oncology and the French-speaking oncology group convened an expert group to provide a coherent outlook on screening modalities in France.

Methods

A literature review was carried out and transmitted to the expert group, which was divided into three workshops to tackle specific questions, with responses presented in a plenary session. A writing committee drafted this article.

Results

The multidisciplinary group favored individual screening in France, when carried out as outlined in this article and after informing subjects of the benefits and risks. The target population involves subjects aged 55–74 years, who are smokers or have a 30 pack-year smoking history. Subjects should be informed about the benefits of quitting. Screening should involve LDCT scanning with specific modalities. Criteria for CT positivity and management algorithms for positive examinations are given.

Conclusions

Individual screening requires rigorous assessment and precise research in order to potentially develop a lung-cancer screening policy.

Clinical implications and added costs of incidental findings in an early detection study of lung cancer by using low-dose spiral computed tomography

INTRODUCTION

To prospectively evaluate the frequency and spectrum of incidental findings (IF) in a 5-year lung cancer screening program with low-dose spiral computed tomography (CT) and to estimate the additional costs of their imaging workup incurred from subsequent radiologic follow-up evaluation.

MATERIALS AND METHODS

A total of 519 asymptomatic volunteers were enrolled. All IFs were reported and were considered clinically relevant if they required further evaluations or with clinical implications if they required more than one additional diagnostic test for characterization or medical and/or surgical intervention.

RESULTS

IFs were commonly found (59.2%, 307/519 participants at baseline and 5.3% per year at 5-year follow-up [123 participants of 2341 LDsCT exams performed during follow-up], with an overall rate of 26.3%). IFs were categorized as previously unknown clinically relevant in 52 (10.0%) individuals at baseline. Of these, 36 (6.9%) individuals had IFs with clinical implications (10 clinically relevant, of which 6 had clinical implications, detected during the subsequent 5-year follow-up). The most common recommendations were for additional imaging of the thyroid and kidneys. Additional imaging was mainly performed by ultrasound (43/68 [63.2%]). Subsequent surgical intervention resulted from these findings in 7 (1.5%) subjects. Six malignancies were diagnosed (rate, 0.2% per year). Costs of subsequent radiologic follow-up studies were calculated as €4644.56 [U.S. $6575.04] at baseline and €1052.30 [U.S. $1489.69] at 5-year follow-up (average added costs per participant €8.95 [U.S. $12.67] and €2.25 [U.S. $3.19], respectively).

CONCLUSIONS

Low-dose spiral CT commonly detects IFs. Some of these require further investigations to assess their clinical relevance. Although such IFs add little clinical benefit to the screening intervention, moderate incremental costs are incurred based on additional radiologic procedures generated during short-term follow-up, given the potential for positive effects on patient care.

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume

Objective

To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmonary nodules on low-dose computed tomography (CT) by nodule volume.

Methods

A total of 400 low-dose chest CT examinations were randomly selected from the NELSON lung cancer screening trial. CTs were evaluated by two independent readers and processed by CAD. A total of 1,667 findings marked by readers and/or CAD were evaluated by a consensus panel of expert chest radiologists. Performance was evaluated by calculating sensitivity of pulmonary nodule detection and number of false positives, by nodule characteristics and volume.

Results

According to the screening protocol, 90.9 % of the findings could be excluded from further evaluation, 49.2 % being small nodules (less than 50 mm³). Excluding small nodules reduced false-positive detections by CAD from 3.7 to 1.9 per examination. Of 151 findings that needed further evaluation, 33 (21.9 %) were detected by CAD only, one of them being diagnosed as lung cancer the following year. The sensitivity of nodule detection was 78.1 % for double reading and 96.7 % for CAD. A total of 69.7 % of nodules undetected by readers were attached nodules of which 78.3 % were vessel-attached.

Conclusions

CAD is valuable in lung cancer screening to improve sensitivity of pulmonary nodule detection beyond double reading, at a low false-positive rate when excluding small nodules.

Key Points

• Computer-aided detection (CAD) has known advantages for computed tomography (CT).

• Combined CAD/nodule size cut-off parameters assist CT lung cancer screening.

• This combination improves the sensitivity of pulmonary nodule detection by CT.

• It increases the positive predictive value for cancer detection.

Double reading of radiological examinations in Norway

BACKGROUND

Double reading of images is a part of the quality assurance activities at many radiological centers.

PURPOSE

To investigate the extent of and routines for double reading in Norway and the institutional heads' attitudes toward double reading.

MATERIAL AND METHODS

A questionnaire was addressed to the heads of all radiological institutions in Norway. The questionnaire concerned staffing, examinations performed, extent of double reading per imaging modality (except mammography screening), guidelines for double reading, checks of completed radiology reports, frequency of regular quality assurance meetings to discuss missed findings, and the heads' attitudes toward double reading.

RESULTS

The response rate was 73% (53/73). The percentage across imaging modalities of examinations being double read was 41% overall: 56% at university hospitals, 37% at local hospitals, and 18% at private centers. Double reading was most common for positron emission tomography (PET)/PET-computed tomography (CT) examinations (100%), and clinical mammography (91%). Almost all examinations read by residents were double read. Only 15% of institutions had written guidelines for double reading, 15% performed random double readings of completed examinations, and 55% organized regular meetings to discuss missed findings. Forty-six percent of the institutional heads wanted an increased use of double reading.

CONCLUSION

Double reading is common in Norway, especially in residency training, mammography, and PET/PET-CT. It is less common at private centers. Established routines for double reading are scarce. Many institutional heads want more double reading. The potential of double reading to assure quality in radiology should be better exploited.

On combining computer-aided detection systems

Computer-aided detection (CAD) is increasingly used in clinical practice and for many applications a multitude of CAD systems have been developed. In practice, CAD systems have different strengths and weaknesses and it is therefore interesting to consider their combination. In this paper, we present generic methods to combine multiple CAD systems and investigate what kind of performance increase can be expected. Experimental results are presented using data from the ANODE09 and ROC09 online CAD challenges for the detection of pulmonary nodules in computed tomography scans and red lesions in retinal images, respectively. For both applications, combination results in a large and significant increase in performance when compared to the best individual CAD system.

Evaluation of a method of computer-aided detection (CAD) of pulmonary nodules with computed tomography

PURPOSE

The authors sought to compare the sensitivity and reading time obtained using computer-aided detection (CAD) software as second reader (SR) or concurrent reader (CR) in the identification of pulmonary nodules.

MATERIALS AND METHODS

Unenhanced CT scans of 100 consecutive cancer patients were retrospectively reviewed by four readers to identify all solid, noncalcified pulmonary nodules ranging from 3 to 30 mm in diameter. The sensitivity and reading time of each reader and of CAD alone were calculated at 3-mm and 5-mm thresholds with respect to the reference standard, consisting of a consensus reading by the four radiologists involved in the study. The McNemar test was used to compare the sensitivities obtained by reading without CAD (readers 1 and 2), with CAD as SR (readers 1 and 2 with a 2-month delay), and with CAD as CR (readers 3 and 4). The paired Student's t test was used to compare reading times. A value of p<0.05 was considered statistically significant.

RESULTS

A total of 258 and 224 nodules were identified at 3-mm and 5-mm thresholds, respectively. The sensitivity of CAD alone was 62.79% and 67.41% at the 3-mm and 5-mm threshold values respectively, with 4.15 and 2.96 false-positive findings per examination. CAD as SR produced a significant increase in sensitivity (p<0.001) in nodule detection with respect to reading without CAD both at 3 mm (12.01%) and 5 mm (10.04%); the average increase in sensitivity obtained when comparing CAD as SR to CAD as CR was statistically significant (p<0.025) both at the 3-mm (5.35%) and 5-mm (4.68%) thresholds. CAD as CR produced a nonsignificant increase in sensitivity compared with reading without CAD (p>0.05). Mean reading time using CAD as SR (330 s) was significantly longer than reading without CAD (135 s, p<0.001) and reading with CAD as CR (195 s, p<0.025).

CONCLUSIONS

The use of CAD as CR, without any significant increase in reading time, produces no significant increase in sensitivity in pulmonary nodule detection when compared with reading without CAD (p>0.05); CAD as SR, at the cost of longer reading times, increases sensitivity when compared with reading without CAD (p<0.001) or with CAD as CR (p<0.025).

Improved image quality of low-dose thoracic CT examinations with a new postprocessing software

In 2008 a phantom study indicated that there is a potential for reducing the CT doses when using a new postprocessing filter. The purpose of this study was to test this new postprocessing filter clinically for low-dose chest CT examinations, to assess whether the diagnostic performance is the same or improved. A standardized clinical chest CT protocol was used on patients with colorectal cancer. Only mA settings changed between patients according to patient size. One standard and one low-dose chest protocol were performed for all patients. The low-dose images were postprocessed with a new software filter, which provides context-controlled restoration of digital images by using adaptive filters. Three radiologists assessed randomly all the images independently. A total of 24 scan series were evaluated with respect to image quality according to quality criteria from the European guidelines for chest CT using a five-point scale; 576 details were assessed. Overall mean score is the average score for all details rated for all three readers for all full-dose series, low-dose series and low-dose enhanced series, respectively. The statistical methods used for comparison were paired sampled t-test and intraclass correlation coefficient. The postprocessing filter improved the diagnostic performance compared to the unenhanced low-dose images. Mean score for full-dose, low-dose and low-dose enhanced series were 3.8, 3.0 and 3.3, respectively. For all patients the full-dose series gave higher scores than the low-dose series. Intraclass correlation coefficients were 0.2, 0.1 and 0.3 for the full-dose, low-dose and low-dose enhanced series, respectively. There is a potential for improving diagnostic performance of low-dose CT chest examinations using this new postprocessing filter.

Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases

RATIONALE AND OBJECTIVES

Most studies of computer-aided detection (CAD) for pulmonary nodules have focused on solid nodule detection. The aim of this study was to evaluate the performance of a commercially available CAD system in the detection of pulmonary nodules with or without ground-glass opacity (GGO) using 64-detector-row computed tomography compared to visual interpretation.

MATERIALS AND METHODS

Computed tomographic examinations were performed on 48 patients with existing or suspicious pulmonary nodules on chest radiography. Three radiologists independently reported the location and pattern (GGO, solid, or part solid) of each nodule candidate on computed tomographic scans, assigned each a confidence score, and then analyzed all scans using the CAD system. A reference standard was established by a consensus panel of different radiologists, who found 229 noncalcified nodules with diameters > or = 4 mm. True-positive and false-positive results and confidence levels were used to generate jackknife alternative free-response receiver-operating characteristic plots.

RESULTS

The sensitivity of GGO for 3 radiologists (60%-80%) was significantly higher than that for the CAD system (21%) (McNemar's test, P < .0001). For overall and solid nodules, the figure-of-merit values without and with the CAD system were significantly different (P = .005-.04) on jackknife alternative free-response receiver-operating characteristic analysis. For GGO and part-solid nodules, the figure-of-merit values with the CAD system were greater than those without the CAD system, indicating no significant differences.

CONCLUSION

Radiologists are significantly superior to this CAD system in the detection of GGO, but the CAD system can still play a complementary role in detecting nodules with or without GGO.

Pediatric MDCT: towards assessing the diagnostic influence of dose reduction on the detection of small lung nodules

RATIONALE AND OBJECTIVES

The purpose of this study was to evaluate the effect of reduced tube current (dose) on lung nodule detection in pediatric multidetector array computed tomography (MDCT).

MATERIALS AND METHODS

The study included normal clinical chest MDCT images of 13 patients (aged 1-7 years) scanned at tube currents of 70 to 180 mA. Calibrated noise addition software was used to simulate cases as they would have been acquired at 70 mA (the lowest original tube current), 35 mA (50% reduction), and 17.5 mA (75% reduction). Using a validated nodule simulation technique, small lung nodules of 3 to 5 mm in diameter were inserted into the cases, which were then randomized and rated independently by three experienced pediatric radiologists for nodule presence on a continuous scale ranging from zero (definitely absent) to 100 (definitely present). The observer data were analyzed to assess the influence of dose on detection accuracy using the Dorfman-Berbaum-Mets method for multiobserver, multitreatment receiver-operating characteristic (ROC) analysis and the Williams trend test.

RESULTS

The areas under the ROC curves were 0.95, 0.91, and 0.92 at 70, 35, and 17.5 mA, respectively, with standard errors of 0.02 and interobserver variability of 0.02. The Dorfman-Berbaum-Mets method and the Williams trend test yielded P values for the effect of dose of .09 and .05, respectively.

CONCLUSION

Tube current (dose) has a weak effect on the detection accuracy of small lung nodules in pediatric MDCT. The effect on detection accuracy of a 75% dose reduction was comparable to interobserver variability, suggesting a potential for dose reduction.

Efficacy of computer-aided detection system and thin-slab maximum intensity projection technique in the detection of pulmonary nodules in patients with resected metastases

OBJECTIVES

To evaluate the efficacy of the computer-aided detection (CAD) system and thin-slab maximum intensity projection (MIP) technique in the detection of pulmonary nodules at multidetector computed tomography (CT) in patients who underwent metastatectomy.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board and patients' informed consent was waived. Forty-nine consecutive patients who underwent pulmonary metastatectomy were enrolled. Four chest radiologists analyzed preoperative 1-mm section CT images and recorded the locus of each nodule candidate. Afterward, they reevaluated the images once using CAD software and once with thin-slab MIP given the results of 1-mm section CT alone. The reference standard for nodule presence was established by a consensus panel and pathologic records for malignant nodules.

RESULTS

A total of 514 nodules were identified by a consensus panel. Of 212 nodules surgically removed, 121 nodules were malignant. The sensitivity of each observer in detecting malignant nodules with thin-section CT scans alone was 91%, 88%, 87%, and 86% for observers A- to D, respectively. With CAD, sensitivity increased significantly to 95%, 95%, 94%, and 95% (P< 0.05 for observer B-D), and using MIP increased to 94%, 96%, 91%, and 92% (P < 0.05 for observer B-D), respectively. There were no significant differences in sensitivity between CAD and MIP for the detection of malignant nodules. The average number of false-positive findings per patient was 0.8 with thin-section CT alone, 1.1 with CAD, and 1.4 with MIP.

CONCLUSIONS

In candidates for metastatectomy, reading with the aid of either CAD or MIP significantly improved the detection of malignant nodules compared with using thin-section CT alone.

Dosimetry of FDG PET/CT and other molecular imaging applications in pediatric patients

Effective doses for PET and SPECT imaging of molecular imaging agents depend on the radiopharmaceutical, administered activity and the weight of the patient. Effective doses for the accompanying CT scan depend on the CT protocol being used. CT protocols can be designed to produce diagnostic quality images, localization images or attenuation correction data without imaging. In each case, the co-registered molecular imaging examination (PET or SPECT) and the CT study must be acquired without patient movement. For PET/CT, attention to the respiratory phase during the CT study is also of critical importance. In addition to the molecular imaging agents (18)F-FDG and (123)I-MIBG that are frequently used in children, additional PET and SPECT imaging agents may have promise for molecular imaging in children.