Objective To estimate the cumulative radiation exposure and lifetime attributable risk of cancer incidence associated with lung cancer screening using annual low dose computed tomography (CT). Design Secondary analysis of data from a lung cancer screening trial and risk-benefit analysis. Setting 10 year, non-randomised, single centre, low dose CT, lung cancer screening trial (COSMOS study) which took place in Milan, Italy in 2004-15 (enrolment in 2004-05). Secondary analysis took place in 2015-16. Participants High risk asymptomatic smokers aged 50 and older, who were current or former smokers (≥20 pack years), and had no history of cancer in the previous five years. Main outcome measures Cumulative radiation exposure from low dose CT and positron emission tomography (PET) CT scans, calculated by dosimetry software; and lifetime attributable risk of cancer incidence, calculated from the Biological Effects of Ionizing Radiation VII (BEIR VII) report. Results Over 10 years, 5203 participants (3439 men, 1764 women) underwent 42 228 low dose CT and 635 PET CT scans. The median cumulative effective dose at the 10th year of screening was 9.3 mSv for men and 13.0 mSv for women. According to participants’ age and sex, the lifetime attributable risk of lung cancer and major cancers after 10 years of CT screening ranged from 5.5 to 1.4 per 10 000 people screened, and from 8.1 to 2.6 per 10 000 people screened, respectively. In women aged 50-54, the lifetime attributable risk of lung cancer and major cancers was about fourfold and threefold higher than for men aged 65 and older, respectively. The numbers of lung cancer and major cancer cases induced by 10 years of screening in our cohort were 1.5 and 2.4, respectively, which corresponded to an additional risk of induced major cancers of 0.05% (2.4/5203). 259 lung cancers were diagnosed in 10 years of screening; one radiation induced major cancer would be expected for every 108 (259/2.4) lung cancers detected through screening. Conclusion Radiation exposure and cancer risk from low dose CT screening for lung cancer, even if non-negligible, can be considered acceptable in light of the substantial mortality reduction associated with screening.

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PurposeTo assess the noise characteristics of the new adaptive statistical iterative reconstruction (ASiR‐V) in comparison to ASiR.MethodsA water phantom was acquired with common clinical scanning parameters, at five different levels of CTDIvol. Images were reconstructed with different kernels (STD, SOFT, and BONE), different IR levels (40%, 60%, and 100%) and different slice thickness (ST) (0.625 and 2.5 mm), both for ASiR‐V and ASiR. Noise properties were investigated and noise power spectrum (NPS) was evaluated.ResultsASiR‐V significantly reduced noise relative to FBP: noise reduction was in the range 23%–60% for a 0.625 mm ST and 12%–64% for the 2.5 mm ST. Above 2 mGy, noise reduction for ASiR‐V had no dependence on dose. Noise reduction for ASIR‐V has dependence on ST, being greater for STD and SOFT kernels at 2.5 mm. For the STD kernel ASiR‐V has greater noise reduction for both ST, if compared to ASiR. For the SOFT kernel, results varies according to dose and ST, while for BONE kernel ASIR‐V shows less noise reduction. NPS for CT Revolution has dose dependent behavior at lower doses. NPS for ASIR‐V and ASiR is similar, showing a shift toward lower frequencies as the IR level increases for STD and SOFT kernels. The NPS is different between ASiR‐V and ASIR with BONE kernel. NPS for ASiR‐V appears to be ST dependent, having a shift toward lower frequencies for 2.5 mm ST.ConclusionsASiR‐V showed greater noise reduction than ASiR for STD and SOFT kernels, while keeping the same NPS. For the BONE kernel, ASiR‐V presents a completely different behavior, with less noise reduction and modified NPS. Noise properties of the ASiR‐V are dependent on reconstruction slice thickness. The noise properties of ASiR‐V suggest the need for further measurements and efforts to establish new CT protocols to optimize clinical imaging.

• This study demonstrated a lower iodine uptake in metastatic than non-metastatic LNs. • Internal distribution of HU was different between metastatic and non-metastatic lymph nodes. • The intranodal iodine distribution disclosed a remarkable correlation with the histological LN structure.

Single-photon emission computed tomography combined with X-ray computed tomography (SPECT/CT) improves diagnostic accuracy by allowing better localization and definition of scintigraphic findings. However, the combined acquisition of functional and anatomical images can substantially increase radiation exposure to patients, particularly when using a hybrid system with diagnostic CT capabilities. At the same time, the introduction of new SPECT and CT reconstruction techniques (based on the use of iterative algorithms), and of CT automatic dose modulation techniques, has opened the way for possible reductions in patient dose and/or improvements of image quality. It is, therefore, essential to carefully balance the diagnostic needs and the radiation protection requirements, optimizing the choice of radiopharmaceutical and administered activity, and the image acquisition and processing modalities both in SPECT and in CT. This is particularly important in the case of pediatric examinations. In short, to maximize benefit to patients, SPECT/CT studies have to be optimized, adopting dose-reduction measures both from CT and SPECT practices. In SPECT, shorter lived gamma emitters should be preferred and the amount of activity administered must be carefully adjusted to the patient's size. In CT, scanning parameters (scanning length, tube current, tube voltage, filtration, collimation, slice thickness, pitch, automatic dose modulation method, reconstruction technique, and image processing) must be chosen carefully, remembering that normally the scanned images are used only for the purposes of attenuation correction and/or a more precise localization of scintigraphic findings, which require lower quality and consequently entail a lower dose to the patient. On the other hand, good quality diagnostic CT images, obtained at higher dose levels, are necessary if a diagnostic CT examination must still be planned for the patient. The purpose of this review on SPECT/CT radiation dosimetry is to provide updated information on the total effective dose and total equivalent doses to critical organs due to both radiopharmaceutical administration and CT scan modality for both adults and pediatric patients. The use of new solid-state detectors (cadmium zinc telluride) for SPECT cameras will also be considered. Finally, the means of easily determining SPECT/CT dose to patients will be provided.

Recent technological advances in the field of artificial intelligence hold promise in addressing medical challenges in breast cancer care, such as early diagnosis, cancer subtype determination and molecular profiling, prediction of lymph node metastases, and prognostication of treatment response and probability of recurrence. Radiomics is a quantitative approach to medical imaging, which aims to enhance the existing data available to clinicians by means of advanced mathematical analysis using artificial intelligence. Various published studies from different fields in imaging have highlighted the potential of radiomics to enhance clinical decision making. In this review, we describe the evolution of AI in breast imaging and its frontiers, focusing on handcrafted and deep learning radiomics. We present a typical workflow of a radiomics analysis and a practical “how-to” guide. Finally, we summarize the methodology and implementation of radiomics in breast cancer, based on the most recent scientific literature to help researchers and clinicians gain fundamental knowledge of this emerging technology. Alongside this, we discuss the current limitations of radiomics and challenges of integration into clinical practice with conceptual consistency, data curation, technical reproducibility, adequate accuracy, and clinical translation. The incorporation of radiomics with clinical, histopathological, and genomic information will enable physicians to move forward to a higher level of personalized management of patients with breast cancer.

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