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.
Radiomics
is an emerging translational field of research aiming to extract mineable high-dimensional data from clinical images. The radiomic process can be divided into distinct steps with definable ...inputs and outputs, such as image acquisition and reconstruction, image segmentation, features extraction and qualification, analysis, and model building. Each step needs careful evaluation for the construction of robust and reliable models to be transferred into clinical practice for the purposes of prognosis, non-invasive disease tracking, and evaluation of disease response to treatment. After the definition of
texture
parameters (shape features; first-, second-, and higher-order features), we briefly discuss the origin of the term
radiomics
and the methods for selecting the parameters useful for a radiomic approach, including cluster analysis, principal component analysis, random forest, neural network, linear/logistic regression, and other. Reproducibility and clinical value of parameters should be firstly tested with
internal cross-validation
and then validated on
independent external cohorts
. This article summarises the major issues regarding this multi-step process, focussing in particular on challenges of the extraction of radiomic features from data sets provided by computed tomography, positron emission tomography, and magnetic resonance imaging.
Objectives
To assess the association between CT features and EGFR, ALK, KRAS mutations in non-small cell lung cancer.
Methods
Patients undergoing chest CT and testing for the above gene mutations ...were included. Qualitative evaluation of CTs included: lobe; lesion diameter; shape; margins; ground-glass opacity; density; cavitation; air bronchogram; pleural thickening; intratumoral necrosis; nodules in tumour lobe; nodules in non-tumour lobes; pleural retraction; location; calcifications; emphysema; fibrosis; pleural contact; pleural effusion. Statistical analysis was performed to assess association of features with each gene mutation. ROC curves for gene mutations were drawn; the corresponding area under the curve was calculated.
P
-values <0.05 were considered significant.
Results
Of 285 patients, 60/280 (21.43 %) were positive for EGFR mutation; 31/270 (11.48 %) for ALK rearrangement; 64/240 (26.67 %) for KRAS mutation. EGFR mutation was associated with air bronchogram, pleural retraction, females, non-smokers, small lesion size, and absence of fibrosis. ALK rearrangements were associated with age and pleural effusion. KRAS mutation was associated with round shape, nodules in non-tumour lobes, and smoking.
Conclusions
This study disclosed associations between CT features and alterations of EGFR (air bronchogram, pleural retraction, small lesion size, absence of fibrosis), ALK (pleural effusion) and KRAS (round lesion shape, nodules in non-tumour lobes).
Key Points
•
Air bronchogram
,
pleural retraction
,
small size relate to EGFR mutation in NSCLC
.
•
Pleural effusion and younger age relate to ALK mutation
.
•
Round lesion shape
,
nodules in non
-
tumour lobes relate to KRAS mutation
.
Screening programs have increased the identification of small or indistinct pulmonary lesions that are difficult to localize. We report our experience in their preoperative localization by ...radiotracer and resection.
Patients with pulmonary nodules of subsolid morphology or smaller than 1 cm, deeper 1 cm below the visceral pleura, or both underwent computed tomography (CT)-guided injection of radiotracer technetium 99m macroaggregates in the vicinity of the lesion. During the operation, a handheld gamma probe was used to detect the hot spot where the radioactive tracer was localized, and this area was resected.
From November 2007 to May 2013, 112 patients (58 men; median age 62 years) underwent preoperative radiotracer injection with a successful marking in all patients. Adverse events included 33 (29.4%) pneumothoraces (one requiring chest tube placement), 23 (20.5%) parenchymal hemorrhage suffusions, and 1 (0.9%) allergic reaction to contrast medium. In all cases except two, the gamma probe revealed pulmonary lesions. Overall, 123 pulmonary nodules were localized and resected. The mean distance from the pleura was 12 mm (range, 0 to 39 mm). Pulmonary resection was performed by thoracoscopy in 70 (62.5%) cases, thoracotomy in 36 (32.1%), and conversion of thoracoscopy to thoracotomy in 6 (5.4%). The mean nodule size was 9 mm (range, 3 to 24 mm). Histology showed 14 (11.4%) benign lesions and 109 (88.6%) malignant lesions (85 primary lung cancers and 24 metastases).
Radiotracer localization of pulmonary lesions is a simple and feasible procedure with a high rate of success. Optimal candidates are patients with suspicious-looking nodules detected by screening or incidental CT resulting frm the high rate of nonsolid morphology and small size.
Purpose:
Four‐dimensional magnetic resonance imaging (4DMRI) is an emerging technique in radiotherapy treatment planning for organ motion quantification. In this paper, the authors present a novel ...4DMRI retrospective image‐based sorting method, providing reduced motion artifacts than using a standard monodimensional external respiratory surrogate.
Methods:
Serial interleaved 2D multislice MRI data were acquired from 24 liver cases (6 volunteers + 18 patients) to test the proposed 4DMRI sorting. Image similarity based on mutual information was applied to automatically identify a stable reference phase and sort the image sequence retrospectively, without the use of additional image or surrogate data to describe breathing motion.
Results:
The image‐based 4DMRI provided a smoother liver profile than that obtained from standard resorting based on an external surrogate. Reduced motion artifacts were observed in image‐based 4DMRI datasets with a fitting error of the liver profile measuring 1.2 ± 0.9 mm (median ± interquartile range) vs 2.1 ± 1.7 mm of the standard method.
Conclusions:
The authors present a novel methodology to derive a patient‐specific 4DMRI model to describe organ motion due to breathing, with improved image quality in 4D reconstruction.
This study applied automatic feature detection on cine-magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking ...methods for motion-compensated liver radiation therapy.
In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each feature was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error.
An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57 mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance.
Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.
Objectives
To evaluate quantification of iodine uptake in metastatic and non-metastatic lymph nodes (LNs) by dual-energy CT (DECT) and to assess if the distribution of iodine within LNs at DECT ...correlates with the pathological structure.
Methods
Ninety LNs from 37 patients (23 with lung and 14 with gynaecological malignancies) were retrospectively selected. Information of LNs sent for statistical analysis included Hounsfield units (HU) at different energy levels; decomposition material densities fat–iodine, iodine–fat, iodine–water, water–iodine. Statistical analysis included evaluation of interobserver variability, material decomposition densities and spatial HU distribution within LNs.
Results
Interobserver agreement was excellent. There was a significant difference in iodine–fat and iodine–water decompositions comparing metastatic and non-metastatic LNs (
p
< 0.001); fat–iodine and water–iodine did not show significant differences. HU distribution showed a significant gradient from centre to periphery within non-metastatic LNs that was significant up to 20–30% from the centre, whereas metastatic LNs showed a more homogeneous distribution of HU, with no significant gradient.
Conclusions
DECT demonstrated a lower iodine uptake in metastatic compared to non-metastatic LNs. Moreover, the internal iodine distribution showed an evident gradient of iodine distribution from centre to periphery in non-metastatic LNs, and a more homogeneous distribution within metastatic LNs, which corresponded to the pathological structure.
Key points
• 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.
This study investigates the impact of whole-body MRI (WB-MRI) in addition to CT of chest-abdomen-pelvis (CT-CAP) and 18F-FDG PET/CT (PET/CT) on systemic treatment decisions in standard clinical ...practice for patients with advanced breast cancer (ABC). WB-MRI examinations in ABC patients were extracted from our WB-MRI registry (2009-2017). Patients under systemic treatment who underwent WB-MRI and a control examination (CT-CAP or PET/CT) were included. Data regarding progressive disease (PD) reported either on WB-MRI or on the control examinations were collected. Data regarding eventual change in treatment after the imaging evaluation were collected. It was finally evaluated whether the detection of PD by any of the two modalities had induced a change in treatment. Among 910 WB-MRI examinations in ABC patients, 58 had a paired control examination (16 CT-CAP and 42 PET/CT) and were analysed. In 23/58 paired examinations, additional sites of disease were reported only on WB-MRI and not on the control examination. In 17/28 paired examinations, PD was reported only on WB-MRI and not on the control examination. In 14 out of the 28 pairs of examinations that were followed by a change in treatment, PD had been reported only on WBMRI (14/28; 50%), while stable disease had been reported on the control examination. In conclusion, WB-MRI disclosed PD earlier than the control examination (CT-CAP or PET/CT), and it was responsible alone for 50% of all changes in treatment.
The diagnosis of breast cancer currently relies on radiological and clinical evaluation, confirmed by histopathological examination. However, such approach has some limitations as the suboptimal ...sensitivity, the long turnaround time for recall tests, the invasiveness of the procedure and the risk that some features of target lesions may remain undetected, making re-biopsy a necessity. Recent technological advances in the field of artificial intelligence hold promise in addressing such medical challenges not only in cancer diagnosis, but also in treatment assessment, and monitoring of disease progression. In the perspective of a truly personalised medicine, based on the early diagnosis and individually tailored treatments, two new technologies, namely radiomics and liquid biopsy, are rising as means to obtain information from diagnosis to molecular profiling and response assessment, without the need of a biopsied tissue sample. Radiomics works through the extraction of quantitative peculiar features of cancer from radiological data, while liquid biopsy gets the whole of the malignancy’s biology from something as easy as a blood sample. Both techniques hopefully will identify diagnostic and prognostic information of breast cancer potentially reducing the need for invasive (and often difficult to perform) biopsies and favouring an approach that is as personalised as possible for each patient. Nevertheless, such techniques will not substitute tissue biopsy in the near future, and even in further times they will require the aid of other parameters to be correctly interpreted and acted upon.
Objectives
Radiomic involves testing the associations of a large number of quantitative imaging features with clinical characteristics. Our aim was to extract a radiomic signature from axial ...T2-weighted (T2-W) magnetic resonance imaging (MRI) of the whole prostate able to predict oncological and radiological scores in prostate cancer (PCa).
Methods
This study included 65 patients with localized PCa treated with radiotherapy (RT) between 2014 and 2018. For each patient, the T2-W MRI images were normalized with the histogram intensity scale standardization method. Features were extracted with the IBEX software. The association of each radiomic feature with risk class, T-stage, Gleason score (GS), extracapsular extension (ECE) score, and Prostate Imaging Reporting and Data System (PI-RADS v2) score was assessed by univariate and multivariate analysis.
Results
Forty-nine out of 65 patients were eligible. Among the 1702 features extracted, 3 to 6 features with the highest predictive power were selected for each outcome. This analysis showed that texture features were the most predictive for GS, PI-RADS v2 score, and risk class; intensity features were highly associated with T-stage, ECE score, and risk class, with areas under the receiver operating characteristic curve (ROC AUC) ranging from 0.74 to 0.94.
Conclusions
MRI-based radiomics is a promising tool for prediction of PCa characteristics. Although a significant association was found between the selected features and all the mentioned clinical/radiological scores, further validations on larger cohorts are needed before these findings can be applied in the clinical practice.
Key Points
• A radiomic model was used to classify PCa aggressiveness.
• Radiomic analysis was performed on T2-W magnetic resonance images of the whole prostate gland.
• The most predictive features belong to the texture (57%) and intensity (43%) domains.
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