Phantom-based analysis of variations in automatic exposure control across three mammography systems: implications for radiation dose and image quality in mammography, DBT, and CEM.

BACKGROUND: Automatic exposure control (AEC) plays a crucial role in mammography by determining the exposure conditions needed to achieve specific image quality based on the absorption characteristics of compressed breasts. This study aimed to characterize the behavior of AEC for digital mammography (DM), digital breast tomosynthesis (DBT), and low-energy (LE) and high-energy (HE) acquisitions used in contrast-enhanced mammography (CEM) for three mammography systems from two manufacturers. METHODS: Using phantoms simulating various breast thicknesses, 363 studies were acquired using all available AEC modes 165 DM, 132 DBT, and 66 LE-CEM and HE-CEM. AEC behaviors were compared across systems and modalities to assess the impact of different technical components and manufacturers' strategies on the resulting mean glandular doses (MGDs) and image quality metrics such as contrast-to-noise ratio (CNR). RESULTS: For all systems and modalities, AEC increased MGD for increasing phantom thicknesses and decreased CNR. The median MGD values (interquartile ranges) were 1.135 mGy (0.772-1.668) for DM, 1.257 mGy (0.971-1.863) for DBT, 1.280 mGy (0.937-1.878) for LE-CEM, and 0.630 mGy (0.397-0.713) for HE-CEM. Medians CNRs were 14.2 (7.8-20.2) for DM, 4.91 (2.58-7.20) for a single projection in DBT, 11.9 (8.0-18.2) for LE-CEM, and 5.2 (3.6-9.2) for HE-CEM. AECs showed high repeatability, with variations lower than 5% for all modes in DM, DBT, and CEM. CONCLUSIONS: The study revealed substantial differences in AEC behavior between systems, modalities, and AEC modes, influenced by technical components and manufacturers' strategies, with potential implications in radiation dose and image quality in clinical settings. RELEVANCE STATEMENT: The study emphasized the central role of automatic exposure control in DM, DBT, and CEM acquisitions and the great variability in dose and image quality among manufacturers and between modalities. Caution is needed when generalizing conclusions about differences across mammography modalities. KEY POINTS: • AEC plays a crucial role in DM, DBT, and CEM. • AEC determines the "optimal" exposure conditions needed to achieve specific image quality. • The study revealed substantial differences in AEC behavior, influenced by differences in technical components and strategies.

The risk-based breast screening (RIBBS) study protocol: a personalized screening model for young women.

The optimal mammography screening strategy for women aged 45-49 years is a matter of debate. We present the RIBBS study protocol, a quasi-experimental, prospective, population-based study comparing a risk- and breast density-stratified screening model (interventional cohort) with annual digital mammography (DM) screening (observational control cohort) in a real-world setting. The interventional cohort consists of 10,269 women aged 45 years enrolled between 2020 and 2021 from two provinces of the Veneto Region (northen Italy). At baseline, participants underwent two-view digital breast tomosynthesis (DBT) and completed the Tyrer-Cuzick risk prediction model. Volumetric breast density (VBD) was calculated from DBT and the lifetime risk (LTR) was estimated by including VBD among the risk factors. Based on VBD and LTR, women were classified into five subgroups with specific screening protocols for subsequent screening rounds: (1) LTR ≤ 17% and nondense breast: biennial DBT; (2) LTR ≤ 17% and dense breast: biennial DBT and ultrasound; (3) LTR 17-30% or LTR > 30% without family history of BC, and nondense breast: annual DBT; (4) LTR 17-30% or > 30% without family history of BC, and dense breast: annual DBT and ultrasound; and (5) LTR > 30% and family history of BC: annual DBT and breast MRI. The interventional cohort is still ongoing. An observational, nonequivalent control cohort of 43,000 women aged 45 years participating in an annual DM screening programme was recruited in three provinces of the neighbouring Emilia-Romagna Region. Cumulative incidence rates of advanced BC at three, five, and ten years between the two cohorts will be compared, adjusting for the incidence difference at baseline.Trial registration This study is registered on Clinicaltrials.gov (NCT05675085).

Using automated software evaluation to improve the performance of breast radiographers in tomosynthesis screening.

OBJECTIVE: To improve breast radiographers' individual performance by using automated software to assess the correctness of breast positioning and compression in tomosynthesis screening. MATERIALS AND METHODS: In this retrospective longitudinal analysis of prospective cohorts, six breast radiographers with varying experience in the field were asked to use automated software to improve their performance in breast compression and positioning. The software tool automatically analyzes craniocaudal (CC) and mediolateral oblique (MLO) views for their positioning quality by scoring them according to PGMI classifications (perfect, good, moderate, inadequate) and checking whether the compression pressure is within the target range. The positioning and compression data from the studies acquired before the start of the project were used as individual baselines, while the data obtained after the training were used to test whether conscious use of the software could help the radiographers improve their performance. The percentage of views rated perfect or good and the percentage of views in target compression were used as overall metrics to assess changes in performance. RESULTS: Following the use of the software, all radiographers significantly increased the percentage of images rated as perfect or good in both CCs and MLOs. Individual improvements ranged from 7 to 14% for CC and 10 to 16% for MLO views. Moreover, most radiographers exhibited improved compression performance in CCs, with improvements up to 16%. CONCLUSION: Active use of a software tool to automatically assess the correctness of breast compression and positioning in breast cancer screening can improve the performance of radiographers. CLINICAL RELEVANCE STATEMENT: This study suggests that the use of a software tool for automatically evaluating correctness of breast compression and positioning in breast cancer screening can improve the performance of radiographers on these metrics, which may ultimately lead to improved screening outcomes. KEY POINTS: • Proper breast positioning and compression are critical in breast cancer screening to ensure accurate diagnosis. • Active use of the software increased the quality of craniocaudal and mediolateral oblique views acquired by all radiographers. • Improved performance of radiographers is expected to improve screening outcomes.

The Multidisciplinary Approach in Stage III Non-Small Cell Lung Cancer over Ten Years: From Radiation Therapy Optimisation to Innovative Systemic Treatments.

Background: About 30% of new non-small cell lung cancer (NSCLC) cases are diagnosed at a locally advanced stage, which includes a highly heterogeneous group of patients with a wide spectrum of treatment options. The management of stage III NSCLC involves a multidisciplinary team, adequate staging, and a careful patient selection for surgery or radiation therapy integrated with systemic treatment. Methods: This is a single-center observational retrospective and prospective study including a consecutive series of stage III NSCLC patients who were referred to the Veneto Institute of Oncology and University Hospital of Padova (Italy) between 2012 and 2021. We described clinico-pathological characteristics, therapeutic pathways, and treatment responses in terms of radiological response in the entire study population and in terms of pathological response in patients who underwent surgery after induction therapy. Furthermore, we analysed survival outcomes in terms of relapse-free survival (RFS) and overall survival (OS). Results: A total of 301 patients were included. The majority of patients received surgical multimodality treatment (n = 223, 74.1%), while the remaining patients (n = 78, 25.9%) underwent definitive CRT followed or not by durvalumab as consolidation therapy. At data cut-off, 188 patients (62.5%) relapsed and the median RFS (mRFS) of the entire population was 18.2 months (95% CI: 15.83−20.57). At the time of analyses 140 patients (46.5%) were alive and the median OS (mOS) was 44.7 months (95% CI: 38.4−51.0). A statistically significant difference both in mRFS (p = 0.002) and in mOS (p < 0.001) was observed according to the therapeutic pathway in the entire population, and selecting patients treated after 2018, a significant difference in mRFS (p = 0.006) and mOS (p < 0.001) was observed according to treatment modality. Furthermore, considering only patients diagnosed with stage IIIB-C (N = 131, 43.5%), there were significant differences both in mRFS (p = 0.047) and in mOS (p = 0.022) as per the treatment algorithm. The mRFS of the unresectable population was 16.3 months (95% CI: 11.48−21.12), with a significant difference among subgroups (p = 0.030) in favour of patients who underwent the PACIFIC-regimen; while the mOS was 46.5 months (95% CI: 26.46−66.65), with a significant difference between two subgroups (p = 0.003) in favour of consolidation immunotherapy. Conclusions: Our work provides insights into the management and the survival outcomes of stage III NSCLC over about 10 years. We found that the choice of radical treatment impacts on outcome, thus suggesting the importance of appropriate staging at diagnosis, patient selection, and of the multidisciplinary approach in the decision-making process. Our results confirmed that the PACIFIC trial and the following introduction of durvalumab as consolidation treatment may be considered as a turning point for several improvements in the diagnostic-therapeutic pathway of stage III NSCLC patients.

Artifact reduction in contrast-enhanced mammography.

OBJECTIVE: To evaluate the effectiveness of a new algorithm developed to reduce artifacts in dual-energy subtraction (DES) contrast-enhanced mammography (CEM) images while preserving contrast enhancement of possible lesions. METHODS: A retrospective multi-reader paired study was performed by using 134 CEM studies obtained from the first 134 women enrolled in a prospective clinical study aiming to compare the clinical performance of CEM to those of breast MRI in screening of women at increased risk of breast cancer. Four experienced readers compared independently the standard (STD) DES images with those obtained by reprocessing the raw images by a new algorithm (NEW), expected to reduce the DES artifact intensity. The intensity of three types of artifacts (breast-in-breast, ripple, and skinfold enhancement) and the intensity of possible contrast uptake were assessed visually and rated using a categorical ordinal scale. Proportions of images rated by the majority of readers as "Absent", "Weak", "Medium", "Strong" in each artifact intensity category were compared between the two algorithms. P-values lower than 0.05 were considered statistically significant. RESULTS: The NEW algorithm succeeded in eliminating 84.5% of breast-in-breast artifacts, 84.2% of ripple artifacts, and 56.9% of skinfold enhancement artifacts versus STD DES images, and reduced the artifact intensity in 12.1%, 13.0%, and 28.8% of the images, respectively. The visibility of lesion contrast uptake was the same with the STD and the NEW algorithms. CONCLUSION: The new dual-energy subtraction algorithm demonstrated to be effective in reducing/eliminating CEM-related artifacts while preserving lesion contrast enhancement.

Radiation Dose of Contrast-Enhanced Mammography: A Two-Center Prospective Comparison.

The radiation dose associated with contrast-enhanced mammography (CEM) has been investigated only by single-center studies. In this retrospective study, we aimed to compare the radiation dose between two centers performing CEM within two prospective studies, using the same type of equipment. The CEM mean glandular dose (MGD) was computed for low energy (LE) and high energy (HE) images and their sum was calculated for each view. MGD and related parameters (entrance dose, breast thickness, compression, and density) were compared between the two centers using the Mann−Whitney test. Finally, per-patient MGD was calculated by pooling the two datasets and determining the contribution of LE and HE images. A total of 348 CEM examinations were analyzed (228 from Center 1 and 120 from Center 2). The median total MGD per view was 2.33 mGy (interquartile range 2.19−2.51 mGy) at Center 1 and 2.46 mGy (interquartile range 2.32−2.70 mGy) at Center 2, with a 0.15 mGy median difference (p < 0.001) equal to 6.2%. LE-images contributed between 64% and 77% to the total patient dose in CEM, with the remaining 23−36% being associated with HE images. The mean radiation dose for a two-view bilateral CEM exam was 4.90 mGy, about 30% higher than for digital mammography.

Quantitative Breast Density in Contrast-Enhanced Mammography.

Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.

Repeat Screening Outcomes with Digital Breast Tomosynthesis Plus Synthetic Mammography for Breast Cancer Detection: Results from the Prospective Verona Pilot Study.

Background Few results are available about subsequent outcomes after screening with digital breast tomosynthesis (DBT). Purpose To compare the diagnostic accuracy of a screening round with DBT plus synthetic mammography (SM) (hereafter, DBT+SM) and the repeat screening round with DBT with SM (hereafter, DBT+SM) or full-field digital mammography (FFDM) with FFDM screening. Materials and Methods This prospective study (Verona Pilot Study, clinical trial identification: 2015/1238) included women screened with DBT+SM between April 2015 and March 2017 and rescreened with DBT+SM or FFDM between April 2017 and March 2019. Screening performance (recall rate, cancer detection rate [CDR], and positive predictive value of recall [PPV1]) was compared with that obtained from 28 680 women screened with FFDM between 2013 and 2014 (control group). Cancer stages were compared between modalities and screening rounds. A χ2 test was used to evaluate differences. P < .05 was indicative of a statistically significant difference. Results Of 34 638 women enrolled, 32 870 (median age, 58 years; age range, 52-71 years) underwent repeat screening-16 198 with DBT+SM and 16 672 with FFDM. The CDR was higher for repeat screening with DBT+SM than for the control group with FFDM (8.1 per 1000 women screened vs 4.5 per 1000 women screened, respectively; P < .01) and was not significantly lower for repeat screening with FFDM (3.5 per 1000 women screened vs 4.5 per 1000 women screened, respectively; P = .11). Compared with the control group, there was no difference in the recall rate at repeat screening with both DBT+SM (3.71% vs 3.40%, respectively; P = .10) and FFDM (3.71% vs 3.69%, P = .92), whereas PPV1 was higher only when repeat screening was performed with DBT+SM (23.8% vs 12.0%, P < .01). At repeat screening, the proportion of cancers stage II or higher was 14.5% (19 of 131 cancers) with DBT+SM and 8.5% (five of 59 cancers) with FFDM, both of which were lower than the proportion in the control group with FFDM (30 of 110 cancers, 27.3%) (P ≤ .01). Conclusion At repeat screening, digital breast tomosynthesis plus synthetic mammography depicted more cancers than full-field digital mammography (FFDM) and found a lower number of stage II cancers compared with FFDM. © RSNA, 2020 See also the editorial by Bae in this issue.

Accuracy of mammography dosimetry in the era of the European Directive 2013/59/Euratom transposition.

PURPOSE: To evaluate the impact of increasing levels of accuracy for mean glandular dose (MGD) evaluation in the era of the European Directive 2013/59/Euratom transposition. METHOD: 4028 women who had a mammography examination by one of five mammography units using different detector technologies were included in this study. 16,006 images were processed by a software algorithm that determines breast glandularity quantitatively and uses this to estimate patient-specific MGD (psMGD). Entrance dose (ED) values and half value layers (HVLs) measured for each mammography system were collected to evaluate the effect of equipment calibration in psMGD calculation. The psMGD values adjusted for system calibration were compared with organ dose (OD) provided by manufacturers as image metadata. RESULTS: Overall median relative difference between calibrated psMGD and organ dose was below 3%, with larger differences for individual systems. The psMGD adjustment for system calibration was particularly useful for one system for which ED had an evident miscalibration issue. The mean difference between psMGD with calibration and organ dose provided by manufacturers was 4.1 %, ranging from -16.3 % to +24.5 %. The proportion of images for which organ dose was more than 10 % 'inaccurate' compared to psMGD was between 11 % and 46 %, depending on the mammography system. CONCLUSION: Patient-specific mean glandular dose, possibly adjusted for system calibration, allows more accurate individual breast dosimetry than what would be performed using organ dose provided by manufacturers. Conversely, definition of diagnostic reference levels could be achieved using either psMGD or organ dose.

Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.

PURPOSE: To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload. METHODS AND MATERIALS: A total of 2652 DM exams (653 cancer) and interpretations by 101 radiologists were gathered from nine previously performed multi-reader multi-case receiver operating characteristic (MRMC ROC) studies. An AI system was used to obtain a score between 1 and 10 for each exam, representing the likelihood of cancer present. Using all AI scores between 1 and 9 as possible thresholds, the exams were divided into groups of low- and high likelihood of cancer present. It was assumed that, under the pre-selection scenario, only the high-likelihood group would be read by radiologists, while all low-likelihood exams would be reported as normal. The area under the reader-averaged ROC curve (AUC) was calculated for the original evaluations and for the pre-selection scenarios and compared using a non-inferiority hypothesis. RESULTS: Setting the low/high-likelihood threshold at an AI score of 5 (high likelihood > 5) results in a trade-off of approximately halving (- 47%) the workload to be read by radiologists while excluding 7% of true-positive exams. Using an AI score of 2 as threshold yields a workload reduction of 17% while only excluding 1% of true-positive exams. Pre-selection did not change the average AUC of radiologists (inferior 95% CI > - 0.05) for any threshold except at the extreme AI score of 9. CONCLUSION: It is possible to automatically pre-select exams using AI to significantly reduce the breast cancer screening reading workload. KEY POINTS: • There is potential to use artificial intelligence to automatically reduce the breast cancer screening reading workload by excluding exams with a low likelihood of cancer. • The exclusion of exams with the lowest likelihood of cancer in screening might not change radiologists' breast cancer detection performance. • When excluding exams with the lowest likelihood of cancer, the decrease in true-positive recalls would be balanced by a simultaneous reduction in false-positive recalls.

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists.

BACKGROUND: Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an AI system to that of radiologists in detecting breast cancer in DM. METHODS: Nine multi-reader, multi-case study datasets previously used for different research purposes in seven countries were collected. Each dataset consisted of DM exams acquired with systems from four different vendors, multiple radiologists' assessments per exam, and ground truth verified by histopathological analysis or follow-up, yielding a total of 2652 exams (653 malignant) and interpretations by 101 radiologists (28 296 independent interpretations). An AI system analyzed these exams yielding a level of suspicion of cancer present between 1 and 10. The detection performance between the radiologists and the AI system was compared using a noninferiority null hypothesis at a margin of 0.05. RESULTS: The performance of the AI system was statistically noninferior to that of the average of the 101 radiologists. The AI system had a 0.840 (95% confidence interval [CI] = 0.820 to 0.860) area under the ROC curve and the average of the radiologists was 0.814 (95% CI = 0.787 to 0.841) (difference 95% CI = -0.003 to 0.055). The AI system had an AUC higher than 61.4% of the radiologists. CONCLUSIONS: The evaluated AI system achieved a cancer detection accuracy comparable to an average breast radiologist in this retrospective setting. Although promising, the performance and impact of such a system in a screening setting needs further investigation.

Quality Controls in Digital Mammography protocol of the EFOMP Mammo Working group.

This article aims to present the protocol on Quality Controls in Digital Mammography published online in 2015 by the European Federation of Organisations for Medical Physics (EFOMP) which was developed by a Task Force under the Mammo Working Group. The main objective of this protocol was to define a minimum set of easily implemented quality control tests on digital mammography systems that can be used to assure the performance of a system within a set and acceptable range. Detailed step-by-step instructions have been provided, limiting as much as possible any misinterpretations or variations by the person performing. It is intended that these tests be implemented as part of the daily routine of medical physicists and system users throughout Europe in a harmonised way so allowing results to be compared. In this paper the main characteristics of the protocol are illustrated, including examples, together with a brief summary of the contents of each chapter. Finally, instructions for the download of the full protocol and of the related software tools are provided.

The "perfect" reader study.

A reader study, i.e. a diagnostic accuracy study aiming to assess clinical performance of one technology versus another, on the basis of image interpretation by a group of human readers, requires an accurate design, with the precise definition of each element concurring to the study itself. In this paper, the main issues to take into consideration when designing reader studies are described, and the characteristics of a number of indices of diagnostic accuracy are summarized. Special care is given to the description of the multiple sources of bias, which should be controlled in order to assure study soundness and allow consistent conclusions. Although a "perfect" reader study does not exist, because bias cannot be completely eliminated, a good study would be designed to minimize the bias effects, and possible unavoidable bias should be described in study reporting and used to provide a correct interpretation of results.

Radiation dose with digital breast tomosynthesis compared to digital mammography: per-view analysis.

OBJECTIVES: To compare radiation dose delivered by digital mammography (FFDM) and breast tomosynthesis (DBT) for a single view. METHODS: 4,780 FFDM and 4,798 DBT images from 1,208 women enrolled in a screening trial were used to ground dose comparison. Raw images were processed by an automatic software to determine volumetric breast density (VBD) and were used together with exposure data to compute the mean glandular dose (MGD) according to Dance's model. DBT and FFDM were compared in terms of operation of the automatic exposure control (AEC) and MGD level. RESULTS: Statistically significant differences were found between FFDM and DBT MGDs for all views (CC: MGDFFDM=1.366 mGy, MGDDBT=1.858 mGy; p<0.0001; MLO: MGDFFDM=1.374 mGy, MGDDBT=1.877 mGy; p<0.0001). Considering the 4,768 paired views, Bland-Altman analysis showed that the average increase of DBT dose compared to FFDM is 38 %, and a range between 0 % and 75 %. CONCLUSIONS: Our findings show a modest increase of radiation dose to the breast by tomosynthesis compared to FFDM. Given the emerging role of DBT, its use in conjunction with synthetic 2D images should not be deterred by concerns regarding radiation burden, and should draw on evidence of potential clinical benefit. KEY POINTS: • Most studies compared tomosynthesis in combination with mammography vs. mammography alone. • There is some concern about the dose increase with tomosynthesis. • Clinical data show a small increase in radiation dose with tomosynthesis. • Synthetic 2D images from tomosynthesis at zero dose reduce potential harm. • The small dose increase should not be a barrier to use of tomosynthesis.

Optimal follow-up intervals in active surveillance of renal masses in patients with von Hippel-Lindau disease.

OBJECTIVES: To estimate an optimal follow-up (FU) interval for von Hippel-Lindau (VHL) patients with renal masses (RMs) by determining tumour growth rates from growth curves. METHODS: Thirty lesions (47.6%) were classified as solid tumours (STs) and 33 (52.4%) as complex cysts (CCs). Variations in lesion volume over time were analyzed. For 53 lesions, we calculated the growth rate during the period when the volume of the lesion changed most rapidly, and called this the fast growth rate (FGR). RESULTS: The STs initially grew fast, followed by a period of slower growth. The CCs varied in volume over time, associated with variable amounts of their fluid component. The FGR correlated better with the latest volume for STs (r = 0.905) than for CCs (r = 0.780). An optimal FU interval between 3 and 12 months was derived by combining the FGR calculated from the curve with the latest volume measured. CONCLUSIONS: Analyzing growth curves and related kinetic parameters for RMs in VHL patients could be useful with a view to optimizing the subsequent FU interval and improving the active surveillance program. KEY POINTS: • Measuring volume changes over time enables tumour growth curves to be charted. • Renal solid tumours increase in volume with a typical sigmoidal curve. • Complex cysts may increase and decrease in volume spontaneously over time. • The fast growth rate of solid tumours correlates with their latest volume. • The fast growth rate can orient the scheduling of subsequent follow-ups.

OECI accreditation at Veneto Institute of Oncology IOV -- IRCCS, general framework and multidisciplinary approach.

The aim of this article is to describe the accreditation process of the Veneto Institute of Oncology (IOV-IRCCS) according to the Organisation of European Cancer Institutes (OECI) model, with particular reference to the standards for the multidisciplinary approach. Through the analysis of the process and the activities of each multidisciplinary team (MDT) and the development, at a regional level, of diagnostic, therapeutic, and care pathways (PDTA), all the necessary steps to meet the OECI standards have been determined. Adjustment is ongoing. We are working on the inclusion of the MDT registration forms in the electronic medical records and on the possibility to extend the OECI model to the MDT not based at IOV, but participated in by IOV professionals. The sarcoma MDT has achieved results demonstrating that the OECI framework has allowed the professionals involved in the multidisciplinary meeting to systematically share the clinical information of the patient, who can benefit from better continuity of care. The model has also provided greater clarity in the management of patients who are enrolled in clinical trials and deviate from Guide Lines (GL)/PDTA. The accreditation process according to the OECI model has added value to the IOV's already well-developed multidisciplinary activities.

Combination of one-view digital breast tomosynthesis with one-view digital mammography versus standard two-view digital mammography: per lesion analysis.

OBJECTIVE: To evaluate the clinical value of combining one-view mammography (cranio-caudal, CC) with the complementary view tomosynthesis (mediolateral-oblique, MLO) in comparison to standard two-view mammography (MX) in terms of both lesion detection and characterization. METHODS: A free-response receiver operating characteristic (FROC) experiment was conducted independently by six breast radiologists, obtaining data from 463 breasts of 250 patients. Differences in mean lesion detection fraction (LDF) and mean lesion characterization fraction (LCF) were analysed by analysis of variance (ANOVA) to compare clinical performance of the combination of techniques to standard two-view digital mammography. RESULTS: The 463 cases (breasts) reviewed included 258 with one to three lesions each, and 205 with no lesions. The 258 cases with lesions included 77 cancers in 68 breasts and 271 benign lesions to give a total of 348 proven lesions. The combination, DBT(MLO)+MX(CC), was superior to MX (CC+MLO) in both lesion detection (LDF) and lesion characterization (LCF) overall and for benign lesions. DBT(MLO)+MX(CC) was non-inferior to two-view MX for malignant lesions. CONCLUSIONS: This study shows that readers' capabilities in detecting and characterizing breast lesions are improved by combining single-view digital breast tomosynthesis and single-view mammography compared to two-view digital mammography. KEY POINTS: • Digital breast tomosynthesis is becoming adopted as an adjunct to mammography (MX) • DBT (MLO) +MX (CC) is superior to MX (CC+MLO) in lesion detection (overall and benign lesions) • DBT (MLO) +MX (CC) is non-inferior to MX (CC+MLO) in cancer detection • DBT (MLO) +MX (CC) is superior to MX (CC+MLO) in lesion characterization (overall and benign lesions) • DBT (MLO) +MX (CC) is non-inferior to MX (CC+MLO) in characterization of malignant lesions.

Performance comparison of single-view digital breast tomosynthesis plus single-view digital mammography with two-view digital mammography.

OBJECTIVE: To determine the performance of combined single-view mediolateral oblique (MLO) digital breast tomosynthesis (DBT) plus single-view cranio-caudal (CC) mammography (MX) compared with that of standard two-view digital mammography. METHODS: A multi-reader multi-case (MRMC) receiver-operating characteristic (ROC) study was conducted, involving six breast radiologists. Two hundred fifty patients underwent bilateral MX and DBT imaging. MX and DBT images with the adjunct of the CC-MX view from 469 breasts were evaluated and rated independently by six readers. Differences in mean areas under the ROC curves (AUCs), mean sensitivity and mean specificity were analysed by analysis of variance (ANOVA) to assess clinical performance. RESULTS: The combined technique was found to be non-inferior to standard two-view mammography (MX((CC+MLO))) in mean AUC (difference: +0.021;95 % LCL = -0.011), but was not statistically significant for superiority (P = 0.197). The combined technique had equivalent sensitivity to standard mammography (76.2 % vs. 72.8 %, P = 0.269) and equivalent specificity (84.9 % vs. 83.0 %, P = 0.130). Specificity for benign lesions was significantly higher with the combination of techniques versus mammography (45.6 % vs. 36.8 %, P = 0.002). CONCLUSION: In this enriched study population, the combination of single-view MLO tomosynthesis plus single-view CC mammography was non-inferior to that of standard two-view digital mammography in terms of ROC curve area, sensitivity and specificity.

Comparison between CT volume measurement and histopathological assessment of response to neoadjuvant therapy in rectal cancer.

OBJECTIVES: The aim of this study was to compare volume measurements on computed tomography (CT) images with histopathological assessments of chemoradiotherapy (CRT)-induced tumor regression in locally advanced rectal cancer (RC). METHODS: In 25 patients (13 males, 12 females; median age, 63 years; age range, 44-79 years) with locally advanced RC treated with preoperative CRT and surgery, two radiologists measured tumor volume on CT images before and after CRT. CT-based tumor volumetry and the modified response evaluation criteria in solid tumors (mRECISTs) were compared with T and N downstaging after CRT, and with the tumor regression grade (TRG). RESULTS: Tumor volumes were significantly smaller on CT images after CRT. The tumors regressed in 52% (13/25), 36% (9/25) and 40% (10/25) of patients, based on T downstaging, TRG and mRECIST findings, respectively. In terms of T downstaging, the pre- and post-CRT tumor volumes of responders and non-responders to the treatment differed statistically, while their tumor volume reduction rates and volume reductions according to the 65% mRECIST threshold did not. In terms of N downstaging and TRG, the differences between the responders' and the non-responders' pre- and post-CRT tumor volumes, tumor volume reduction rates, and mRECIST thresholds were never statistically significant. CONCLUSION: Measuring tumor size on CT images is of limited value in predicting the histopathological response to preoperative CRT in RC patients, so it may be unwise to select surgical treatment strategies based on CT volumetry.