Breast Digital Tomosynthesis versus Contrast-Enhanced Mammography: Comparison of Diagnostic Application and Radiation Dose in a Screening Setting.

This study aims to evaluate the Average Glandular Dose (AGD) and diagnostic performance of CEM versus Digital Mammography (DM) as well as versus DM plus one-view Digital Breast Tomosynthesis (DBT), which were performed in the same patients at short intervals of time. A preventive screening examination in high-risk asymptomatic patients between 2020 and 2022 was performed with two-view Digital Mammography (DM) projections (Cranio Caudal and Medio Lateral) plus one Digital Breast Tomosynthesis (DBT) projection (mediolateral oblique, MLO) in a single session examination. For all patients in whom we found a suspicious lesion by using DM + DBT, we performed (within two weeks) a CEM examination. AGD and compression force were compared between the diagnostic methods. All lesions identified by DM + DBT were biopsied; then, we assessed whether lesions found by DBT were also highlighted by DM alone and/or by CEM. We enrolled 49 patients with 49 lesions in the study. The median AGD was lower for DM alone than for CEM (3.41 mGy vs. 4.24 mGy, p = 0.015). The AGD for CEM was significantly lower than for the DM plus one single projection DBT protocol (4.24 mGy vs. 5.55 mGy, p < 0.001). We did not find a statistically significant difference in the median compression force between the CEM and DM + DBT. DM + DBT allows the identification of one more invasive neoplasm one in situ lesion and two high-risk lesions, compared to DM alone. The CEM, compared to DM + DBT, failed to identify only one of the high-risk lesions. According to these results, CEM could be used in the screening of asymptomatic high-risk patients.

How Radiomics Can Improve Breast Cancer Diagnosis and Treatment.

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.

Prediction of the Malignancy of a Breast Lesion Detected on Breast Ultrasound: Radiomics Applied to Clinical Practice.

The study aimed to evaluate the performance of radiomics features and one ultrasound CAD (computer-aided diagnosis) in the prediction of the malignancy of a breast lesion detected with ultrasound and to develop a nomogram incorporating radiomic score and available information on CAD performance, conventional Breast Imaging Reporting and Data System evaluation (BI-RADS), and clinical information. Data on 365 breast lesions referred for breast US with subsequent histologic analysis between January 2020 and March 2022 were retrospectively collected. Patients were randomly divided into a training group (n = 255) and a validation test group (n = 110). A radiomics score was generated from the US image. The CAD was performed in a subgroup of 209 cases. The radiomics score included seven radiomics features selected with the LASSO logistic regression model. The multivariable logistic model incorporating CAD performance, BI-RADS evaluation, clinical information, and radiomic score as covariates showed promising results in the prediction of the malignancy of breast lesions: Area under the receiver operating characteristic curve, [AUC]: 0.914; 95% Confidence Interval, [CI]: 0.876-0.951. A nomogram was developed based on these results for possible future applications in clinical practice.

Radiomic Features Applied to Contrast Enhancement Spectral Mammography: Possibility to Predict Breast Cancer Molecular Subtypes in a Non-Invasive Manner.

We aimed to investigate the association between the radiomic features of contrast-enhanced spectral mammography (CESM) images and a specific receptor pattern of breast neoplasms. In this single-center retrospective study, we selected patients with neoplastic breast lesions who underwent CESM before a biopsy and surgical assessment between January 2013 and February 2022. Radiomic analysis was performed on regions of interest selected from recombined CESM images. The association between the features and each evaluated endpoint (ER, PR, Ki-67, HER2+, triple negative, G2-G3 expressions) was investigated through univariate logistic regression. Among the significant and highly correlated radiomic features, we selected only the one most associated with the endpoint. From a group of 321 patients, we enrolled 205 malignant breast lesions. The median age at the exam was 50 years (interquartile range (IQR) 45-58). NGLDM_Contrast was the only feature that was positively associated with both ER and PR expression (p-values = 0.01). NGLDM_Coarseness was negatively associated with Ki-67 expression (p-value = 0.02). Five features SHAPE Volume(mL), SHAPE_Volume(vx), GLRLM_RLNU, NGLDM_Busyness and GLZLM_GLNU were all positively and significantly associated with HER2+; however, all of them were highly correlated. Radiomic features of CESM images could be helpful to predict particular molecular subtypes before a biopsy.

Application of nnU-Net for Automatic Segmentation of Lung Lesions on CT Images and Its Implication for Radiomic Models.

Radiomics investigates the predictive role of quantitative parameters calculated from radiological images. In oncology, tumour segmentation constitutes a crucial step of the radiomic workflow. Manual segmentation is time-consuming and prone to inter-observer variability. In this study, a state-of-the-art deep-learning network for automatic segmentation (nnU-Net) was applied to computed tomography images of lung tumour patients, and its impact on the performance of survival radiomic models was assessed. In total, 899 patients were included, from two proprietary and one public datasets. Different network architectures (2D, 3D) were trained and tested on different combinations of the datasets. Automatic segmentations were compared to reference manual segmentations performed by physicians using the DICE similarity coefficient. Subsequently, the accuracy of radiomic models for survival classification based on either manual or automatic segmentations were compared, considering both hand-crafted and deep-learning features. The best agreement between automatic and manual contours (DICE = 0.78 ± 0.12) was achieved averaging 2D and 3D predictions and applying customised post-processing. The accuracy of the survival classifier (ranging between 0.65 and 0.78) was not statistically different when using manual versus automatic contours, both with hand-crafted and deep features. These results support the promising role nnU-Net can play in automatic segmentation, accelerating the radiomic workflow without impairing the models' accuracy. Further investigations on different clinical endpoints and populations are encouraged to confirm and generalise these findings.

HeLLePhant: A phantom mimicking non-small cell lung cancer for texture analysis in CT images.

PURPOSE: Phantoms mimicking human tissue heterogeneity and intensity are required to establish radiomic features robustness in Computed Tomography (CT) images. We developed inserts with two different techniques for the radiomic study of Non-Small Cell Lung Cancer (NSCLC) lesions. METHODS: We developed two insert prototypes: two 3D-printed made of glycol-modified polyethylene terephthalate (PET-G), and nine with sodium polyacrylate plus iodinated contrast medium. The inserts were put in a handcraft phantom (HeLLePhant). We also analysed four materials of a commercial homogeneous phantom (Catphan® 424) and collected 29 NSCLC patients for comparison. All the CT acquisitions were performed with the same clinical protocol and scanner at 120kVp. The HeLLePhant phantom was scanned ten times in fixed condition at 120kVp and 100kVp for repeatability investigation. We extracted 153 radiomic features using Pyradiomics. To compare the features between phantoms and patients, we computed how many phantom features fell in the range between 10th and 90th percentile of the corresponding patient values. We deemed repeatable the features with a coefficient of variation (CV) less than or equal to 0.10. RESULTS: The best similarity with the patients was obtained with the polyacrylate inserts (55.6-90.2%), the worst with Catphan (15.7-19.0%). For the PET-G inserts 35.3% and 36.6% of the features match the patient range. We found high repeatability for all the inserts of the HeLLePhant phantom (74.3-100% at 120kVp, 75.7-97.9% at 100kVp), and observed a texture dependency in repeatability. CONCLUSIONS: Our study shows a promising way to construct heterogeneous inserts mimicking a target tissue for radiomic studies.

Influence of different urinary bladder filling levels and controlling regions of interest selection on deformable image registration algorithms.

PURPOSE: Evaluation of Raystation ANAtomically CONstrained Deformation Algorithm (ANACONDA) performance to different urinary bladder filling levels in male pelvis anatomic site varying the controlling Regions Of Interest (ROIs). METHODS: Different image datasets were obtained with ImSimQA (Oncology System Limited, Shrewsbury, UK) to evaluate ANACONDA performances (RaySearch Laboratories, Stockholm, Sweden). Deformation vector fields were applied to a synthetic man pelvis and a real patient computed tomography (CT) dataset (reference CTs) resulting in deformed CTs (target CTs) with various bladder filling levels. Different deformable image registrations (DIRs) were generated between each target CTs and reference CTs varying the controlling ROIs subset. Deformed ROIs were mapped from target CT to reference CT and then compared to reference ROIs. Evaluation was performed by Dice Similarity Coefficient (DSC), Correlation Coefficient (CC), Mean Distance to Agreement (MDA), maximum Distance to Agreement (maxDA) and with the introduction of global DSC (global_DSC) and global CC (global_CC) parameters. RESULTS: In both synthetic and real patient CT cases, DSC scored less than 0.75 and MDA greater than 3 mm when no ROIs or only bladder were exploited as controlling ROI. DSC and CC increased by increasing the number of controlling ROIs selected whereas, an opposite behavior was observed for MDA and maxDA. CONCLUSIONS: ANACONDA performances can be influenced by bladder filling fluctuation if no controlling ROIs are selected. Global_DSC and global_CC are useful parameters to quantitatively compare DIR algorithms. DIR performances improve by increasing the number of controlling ROIs selected, reaching a saturation level after a defined ROIs subset selection.

Cone-beam CT-based inter-fraction localization errors for tumors in the pelvic region.

PURPOSE: To evaluate inter-fraction tumor localization errors (TE) in the RapidArc® treatment of pelvic cancers based on CBCT. Appropriate CTV-to PTV margins in a non-IGRT scenario have been proposed. METHODS: Data of 928 patients with prostate, gynecological, and rectum/anal canal cancers were retrospectively analyzed to determine systematic and random localization errors. Two protocols were used: daily online IGRT (d-IGRT) and weekly IGRT. The latter consisted in acquiring a CBCT for the first 3 fractions and subsequently once a week. TE for patients who underwent d-IGRT protocol were calculated using either all CBCTs or the first 3. RESULTS: The systematic (and random) TE in the AP, LL, and SI direction were: for prostate bed 2.7(3.2), 2.3(2.8) and 1.9(2.2) mm; for prostate 4.2(3.1), 2.9(2.8) and 2.3(2.2) mm; for gynecological 3.0(3.6), 2.4(2.7) and 2.3(2.5) mm; for rectum 2.8(2.8), 2.4(2.8) and 2.3(2.5) mm; for anal canal 3.1(3.3), 2.1(2.5) and 2.2(2.7) mm. CTV-to-PTV margins determined from all CBCTs were 14 mm in the AP, 10 mm in the LL and 9-9.5 mm in the SI directions for the prostate and the gynecological groups and 9.5-10.5 mm in AP, 9 mm in LL and 8-10 mm in the SI direction for the prostate bed and the rectum/anal canal groups. If assessed on the basis of the first 3 CBCTs, the calculated CTV-to-PTV margins were slightly larger. CONCLUSIONS: without IGRT, large CTV-to-PTV margins up to 15 mm are required to account for inter-fraction tumor localization errors. Daily IGRT should be used for all hypo-fractionated treatments to reduce margins and avoid increased toxicity to critical organs.

Metastatic and non-metastatic lymph nodes: quantification and different distribution of iodine uptake assessed by dual-energy CT.

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.

High-Risk Prostate Cancer and Radiotherapy: The Past and the Future. A Benchmark for a New Mixed Beam Radiotherapy Approach.

BACKGROUND: The prognosis for patients with high-risk prostate cancer is poor. No consensus exists on the most effective treatment. The aim of this retrospective study was to identify the biochemical progression-free survival and the toxicity profile of patients with localized high-risk prostate cancer treated with external beam radiation therapy. These results will constitute a benchmark for a prospective "mixed beam" trial: a boost with carbon ions followed by a pelvic photon intensity-modulated radiotherapy (NCT02672449 [clinicaltrials.gov]). PATIENTS AND METHODS: We retrospectively reviewed the data of 76 patients treated in our institution with photon radiation therapy according to the inclusion criteria of the future "mixed beam" trial: cT3a and/or serum prostate-specific antigen > 20 ng/mL and/or Gleason score of 8 to 10, cN0 cM0. Toxicity, and biochemical and clinical progression-free survival were assessed. RESULTS: Seventy-six patients fulfilled our criteria. The median follow-up was 30.2 months (range, 7.2-61.1). Biochemical progression was observed in 22 patients (28.9%) after a median time of 20.2 months (range, 5-58.1) from the end of radiotherapy. Sixteen patients had clinical progression, in all the cases preceded by biochemical progression. Fifty-seven patients (75%) are alive with no evidence of disease, 13 (17.1%) are alive with clinically evident disease, 6 died (3 of prostate disease 3.9%). CONCLUSION: Our results suggest that a more aggressive treatment is necessary. Local treatment intensification based on the "mixed beam" approach combining carbon ions (with its known radiobiological advantages) and photons might represent a promising strategy in high-risk prostate cancer and it will be investigated with our prospective clinical trial.

Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis.

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.

Labrys portucalensis sp. nov., a fluorobenzene-degrading bacterium isolated from an industrially contaminated sediment in northern Portugal.

A detailed classification of a novel bacterial strain, designated F11(T), capable of degrading fluorobenzene as a sole carbon and energy source, was performed by using a polyphasic approach. This Gram-negative, rod-shaped, non-motile, non-spore-forming, aerobic bacterium was isolated from a sediment sample collected from an industrially contaminated site in northern Portugal. The predominant whole-cell fatty acids were C(19 : 0) cyclo omega8c, C(16 : 0), C(18 : 1)omega7c, C(18 : 0), C(18 : 0) 3-OH and C(16 : 0) 3-OH. The G+C content of the DNA was 62.9 mol% and the major respiratory quinone was ubiquinone 10 (UQ-10). 16S rRNA gene sequence analysis revealed that strain F11(T) was a member of the class Alphaproteobacteria and was phylogenetically related to the genus Labrys, having sequence similarities of 95.6 and 93.1 % to the type strains of Labrys monachus and Labrys methylaminiphilus, respectively. DNA-DNA hybridization experiments revealed levels of relatedness of <70 % between strain F11(T) and the type strains of L. monachus and L. methylaminiphilus (38.6 and 34.1 %, respectively), justifying the classification of strain F11(T) as representing a novel species of the genus Labrys. The name Labrys portucalensis sp. nov. is proposed for this organism. The type strain is F11(T) (=LMG 23412(T)=DSM 17916(T)).

Role of respiration and glutathione in cadmium-induced oxidative stress in Escherichia coli K-12.

Cadmium is a widespread pollutant that has been associated with oxidative stress, but the mechanism behind this effect in prokaryotes is still unclear. In this work, we exposed two glutathione deficient mutants (DeltagshA and DeltagshB) and one respiration deficient mutant (DeltaubiE) to a sublethal concentration of cadmium. The glutathione mutants show a similar increase in reactive oxygen species as the wild type. Experiments performed using the DeltaubiE strain showed that this mutant is more resistant to cadmium ions and that Cd-induced reactive oxygen species levels were not altered. In the light of these facts, we conclude that the interference of cadmium with the respiratory chain is the cause of the oxidative stress induced by this metal and that, contrary to previously proposed models, the reactive oxygen species increase is not due to glutathione depletion, although this peptide is crucial for cadmium detoxification.

Identification, mutagenesis, and transcriptional analysis of the methanesulfonate transport operon of Methylosulfonomonas methylovora.

Recently identified genes located downstream (3') of the msmEF (transport encoding) gene cluster, msmGH, and located 5' of the structural genes for methanesulfonate monooxygenase (MSAMO) are described from Methylosulfonomonas methylovora. Sequence analysis of the derived polypeptide sequences encoded by these genes revealed a high degree of identity to ABC-type transporters. MsmE showed similarity to a putative periplasmic substrate binding protein, MsmF resembled an integral membrane-associated protein, and MsmG was a putative ATP-binding enzyme. MsmH was thought to be the cognate permease component of the sulfonate transport system. The close association of these putative transport genes to the MSAMO structural genes msmABCD suggested a role for these genes in transport of methanesulfonic acid (MSA) into M. methylovora. msmEFGH and msmABCD constituted two operons for the coordinated expression of MSAMO and the MSA transporter systems. Reverse-transcription-PCR analysis of msmABCD and msmEFGH revealed differential expression of these genes during growth on MSA and methanol. The msmEFGH operon was constitutively expressed, whereas MSA induced expression of msmABCD. A mutant defective in msmE had considerably slower growth rates than the wild type, thus supporting the proposed role of MsmE in the transport of MSA into M. methylovora.

Enrichment of microbial cultures able to degrade 1,3-dichloro-2-propanol: a comparison between batch and continuous methods.

Microbial cultures able to degrade xenobiotic compounds are the key element for biological treatment of waste effluents and are obtained from enrichment processes. In this study, two common enrichment methods, suspension batch and immobilized continuous, were compared. The main selection factor was the presence of 1,3-dichloro-2-propanol (1,3-DCP) as the single carbon source. Both methods have successfully enriched microbial consortia able to degrade 1,3-DCP. When tested in batch culture, the degradation rates of 1,3-DCP by the two consortia were different, with the consortia obtained by batch enrichment presenting slightly higher rates. A preliminary morphological and biochemical analysis of the predominant colonial types present in each degrading consortia revealed the presence of different constituting strains. Three bacterial isolates capable of degrading 1,3-DCP as single strains were obtained from the batch enrichments. These strains were classified by 16S rRNA analysis as belonging to the Rhizobiaceae group. Degradation rates of 1,3-DCP were lower when single species were used, reaching 45 mg 1(-1) d(-1), as compared to 74 mg 1(-1) d(-1) of the consortia enriched on the batch method. Mutualistic interactions may explain the better performance of the enriched consortia.