Luca Basso
@sdn-napoli.it
Research
IRCCS SDN
Scopus Publications
Scopus Publications
Marianna Amboni, Carlo Ricciardi, Sarah Adamo, Emanuele Nicolai, Antonio Volzone, Roberto Erro, Sofia Cuoco, Giuseppe Cesarelli, Luca Basso, Giovanni D'Addio,et al.
Frontiers Media SA
BackgroundClinical markers of cognitive decline in Parkinson's disease (PD) encompass several mental non-motor symptoms such as hallucinations, apathy, anxiety, and depression. Furthermore, freezing of gait (FOG) and specific gait alterations have been associated with cognitive dysfunction in PD. Finally, although low cerebrospinal fluid levels of amyloid-β42 have been found to predict cognitive decline in PD, hitherto PET imaging of amyloid-β (Aβ) failed to consistently demonstrate the association between Aβ plaques deposition and mild cognitive impairment in PD (PD-MCI).AimFinding significant features associated with PD-MCI through a machine learning approach.Patients and methodsPatients were assessed with an extensive clinical and neuropsychological examination. Clinical evaluation included the assessment of mental non-motor symptoms and FOG using the specific items of the MDS-UPDRS I and II. Based on the neuropsychological examination, patients were classified as subjects without and with MCI (noPD-MCI, PD-MCI). All patients were evaluated using a motion analysis system. A subgroup of PD patients also underwent amyloid PET imaging. PD-MCI and noPD-MCI subjects were compared with a univariate statistical analysis on demographic data, clinical features, gait analysis variables, and amyloid PET data. Then, machine learning analysis was performed two times: Model 1 was implemented with age, clinical variables (hallucinations/psychosis, depression, anxiety, apathy, sleep problems, FOG), and gait features, while Model 2, including only the subgroup performing PET, was implemented with PET variables combined with the top five features of the former model.ResultsSeventy-five PD patients were enrolled (33 PD-MCI and 42 noPD-MCI). PD-MCI vs. noPD-MCI resulted in older and showed worse gait patterns, mainly characterized by increased dynamic instability and reduced step length; when comparing amyloid PET data, the two groups did not differ. Regarding the machine learning analyses, evaluation metrics were satisfactory for Model 1 overcoming 80% for accuracy and specificity, whereas they were disappointing for Model 2.ConclusionsThis study demonstrates that machine learning implemented with specific clinical features and gait variables exhibits high accuracy in predicting PD-MCI, whereas amyloid PET imaging is not able to increase prediction. Additionally, our results prompt that a data mining approach on certain gait parameters might represent a reliable surrogate biomarker of PD-MCI.
Valentina Brancato, Giuseppe Della Pepa, Lutgarda Bozzetto, Marilena Vitale, Giovanni Annuzzi, Luca Basso, Carlo Cavaliere, Marco Salvatore, Angela Albarosa Rivellese, and Serena Monti
MDPI AG
Dixon-based methods for the detection of fatty liver have the advantage of being non-invasive, easy to perform and analyze, and to provide a whole-liver coverage during the acquisition. The aim of the study was to assess the feasibility of a whole-liver Dixon-based approach for liver fat quantification in type 2 diabetes (T2D) patients who underwent two different isocaloric dietary treatments: a diet rich in monosaturated fatty acids (MUFA) and a multifactorial diet. Thirty-nine T2D patients were randomly assigned to MUFA diet (n = 21) and multifactorial diet (n = 18). The mean values of the proton density fat fraction (PDFF) over the whole liver and over the ROI corresponding to that chosen for MRS were compared to MRS-PDFF using Spearman’s correlation (ρ). Before–after changes in percentage of liver volume corresponding to MRI-PDFF above thresholds associated with hepatic steatosis (LV%TH, with TH = 5.56%, 7.97% and 8.8%) were considered to assess the proposed approach and compared between diets using Wilcoxon rank-sum test. Statistical significance set at p < 0.05. A strong linear relationship was found between MRS-PDFF and MRI-PDFFs (ρ = 0.85, p < 0.0001). Changes in LV%TH% were significantly higher (p < 0.05) in the multifactorial diet than in MUFA diet (25% vs. 9%, 35% vs. 12%, and 38% vs. 13% decrease, respectively, for TH = 5.56%, 7.97%, and 8.8%) and this was reproducible compared to results obtained using the standard liver fat analysis. A volumetric approach based on Dixon method could be an effective, non-invasive technique that could be used for the quantitative analysis of hepatic steatosis in T2D patients.
Rossana Castaldo, Nunzia Garbino, Carlo Cavaliere, Mariarosaria Incoronato, Luca Basso, Renato Cuocolo, Leonardo Pace, Marco Salvatore, Monica Franzese, and Emanuele Nicolai
MDPI AG
Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman’s correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.
Pasquale Borrelli, Miriam Zacchia, Carlo Cavaliere, Luca Basso, Marco Salvatore, Giovambattista Capasso, and Marco Aiello
Springer Science and Business Media LLC
AbstractKidney structural abnormalities are common features of Bardet-Biedl syndrome (BBS) patients that lead to a progressive decline in renal function. Magnetic resonance diffusion tensor imaging (DTI) provides useful information on renal microstructures but it has not been applied to these patients. This study investigated using DTI to detect renal abnormalities in BBS patients with no overt renal dysfunction. Ten BBS subjects with estimated glomerular filtration rates over 60 ml/min/1.73m2 and 14 individuals matched for age, gender, body mass index and renal function were subjected to high-field DTI. Fractional anisotropy (FA), and mean, radial and axial diffusivity were evaluated from renal cortex and medulla. Moreover, the corticomedullary differentiation of each DTI parameter was compared between groups. Only cortical FA statistically differed between BBS patients and controls (p = 0.033), but all the medullary DTI parameters discriminated between the two groups with lower FA (p < 0.001) and axial diffusivity (p = 0.021) and higher mean diffusivity (p = 0.043) and radial diffusivity (p < 0.001) in BBS patients compared with controls. Corticomedullary differentiation values were significantly reduced in BBS patients. Thus, DTI is a valuable tool for investigating microstructural alterations in renal disorders when kidney functionality is preserved.
Valentina Brancato, Marco Aiello, Luca Basso, Serena Monti, Luigi Palumbo, Giuseppe Di Costanzo, Marco Salvatore, Alfonso Ragozzino, and Carlo Cavaliere
Springer Science and Business Media LLC
AbstractDespite the key-role of the Prostate Imaging and Reporting and Data System (PI-RADS) in the diagnosis and characterization of prostate cancer (PCa), this system remains to be affected by several limitations, primarily associated with the interpretation of equivocal PI-RADS 3 lesions and with the debated role of Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), which is only used to upgrade peripheral PI-RADS category 3 lesions to PI-RADS category 4 if enhancement is focal. We aimed at investigating the usefulness of radiomics for detection of PCa lesions (Gleason Score ≥ 6) in PI-RADS 3 lesions and in peripheral PI-RADS 3 upgraded to PI-RADS 4 lesions (upPI-RADS 4). Multiparametric MRI (mpMRI) data of patients who underwent prostatic mpMRI between April 2013 and September 2018 were retrospectively evaluated. Biopsy results were used as gold standard. PI-RADS 3 and PI-RADS 4 lesions were re-scored according to the PI-RADS v2.1 before and after DCE-MRI evaluation. Radiomic features were extracted from T2-weighted MRI (T2), Apparent diffusion Coefficient (ADC) map and DCE-MRI subtracted images using PyRadiomics. Feature selection was performed using Wilcoxon-ranksum test and Minimum Redundancy Maximum Relevance (mRMR). Predictive models were constructed for PCa detection in PI-RADS 3 and upPI-RADS 4 lesions using at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. 41 PI-RADS 3 and 32 upPI-RADS 4 lesions were analyzed. Among 293 radiomic features, the top selected features derived from T2 and ADC. For PI-RADS 3 stratification, second order model showed higher performances (Area Under the Receiver Operating Characteristic Curve—AUC— = 80%), while for upPI-RADS 4 stratification, first order model showed higher performances respect to superior order models (AUC = 89%). Our results support the significant role of T2 and ADC radiomic features for PCa detection in lesions scored as PI-RADS 3 and upPI-RADS 4. Radiomics models showed high diagnostic efficacy in classify PI-RADS 3 and upPI-RADS 4 lesions, outperforming PI-RADS v2.1 performance.
Dario Baldi, Luca Basso, Gisella Nele, Giovanni Federico, Giuseppe Walter Antonucci, Marco Salvatore, and Carlo Cavaliere
SAGE Publications
Rhinoplasty and surgical reconstruction of cartilaginous structures still remain a great challenge today. This study aims to identify an imaging strategy in order to merge the information from CT scans and magnetic resonance imaging (MRI) acquisitions and build a 3D printed model true to the patient’s anatomy, for better surgical planning. Using MRI, information can be obtained about the cartilage structures of which the nose is composed. Ten rhinoplasty candidate patients underwent both a low-dose protocol CT scan and a specific MRI for characterization of nasal structures. Bone and soft tissue segmentations were performed in CT, while cartilage segmentations were extrapolated from MRI and validated by both an expert radiologist and surgeon. Subsequently, a 3D model was produced in materials and colors reproducing the density of the three main structures (bone, soft tissue, and cartilage), useful for pre-surgical evaluation. This study has highlighted that the optimization of a CT and MR dedicated protocol has allowed to reduce the CT radiation dose up to 60% compared to standard acquisitions with the same machine, and MR acquisition time of about 20%. Patient-tailored 3D models and pre-surgical planning have reduced the mean operative time by 20 minutes.
Roberta Galatola, Ludovica Attanasio, Valeria Romeo, Ciro Mainolfi, Michele Klain, Chiara Simeoli, Roberta Modica, Elia Guadagno, Giovanni Aprea, Luca Basso,et al.
MDPI AG
Pheochromocytomas may show atypical imaging findings leading to diagnostic pitfalls. We correlated the results of magnetic resonance imaging (MRI) with those of radionuclide studies in patients with pheochromocytomas. T2-weighted (-w), T1-w chemical-shift and T1-w dynamic contrast enhanced (DCE) MRI sequences were evaluated to assess tumor structure. 131Iodine metaiodobenzylguanidine (MIBG) scintigraphy, 18fluoro (F) deoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) or FDG PET/MRI were evaluated for direct comparison. Of a total of 80 adrenal lesions in 73 patients, 20 in 18 patients were pheochromocytomas. More than half (55%) of the pheochromocytomas (n = 11) had the typical increased signal intensity on T2-w and T1-w DCE, while the remaining (n = 9) lesions showed atypical findings; of these nine latter atypical lesions, seven (35%) were cystic (two totally, three predominantly and two partially) and two (10%) were hemorrhagic on MRI. In these atypical lesions, MIBG scintigraphy (n = 5), FDG PET/CT (n = 6) or FDG PET/MRI (n = 2) showed inhomogeneous tracer uptake in the residual viable tissue providing tumor characterization; however, one predominantly cystic pheochromocytoma showed false negative MIBG scan. Our preliminary results show that cystic degeneration may be frequent in pheochromocytoma being so marked that only a thin rim of viable cells may residue to disclose the true nature of the tumor. MRI findings together with those of correlative planar/hybrid radionuclide images are helpful to characterize these atypical pheochromocytomas. In particular, tumor accumulation of MIBG and/or FDG is able to classify these lesions as not simple cysts; in detail, the presence of partial MIBG uptake allows the diagnosis of pheochromocytomas, while the presence of partial FDG uptake generically reflects the presence of viable solid tissue of such cystic tumors.
Valeria Romeo, Giuseppe Accardo, Teresa Perillo, Luca Basso, Nunzia Garbino, Emanuele Nicolai, Simone Maurea, and Marco Salvatore
MDPI AG
Neoadjuvant chemotherapy (NAC) is becoming the standard of care for locally advanced breast cancer, aiming to reduce tumor size before surgery. Unfortunately, less than 30% of patients generally achieve a pathological complete response and approximately 5% of patients show disease progression while receiving NAC. Accurate assessment of the response to NAC is crucial for subsequent surgical planning. Furthermore, early prediction of tumor response could avoid patients being overtreated with useless chemotherapy sections, which are not free from side effects and psychological implications. In this review, we first analyze and compare the accuracy of conventional and advanced imaging techniques as well as discuss the application of artificial intelligence tools in the assessment of tumor response after NAC. Thereafter, the role of advanced imaging techniques, such as MRI, nuclear medicine, and new hybrid PET/MRI imaging in the prediction of the response to NAC is described in the second part of the review. Finally, future perspectives in NAC response prediction, represented by AI applications, are discussed.
Leonardo Pace, Emanuele Nicolai, Carlo Cavaliere, Luca Basso, Nunzia Garbino, Giacomo Spinato, and Marco Salvatore
Springer Science and Business Media LLC
Abstract Objective The aim of this study was to evaluate the prognostic value of combined positron emission tomography (PET)/magnetic resonance imaging (MRI) parameters provided by simultaneous 18F-fluorodeoxyglucose (FDG) PET/MRI in patients with locally advanced oropharyngeal and hypopharyngeal squamous cell carcinomas (OHSCC). Methods Forty-five patients with locally advanced OHSCC who underwent simultaneous FDG PET/MRI before (chemo)radiotherapy were retrospectively enrolled. Peak standardized uptake value (SULpeak), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary lesion were obtained on PET data. On MRI scans, primary tumor size, diffusion and perfusion parameters were assessed using pre-contrast and high-resolution post-contrast images. Ratios between metabolic/metabolo-volumetric parameters and ADC were calculated. Comparisons between groups were performed by Student’s t test. Survival analysis was performed by univariate Cox proportional hazard regression analysis. Overall survival curves were obtained by the Kaplan–Meier method and compared with the log-rank test. Survivors were censored at the time of the last clinical control. p < 0.05 was considered statistically significant Results During follow-up (mean 31.4 ± 21 months), there were 15 deaths. Univariate analysis shows that SULpeak and SULpeak/ADCmean were significant predictors of overall survival (OS). At multivariate analysis, only SULpeak remained a significant predictor of OS. Kaplan–Meier survival analyses showed that patients with higher SULpeak had poorer outcome compared to those with lower values (HR: 3.7, p = 0.007). Conclusion Pre-therapy SULpeak of the primary site was predictive of overall survival in patients with oropharyngeal or hypopharyngeal cancer treated with (chemo)radiotherapy.
Francesco Verde, Elena Vigliar, Valeria Romeo, Maria Raffaela Campanino, Antonello Accurso, Luigi Canta, Nunzia Garbino, Luca Basso, Carlo Cavaliere, Emanuele Nicolai,et al.
Springer Science and Business Media LLC
Abstract We report a case of a 55-year-old woman with left breast cosmetic augmentation performed 5 years earlier, showing at ultrasound a left small amount of peri-implant effusion suspicious for an anaplastic large cell lymphoma localization. The final diagnosis was obtained by cytology using a small amount of fluid (6 ml). Subsequently, hybrid 18F-FDG PET/MRI was used for pre-operative staging and follow-up. An appropriate management of BIA-ALCL could be obtained even in cases of a small amount of peri-implant effusion, using a comprehensive approach of clinical and imaging evaluation, including PET/MRI as useful and innovative staging imaging technique.
Roberta Galatola, Valeria Romeo, Chiara Simeoli, Elia Guadagno, Ilaria De Rosa, Luca Basso, Ciro Mainolfi, Michele Klain, Emanuele Nicolai, Annamaria Colao,et al.
AME Publishing Company
Luca Basso, Dario Baldi, Lorenzo Mannelli, Carlo Cavaliere, Marco Salvatore, and Valentina Brancato
SAGE Publications
Background and Purpose: Quantification of hepatic virtual iron content (VIC) by using Multidetector Dual Energy Computed Tomography (DECT) has been recently investigated since this technique could offer a good compromise between accuracy and non-invasiveness for liver iron content quantification. The aim of our study is to investigate differences in VIC at different DECT time points (namely baseline and arterial, venous and tardive phases), identifying the most reliable and also exploring the underlying temporal trend of these values. Materials and Methods: Eleven patients who underwent DECT examination and were characterized by low liver fat content were included in this retrospective study. By using the Syngo.via Frontier–DE IronVNC tool, regions of interest (ROI) were placed on the VIC images at 3 hepatic levels, both in left and right liver lobes, at each DECT time point. Friedman’s test followed by Bonferroni-adjusted Wilcoxon signed-rank test for post-hoc analysis was performed to assess differences between DECT timepoints. Page’s L test was performed to test the temporal trend of VIC across the 4 examined timepoints. Results: For both liver lobes, Friedman’s test followed by Bonferroni-adjusted Wilcoxon signed-rank test revealed that VIC values differed significantly when extracted from ROIs placed at the 4 different timepoints. The Page’s L test for multiple comparison revealed a significant growing trend for VIC, from baseline acquisition to the fourth and last time point post-contrast agent injection. Conclusions: The extraction of hepatic VIC in healthy subjects was found to be significantly influenced by the DECT time point chosen for the extrapolation of the VIC values.
Valentina Brancato, Marco Aiello, Roberta Della Pepa, Luca Basso, Nunzia Garbino, Emanuele Nicolai, Marco Picardi, Marco Salvatore, and Carlo Cavaliere
MDPI AG
The lack of validation and standardization represents the main drawback for a clear role of whole-body diffusion weighted imaging (WB-DWI) for prediction and assessment of treatment response in Hodgkin’s lymphoma (HL). We explored the reliability of an automatic approach based on the WB-DWI technique for prediction and assessment of response to treatment in patients with HL. The study included 20 HL patients, who had whole-body positron emission tomography (PET)/ magnetic resonance Imaging (MRI) performed before, during and after chemotherapy. Using the syngo.via MR Total Tumor Load tool, we automatically extracted values of diffusion volume (DV) and its associated histogram features by WB-DWI images, and evaluated their utility in predicting and assessing interim and end-of-treatment (EOT) response. The Mann–Whitney test followed by receiver operator characteristic (ROC) analysis was performed between features and their inter-time point percentage differences for patients having a complete or partial treatment response, revealing that several WB-DWI associated features allowed for prediction of interim response and both prediction and assessment of EOT response. Our proposed method offers huge advantages in terms of saving time and work, enabling clinicians to draw conclusions relating to HL treatment response in a fully automatic way, and encloses, also, all DWI advantages compared to PET/ computed tomography (CT).
Leonardo Pace, Emanuele Nicolai, Luca Basso, Nunzia Garbino, Andrea Soricelli, and Marco Salvatore
Springer Science and Business Media LLC
Recently brown adipose tissue (BAT) activation has been proposed to have a possible role in breast cancer. The aim of this study was to evaluate BAT activation in patients with breast cancer and its relationship with molecular characteristics of tumor. The study group comprised 79 patients with histologically proven ductal breast carcinoma (51 ± 13 years). Data on distribution, intensity (SUVmax), and total metabolic activity (TMA) of BAT were obtained from [18F] FDG-PET/CT. Clinical and biochemical data were obtained from the database. BAT activation was present in 12 of the 79 patients (15.2 %). Patients with BAT activation were younger and had a lower body mass index (BMI) (p < 0.05 and p < 0.0005, respectively) and showed less frequently metastasis (p < 0.05). No significant differences were found in estrogen receptor (ER), progesterone receptor (PgR), Ki67, grade, and in molecular subtypes. In patients younger than 55 years and with a BMI < 26, no significant differences were observed between patients with and without BAT activation. In the 12 patients with BAT activation, a significant inverse correlation was observed between TMA and BMI (r = − 0.64, p < 0.05). TMA and SUVmax were higher in grade 2 than in grade 3 patients. No significant differences were found in both TMA and SUVmax between patients with and without lymph node metastases. A significant difference in both TMA and SUVmax was observed among different molecular types, with luminal B patients showing higher values. In conclusion, the present study suggests a relation between BAT activation and positive known prognostic factor in breast cancer, such as intermediate tumor grade and luminal B cancer type.
Valeria Romeo, Carlo Cavaliere, Massimo Imbriaco, Francesco Verde, Mario Petretta, Monica Franzese, Arnaldo Stanzione, Renato Cuocolo, Marco Aiello, Luca Basso,et al.
Elsevier BV
PURPOSE
to assess if tumor segmentation analysis performed at different post-contrast time points (TPs) on dynamic images could influence the extraction of dynamic contrast enhanced (DCE)-MRI parameters in locally advanced breast cancer (LABC), and potentially represent a source of variability.
METHOD
forty patients with forty-two LABC lesions were prospectively enrolled and underwent breast DCE-MRI examination at 3 T. On post-processed dynamic images, enhancing tumor lesions were manually segmented at four different TPs: at the first post-contrast dynamic image in which the lesion was appreciable (TP 1) and at 1, 5 and 10 min after contrast-agent administration (TPs 2, 3 and 4, respectively) and corresponding DCE-MRI parameters were extracted. Friedman's test followed by Bonferroni-adjusted Wilcoxon signed rank test for post-hoc analysis was used to compare DCE-MRI parameters. Intra- and inter-observer reliability of DCE-MRI parameters measurements was assessed using the Intraclass Correlation Coefficient (ICC) analysis.
RESULTS
Ktrans, Kep and iAUC were significantly higher when extracted from ROIs placed at TP1 and progressively decreased from TP 2-4. The intra-observer reliability ranged from good to excellent (ICC's: 0.894 to 0.990). The inter-observer reliability varied from moderate to excellent (0.770 to 0.942). The inter-observer reliability was significantly higher for Ktrans and Kep extracted at TPs1 and 2 as compared to TPs 3 and 4.
CONCLUSIONS
A significant variability of DCE-MRI quantitative parameters occurs when tumor segmentation is performed at different TPs. We suggest to performing tumor delineation at an established TP, preferably the earliest, in order to extract reliable and comparable DCE-MRI data.
Serena Monti, Valentina Brancato, Giuseppe Di Costanzo, Luca Basso, Marta Puglia, Alfonso Ragozzino, Marco Salvatore, and Carlo Cavaliere
MDPI AG
Prostate cancer (PCa) is a disease affecting an increasing number of men worldwide. Several efforts have been made to identify imaging biomarkers to non-invasively detect and characterize PCa, with substantial improvements thanks to multiparametric Magnetic Resonance Imaging (mpMRI). In recent years, diffusion kurtosis imaging (DKI) was proposed to be directly related to tissue physiological and pathological characteristic, while the radiomic approach was proven to be a key method to study cancer imaging phenotypes. Our aim was to compare a standard radiomic model for PCa detection, built using T2-weighted (T2W) and Apparent Diffusion Coefficient (ADC), with an advanced one, including DKI and quantitative Dynamic Contrast Enhanced (DCE), while also evaluating differences in prediction performance when using 2D or 3D lesion segmentation. The obtained results in terms of diagnostic accuracy were high for all of the performed comparisons, reaching values up to 0.99 for the area under a receiver operating characteristic curve (AUC), and 0.98 for both sensitivity and specificity. In comparison, the radiomic model based on standard features led to prediction performances higher than those of the advanced model, while greater accuracy was achieved by the model extracted from 3D segmentation. These results provide new insights into active topics of discussion, such as choosing the most convenient acquisition protocol and the most appropriate postprocessing pipeline to accurately detect and characterize PCa.
Valentina Brancato, Giuseppe Di Costanzo, Luca Basso, Liberatore Tramontano, Marta Puglia, Alfonso Ragozzino, and Carlo Cavaliere
MDPI AG
The role of dynamic contrast-enhanced-MRI (DCE-MRI) for Prostate Imaging-Reporting and Data System (PI-RADS) scoring is a controversial topic. In this retrospective study, we aimed to measure the added value of DCE-MRI in combination with T2-weighted (T2W) and diffusion-weighted imaging (DWI) using PI-RADS v2.1, in terms of reproducibility and diagnostic accuracy, for detection of prostate cancer (PCa) and clinically significant PCa (CS-PCa, for Gleason Score ≥ 7). 117 lesions in 111 patients were identified as suspicion by multiparametric MRI (mpMRI) and addressed for biopsy. Three experienced readers independently assessed PI-RADS score, first using biparametric MRI (bpMRI, including DWI and T2W), and then multiparametric MRI (also including DCE). The inter-rater and inter-method agreement (bpMRI- vs. mpMRI-based scores) were assessed by Cohen’s kappa (κ). Receiver operating characteristics (ROC) analysis was performed to evaluate the diagnostic accuracy for PCa and CS-PCa detection among the two scores. Inter-rater agreement was excellent for the three pairs of readers (κ ≥ 0.83), while the inter-method agreement was good (κ ≥ 0.73). Areas under the ROC curve (AUC) showed similar high-values (0.8 ≤ AUC ≤ 0.85). The reproducibility of PI-RADS v2.1 scoring was comparable and high among readers, without relevant differences, depending on the MRI protocol used. The inclusion of DCE did not influence the diagnostic accuracy.
Pasquale Borrelli, Carlo Cavaliere, Luca Basso, Andrea Soricelli, Marco Salvatore, and Marco Aiello
Springer Science and Business Media LLC
Diffusion tensor imaging (DTI) is particularly suitable for kidney studies due to tubules, collector ducts and blood vessels in the medulla that produce spatially restricted diffusion of water molecules, thus reflecting the high grade of anisotropy detectable by DTI. Kidney DTI is still a challenging technique where the off-resonance susceptibility artefacts and subject motion can severely affect the reproducibility of results. The aim of this study is to design a reliable processing pipeline by assessing different image processing approaches in terms of reproducibility and image artefacts correction. The results of four different processing pipelines (eddy: correction of eddy-currents and motion between DTI volume; eddy-s2v: eddy and within DTI volume motion correction; topup: eddy and geometric distortion correction; topup-s2v: topup and within DTI volume motion correction) are compared in terms of reproducibility by test-retest analysis in 14 healthy subjects. Within-subject coefficient of variation (wsCV) and intra-class correlation coefficient (ICC) are measured to assess the reproducibility and Dice similarity index is evaluated for the spatial alignment between DTI and anatomical images. Topup-s2v pipeline provides highest reproducibility (wsCV = 0.053, ICC = 0.814) and best correction of image distortion (Dice = 0.83). This study definitely provides a recipe for data processing, enabling for a clinical suitability of kidney DTI.
Maria Felicia Fiordelisi, Carlo Cavaliere, Luigi Auletta, Luca Basso, and Marco Salvatore
MDPI AG
The translation of results from the preclinical to the clinical setting is often anything other than straightforward. Indeed, ideas and even very intriguing results obtained at all levels of preclinical research, i.e., in vitro, on animal models, or even in clinical trials, often require much effort to validate, and sometimes, even useful data are lost or are demonstrated to be inapplicable in the clinic. In vivo, small-animal, preclinical imaging uses almost the same technologies in terms of hardware and software settings as for human patients, and hence, might result in a more rapid translation. In this perspective, magnetic resonance imaging might be the most translatable technique, since only in rare cases does it require the use of contrast agents, and when not, sequences developed in the lab can be readily applied to patients, thanks to their non-invasiveness. The wide range of sequences can give much useful information on the anatomy and pathophysiology of oncologic lesions in different body districts. This review aims to underline the versatility of this imaging technique and its various approaches, reporting the latest preclinical studies on thyroid, breast, and prostate cancers, both on small laboratory animals and on human patients, according to our previous and ongoing research lines.
M. F. Fiordelisi, L. Auletta, L. Meomartino, L. Basso, G. Fatone, M. Salvatore, M. Mancini, and A. Greco
Hindawi Limited
Precision and personalized medicine is gaining importance in modern clinical medicine, as it aims to improve diagnostic precision and to reduce consequent therapeutic failures. In this regard, prior to use in human trials, animal models can help evaluate novel imaging approaches and therapeutic strategies and can help discover new biomarkers. Breast cancer is the most common malignancy in women worldwide, accounting for 25% of cases of all cancers and is responsible for approximately 500,000 deaths per year. Thus, it is important to identify accurate biomarkers for precise stratification of affected patients and for early detection of responsiveness to the selected therapeutic protocol. This review aims to summarize the latest advancements in preclinical molecular imaging in breast cancer mouse models. Positron emission tomography (PET) imaging remains one of the most common preclinical techniques used to evaluate biomarker expression in vivo, whereas magnetic resonance imaging (MRI), particularly diffusion-weighted (DW) sequences, has been demonstrated as capable of distinguishing responders from nonresponders for both conventional and innovative chemo- and immune-therapies with high sensitivity and in a noninvasive manner. The ability to customize therapies is desirable, as this will enable early detection of diseases and tailoring of treatments to individual patient profiles. Animal models remain irreplaceable in the effort to understand the molecular mechanisms and patterns of oncologic diseases.