Improving the quality of patient care in lung cancer: key factors for successful multidisciplinary team working.

International Guidelines as well as Cancer Associations recommend a multidisciplinary approach to lung cancer care. A multidisciplinary team (MDT) can significantly improve treatment decision-making and patient coordination by putting different physicians and other health professionals "in the same room", who collectively decide upon the best possible treatment. However, this is not a panacea for cancer treatment. The impact of multidisciplinary care (MDC) on patient outcomes is not univocal, while the effective functioning of the MDT depends on many factors. This review presents the available MDT literature with an emphasis on the key factors that characterize high-quality patient care in lung cancer. The study was conducted with a bibliographic search using different electronic databases (PubMed Central, Scopus, Google Scholar, and Google) referring to multidisciplinary cancer care settings. Many key elements appear consolidated, while others emerge as prevalent and actual, especially those related to visible barriers which work across geographic, organizational, and disciplinary boundaries. MDTs must be sustained by strategic management, structured within the entity, and cannot be managed as a separate care process. Furthermore, they need to coordinate with other teams (within and outside the organization) and join with the broad range of services delivered by multiple providers at various points of the cancer journey or within the system, with the vision of integrated care.

Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome.

OBJECTIVE: The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome. METHODS: A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer. RESULTS: The best accuracy for discriminating HER2 + versus HER2 - breast cancers was obtained considering nine predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 88% on validation set). The best accuracy for discriminating HR + versus HR - breast cancers was obtained considering nine predictors by T2-weighted subtraction images and a decision tree (accuracy of 90% on validation set). The best accuracy for discriminating G1 + G2 versus G3 breast cancers was obtained considering 16 predictors by early phase T1-weighted subtraction images in a linear regression model with an accuracy of 75%. The best accuracy for discriminating luminal versus non-luminal breast cancers was obtained considering 27 predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 94% on validation set). CONCLUSIONS: The combination of radiomics analysis and artificial intelligence techniques could be used to support physician decision-making in prediction of Breast Cancer Histological Outcome.

Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography.

PURPOSE: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. METHODS: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually segmenting the region of interest from both craniocaudally (CC) and mediolateral oblique (MLO) views. Non-parametric Wilcoxon-Mann-Whitney test, receiver operating characteristic, logistic regression and tree-based machine learning algorithms were used. The Adaptive Synthetic Sampling balancing approach was used and a feature selection process was implemented. RESULTS: In univariate analysis, the classification of malignant versus benign lesions achieved the best performance when considering the original_gldm_DependenceNonUniformity feature extracted on CC view (accuracy of 88.98%). An accuracy of 83.65% was reached in the classification of grading, whereas a slightly lower value of accuracy (81.65%) was found in the classification of the presence of the hormone receptor; the features extracted were the original_glrlm_RunEntropy and the original_gldm_DependenceNonUniformity, respectively. The results of multivariate analysis achieved the best performances when using two or more features as predictors for classifying malignant versus benign lesions from CC view images (max test accuracy of 95.83% with a non-regularized logistic regression). Considering the features extracted from MLO view images, the best test accuracy (91.67%) was obtained when predicting the grading using a classification-tree algorithm. Combinations of only two features, extracted from both CC and MLO views, always showed test accuracy values greater than or equal to 90.00%, with the only exception being the prediction of the human epidermal growth factor receptor 2, where the best performance (test accuracy of 89.29%) was obtained with the random forest algorithm. CONCLUSIONS: The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images.

Abbreviated breast dynamic contrast-enhanced MR imaging for lesion detection and characterization: the experience of an Italian oncologic center.

BACKGROUND: To evaluate the performance of an abbreviated dynamic contrast-enhanced MR imaging (MRI) protocol for breast cancer detection; a comparison with the complete diagnostic protocol has been conducted. METHODS: A retrospective analysis on 508 patients was performed. Abbreviated protocol (AP) included one pre-contrast and the first post-contrast T1-weighted series. Complete protocol (CP) consisted of four post-contrast and one pre-contrast T1-weighted series. Diagnostic performance was assessed for AP and CP. Performance comparison was made using McNemar's test for sensitivity and specificity and Moskowitz and Pepe's method as regards negative predictive value (NPV) and positive predictive value (PPV). AP has been realized in two different ways (AP1 and AP2) and they were compared by means of Cohen's κ. RESULTS: Both CP and AP revealed 206 of 207 cancers. There were no statistically significant differences between AP and CP diagnostic performance (P > 0.05). NPVs of CP and both versions of AP (99.57 vs. 99.56%, P = 0.39), as well as the specificity (77.08 vs. 75.42%, P = 0.18), were substantially equivalent. Relative predictive value method did not reveal the presence of a statistically significant difference between the PPV of CP and both versions of AP (74.91 vs. 73.57%, P = 0.099). Analysis for single lesion confirmed that both CP and AP had equivalent results: CP and AP revealed 280 of 281 malignancies. NPVs of CP and both AP versions, as well as the specificity (P > 0.05), were substantially equivalent. Relative predictive value method did not reveal the presence of a significant difference between the PPV of CP and both AP versions (70.89 vs. 70.18%, P = 0.25; 70.89 vs. 70.00%, P = 0.13). CONCLUSIONS: Abbreviated approach to breast MRI examination reduces the image acquisition and the reading time associated with MR substantially without influencing the diagnostic accuracy (high sensitivity and NPV >99.5%). AP could translate into cost-savings and could enable a higher number of examinations within the same MR session.

Surgical impact of preoperative breast MRI in women below 40 years of age.

Our aim was to evaluate the surgical impact of preoperative MRI in young patients. We reviewed a single-institution database of 283 consecutive patients below 40 years of age and who were treated for breast cancer. Thirty-seven (13 %) patients who received neoadjuvant chemotherapy were excluded. The remaining 246 patients included 124 (50 %) who preoperatively underwent conventional imaging (CI), i.e., mammography/ultrasonography (CI-group), and 122 (50 %) who underwent CI and dynamic MRI (CI + MRI-group). Pathology of surgical specimens served as a reference standard. Mann-Whitney, χ (2), and McNemar statistics were used. There were no significant differences between groups in terms of age, tumor pathologic subtype, stage, receptor, or nodal status. The mastectomy rate was 111/246 (45 %) overall but was significantly different between groups (46/124, 37 %, for the CI group and 65/122, 53 %, for the CI + MRI group; p = 0.011). Of 122 CI + MRI patients, 46 (38 %) would have undergone mastectomy due to CI alone, while MRI determined 19 additional mastectomies, increasing the mastectomy rate from 38 % to 53 % (p < 0.001). The number of patients with multifocal, multicentric, synchronous, or bilateral cancers was significantly different between groups (10/124, 8 %, for the CI group and 33/122, 27 %, for the CI + MRI group; p < 0.001). In the CI + MRI group, multifocal, multicentric, or synchronous bilateral cancers were detected with mammography in 5/33 (15 %) patients, with ultrasonography in 15/33 (45 %) patients, and with MRI in 32/33 (97 %) patients (p < 0.005). Two mastectomies were due to false positives at both conventional tests in the CI group (2/124, 1.6 %) and two mastectomies were due to MRI false positives in the CI + MRI group (2/122, 1.6 %). In conclusion, breast cancer in young patients was treated with mastectomy in 37-38 % of cases on the basis of CI only and in these patients MRI was more sensitive than CI for multifocal, multicentric, or synchronous bilateral cancers, resulting in an additional mastectomy rate of 15 %. A low probability of inappropriate imaging-based decision-making for mastectomy exists for both CI alone and for CI + MRI, making presurgical needle biopsy mandatory for findings that suggest a need for mastectomy.

Preliminary study on the correlation between grading and histology of solitary pulmonary nodules and contrast enhancement and [18F]fluorodeoxyglucose standardised uptake value after evaluation by dynamic multiphase CT and PET/CT.

AIM: To evaluate whether the histology and grading of solitary pulmonary nodules (SPNs) correlated with the results of dynamic multiphase multidetector CT (MDCT) and the [(18)F]fluorodeoxyglucose standardised uptake value (SUV) in 30 patients. METHODS: Chest x-rays of 270 patients with incidentally detected SPNs were retrospectively evaluated. Thirty patients with histologically proven SPNs were enrolled. On MDCT and positron emission tomography (PET)/CT images, two experts measured the density of nodules in all perfusion phases and the SUV. Net enhancement (NE) was calculated by subtracting peak pre-contrast density from peak post-contrast density. The Pearson test was used to correlate nodule NE, SUV, grading, histology and diameter. RESULTS: Of the 30 malignant SPNs, six were classified as G1 (median NE, 31.5 Hounsfield units (HU); median SUV, 4.8 units), 15 were classified as G2 (median NE, 49 HU; median SUV, 6 units), and nine were classified as G3 (median NE, 32 HU; median SUV, 4.5 units). A highly negative correlation was found in G3 SPNs between NE and the corresponding diameters (r=-0.834; p=0.00524). NE increased with the increase in diameter (r=0.982; p=0.284). SUV increased as the SPN diameter increased (r=0.789; p=0.421). NE and SUV were higher in G2 than G1 SPNs, and lower in G2 than G3 SPNs (r=0.97; p=0.137). CONCLUSIONS: The significant correlation in dedifferentiated (G3) SPNs between NE and diameter (r=-0.834; p=0.00524) supports the theory that stroma and neoangiogenesis are fundamental in SPN growth. The highly negative correlation between NE and diameter demonstrates a net decrease in perfusion despite an increase in dimension. The multidisciplinary approach used herein may result in a more precise prognosis and consequently a better therapeutic outcome, particularly in patients with undifferentiated lung cancer.

Ogilvie's syndrome (acute colonic pseudo-obstruction): review of the literature and report of 6 additional cases.

PURPOSE: Ogilvie's syndrome is defined as an acute pseudo-obstruction of the colon, characterized by the signs, symptoms and radiological pattern of a large-bowel obstruction, but without a detectable organic cause. The aetiology of Ogilvie's syndrome appears to be multifactorial, with a series of possibly interacting pathogenic noxae all resulting in colon inactivity. Our study reports on six cases of Ogilvie's syndrome diagnosed and treated between 1997 and 2002. MATERIALS AND METHODS: From October 1997 to September 2002 we studied six patients affected by pseudo-obstruction of the colon. The pseudo-obstruction was recurrent in two cases. Acute dilatation of the colon without radiologically-detectable organic obstruction was the inclusion criterion for the study. RESULTS: Plain abdominal radiography revealed colon dilatation that extended to the splenic flexure in three patients, to the hepatic flexure in two patients, and confined to the transverse colon in one patient. None of the patients showed air-fluid levels of the small intestine. CONCLUSIONS: The most relevant clinical finding in Ogilvie's syndrome is abdominal distension, which arises suddenly, has a progressive course and reaches massive levels. The first-line diagnostic investigation is plain abdominal radiography which shows extreme colon dilation without air-fluid levels of the small intestine. In three of our patients, conservative therapy alone was able to restore normal conditions within five days; two patients required decompressive colonoscopy, and one patient died from cardio-circulatory arrest after 48 hours.