Relationship between Eccentricity and Volume Determined by Spectral Algorithms Applied to Spatially Registered Bi-Parametric MRI and Prostate Tumor Aggressiveness: A Pilot Study

(1) Background: Non-invasive prostate cancer assessments using multi-parametric MRI are essential to the reliable detection of lesions and proper management of patients. While current guidelines call for the administration of Gadolinium-containing intravenous contrast injections, eliminating such injections would simplify scanning and reduce patient risk and costs. However, augmented image analysis is necessary to extract important diagnostic information from MRIs. Purpose: This study aims to extend previous work on the signal to clutter ratio and test whether prostate tumor eccentricity and volume are indicators of tumor aggressiveness using bi-parametric (BP)-MRI. (2) Methods: This study retrospectively processed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRIs (apparent diffusion coefficient, high b-value, and T2 images) were resized, translated, cropped, and stitched to form spatially registered BP-MRIs. The International Society of Urological Pathology (ISUP) grade was used to judge cases of prostate cancer as either clinically significant prostate cancer (CsPCa) (ISUP ≥ 2) or clinically insignificant prostate cancer (CiPCa) (ISUP < 2). The Adaptive Cosine Estimator (ACE) algorithm was applied to the BP-MRIs, followed by thresholding, and then eccentricity and volume computations, from the labeled and blobbed detection maps. Then, univariate and multivariate linear regression fittings of eccentricity and volume were applied to the ISUP grade. The fits were quantitatively evaluated by computing correlation coefficients (R) and p-values. Area under the curve (AUC) and receiver operator characteristic (ROC) curve scores were used to assess the logistic fitting to CsPCa/CiPCa. (3) Results: Modest correlation coefficients (R) (>0.35) and AUC scores (0.70) for the linear and/or logistic fits from the processed prostate tumor eccentricity and volume computations for the spatially registered BP-MRIs exceeded fits using the parameters of prostate serum antigen, prostate volume, and patient age (R~0.17). (4) Conclusions: This is the first study that applied spectral approaches to BP-MRIs to generate tumor eccentricity and volume metrics to assess tumor aggressiveness. This study found significant values of R and AUC (albeit below those from multi-parametric MRI) to fit and relate the metrics to the ISUP grade and CsPCA/CiPCA, respectively.

Association of tumor morphology with long-term prognosis after liver resection for patients with a solitary huge hepatocellular carcinoma-a multicenter propensity score matching analysis

BACKGROUND

A solitary hepatocellular carcinoma (HCC) without macrovascular invasion and distant metastasis, regardless of tumor size, is currently classified as early-stage disease by the latest Barcelona Clinic Liver Cancer (BCLC) staging system. While the preferred treatment is surgical resection, the association of tumor morphology with long-term survival outcomes after liver resection for a solitary huge HCC of ≥10 cm has not been defined.

METHODS

Patients who underwent curative liver resection for a solitary huge HCC were identified from a multicenter database. Preoperative imaging findings were used to define spherical- or ellipsoidal-shaped lesions with smooth edges as balloon-shaped HCCs (BS-HCCs); out-of-shape lesions or lesions of any shape with matt edges were defined as non-balloon-shaped HCCs (NBS-HCCs). The two groups of patients with BS-HCCs and NBS-HCCs were matched in a 1:1 ratio using propensity score matching (PSM). Clinicopathologic characteristics, long-term overall survival (OS) and recurrence-free survival (RFS) were assessed.

RESULTS

Among patients with a solitary huge HCC, 74 pairs of patients with BS-HCC and NBS-HCC were matched. Tumor pathological features including proportions of microvascular invasion, satellite nodules, and incomplete tumor encapsulation in the BS-HCC group were lower than the NBS-HCC group. At a median follow-up of 50.7 months, median OS and RFS of all patients with a solitary huge HCC after PSM were 27.8 and 10.1 months, respectively. The BS-HCC group had better median OS and RFS than the NBS-HCC group (31.9 vs. 21.0 months, P=0.01; and 19.7 vs. 6.4 months, P=0.015). Multivariate analyses identified BS-HCC as independently associated with better OS (HR =0.592, P=0.009) and RFS (HR =0.633, P=0.013).

CONCLUSIONS

For a solitary huge HCC, preoperative imaging on tumor morphology was associated with prognosis following resection. In particular, patients with BS-HCCs had better long-term survival following liver resection versus patients with large NBS-HCCs.

High-resolution diffusion-weighted imaging compared with conventional diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging with regard to image quality and assessment of breast cancer morphology

PURPOSE

To evaluate the image quality and tumor morphology depiction ability of high resolution (HR) diffusion- weighted imaging (f-DWI) in comparison to conventional DWI (c-DWI) and dynamic contrast- enhanced magnetic resonance imaging (DCE-MRI) in the primary breast cancer setting.

METHODS

The f-DWI, c-DWI, and DCE-MRIs of 160 malignant breast masses were evaluated retrospectively by two independent radiologists. Data on image quality [sharpness, distortion, and perceived signalto- noise ratio (SNR)], apparent diffusion coefficient (ADC) value, lesion size, and tumor morphology (shape, margin, and internal pattern) obtained on f-DWI, c-DWI, and DCE-MRI were compared. Consistency between the readers and imaging methods for morphological parameters was analyzed.

RESULTS

The ADC values measured on f-DWI were significantly lower than those measured on c-DWI for both readers (P < 0.001 for each), whereas mean lesion size was significantly larger in c-DWI than in f-DWI and DCE-MRI for both readers (P < 0.001 for each). Higher consistency values were obtained for f-DWI compared with c-DWI when correlated with DCE-MRI for each morphological parameter. The least distorted images were obtained using DCE-MRI compared with c-DWI and f-DWI for both readers, whereas the highest distortion scores were obtained using c-DWI. Sharpness and perceived SNR scores were rated as significantly higher for f-DWI and DCE-MRI images compared with c-DWI by both readers (P < 0.001 for all). The concordance between c-DWI and DCE-MRI was fair to slight (κ = 0.15 to 0.41), whereas concordance between f-DWI and DCE-MRI was significantly better (κ = 0.68 to 0.87) for each reader and for all morphological parameters (P < 0.001). The highest concordance between the readers was achieved in margin assessment (κ = 0.87 to 0.89) regardless of the MRI method, followed by shape and internal pattern parameters (κ = 0.63 to 0.79).

CONCLUSION

The results demonstrated that f-DWI produces higher-quality images than c-DWI, enabling the morphological features to be identified in similar detail to that offered by HR DCE-MRI. Accordingly, f-DWI, as a method that highly correlates with DCE in determining the morphological characteristics of breast cancers, seems to have potential in the evaluation of breast tumors in patients for whom the use of contrast media is contraindicated.

A morphology-based nephrometry score to predict pathological upstaging to T3 renal cell carcinoma

Background

Patients with clinical T1-2 renal cell carcinoma (RCC) upstaging to pathological T3 showed worse survival prognosis than those without upstaging. We aimed to develop and validate a morphology-based nephrometry scoring system for predicting pathological upstaging to T3 of RCC.

Methods

We retrospectively reviewed 200 patients with clinical T1-2 RCC who underwent surgical treatment. The nephrometry scores were measured through preoperative computed tomography images. The risk factors of pathological upstaging were identified by logistic regression models. The predictive accuracy of a novel morphology-based nephrometry scoring system (M-Index), was compared with R.E.N.A.L (radius, exophytic/endophytic, nearness, anterior/posterior, location), PADUA (preoperative aspects and dimensions used for an anatomic classification), DAP (diameter, axial, polar) and C-Index scores.

Results

The upstaging rate of the population was 17% (34 out of 200 patients). The upstaging and non-upstaging groups were comparable in terms of age, gender ratio, body mass index, tumor laterality, and pathological type, while the upstaging group tended to have large tumor diameter, irregular tumor morphology, inner tumor location, and short polar and axial distance. Large tumor diameter refers to larger than 5 cm, while irregular tumor morphology refers to not regular shapes such as round, oval, or lobular. Univariate and multivariate logistic regression analyses showed that tumor morphology [odds ratio (OR) 3.26, 95% confidence interval (CI): 1.79-5.97] and tumor rim location (OR 2.95, 95% CI: 1.16-7.46) were independent risk factors for pathological upstaging. The receiver operating characteristic curve and decision curve analysis (DCA) demonstrated the novel M-Index based on tumor morphology and rim location outperformed R.E.N.A.L, PADUA, DAP, and C-Index in the prediction of pathological upstaging (area under curve 0.756 vs. 0.728 vs. 0.641 vs. 0.661 vs. 0.743).

Conclusions

Consisting of fewer non-complex parameters, the M-Index is an intuitive and practical tool with satisfactory predictive power for pathological upstaging to T3 in RCC patients undergoing surgery.

Deep Learning Approaches in Histopathology

The revolution of artificial intelligence and its impacts on our daily life has led to tremendous interest in the field and its related subtypes: machine learning and deep learning. Scientists and developers have designed machine learning- and deep learning-based algorithms to perform various tasks related to tumor pathologies, such as tumor detection, classification, grading with variant stages, diagnostic forecasting, recognition of pathological attributes, pathogenesis, and genomic mutations. Pathologists are interested in artificial intelligence to improve the diagnosis precision impartiality and to minimize the workload combined with the time consumed, which affects the accuracy of the decision taken. Regrettably, there are already certain obstacles to overcome connected to artificial intelligence deployments, such as the applicability and validation of algorithms and computational technologies, in addition to the ability to train pathologists and doctors to use these machines and their willingness to accept the results. This review paper provides a survey of how machine learning and deep learning methods could be implemented into health care providers' routine tasks and the obstacles and opportunities for artificial intelligence application in tumor morphology.

Association between tumor morphology and dosimetric parameters of organs at risk after intensity-modulated radiotherapy in esophagus cancer

PURPOSE

We explored the effects of geometrical topological properties of tumors such as tumor length and "axial cross-sectional area (ACSA)" of tumors (planning target volume [PTV] volume /PTV length) on the dosimetric parameters of organs at risk (lung and heart) in patients with esophagus cancer (EPC) treated by way of intensity-modulated radiation therapy (IMRT), so as to provide a guideline for the dosimetric limitation for organs at risk in IMRT treatment.

METHODS

A retrospective analysis was done on 103 cases of patients with EPC who were treated by IMRT from November 2010 to August 2019, in which PTV-G stood for the externally expanded planning target volume (PTV) of the gross tumor volume (GTV) and PTV-C for the externally expanded volume of the clinical target volume (CTV). A linear regression model was employed to analyze the several pairs of correlation: the 1st one between the relative length of tumors (PTV length/lung length) and pulmonary dose-volume parameters, the 2nd one between ACSA of tumors and pulmonary dose-volume parameters, the 3rd one between PTV length and the dosimetric parameters of the heart, and the last one between ACSA of tumors and the dosimetric parameters of the heart.

RESULTS

(i) There was a strong positive correlation between the relative length of tumors (PTV length/lung length) and V₅ (p < 0.001, r = 0.73), and V₁₀ (p < 0.001, r = 0.66) of the lung. There was a moderate positive correlation between the relative length of tumors and V₃₀ (p < 0.001, r = 0.44) of the lung, and a weak positive correlation between the relative length of tumors and V₂₀ (p < 0.001, r = 0.39) of the lung. (ii) There was a strong positive correlation between ACSA of tumors (PTV volume/PTV length) and V₃₀ (p < 0.001, r = 0.67) of the lung, a moderate positive correlation between ACSA of tumors and V₂₀ (p <0.001, r = 0.51) of the lung, and a weak positive correlation between ACSA of tumors and V₁₀ (p = 0.019, r = 0.23) of the lung, yet there was not an obvious correlation between ACSA of tumors and V₅ p > 0.05) of the lung. (iii) There was a moderate positive correlation between PTV length and V₄₀ (p < 0.001, r = 0.58), and D_mean (p < 0.001, r = 0.52) of the heart, yet there was no obvious correlation between ACSA of tumors and D_mean and V₄₀ of the heart (p > 0.05).

CONCLUSIONS

(i) Compared with the high-dose region of the lung, the relative length of tumors (PTV length/lung length) has a greater impact on the low-dose region of the lung. The linear regression equation of scatter plot showed that when the relative length of tumors increased by 0.1, the lung dose-volume parameters of V₅ , V₁₀ , V₂₀ , and V₃₀ increased by approximately 5.37%, 3.59%, 1.05%, and 1.08%, respectively. When PTV length increased by 1 cm, D_mean and V₄₀ of the heart increased by approximately 153.6 cGy and 2.03%, respectively. (ii) Compared with the low-dose region of the lung, the value of ACSA of tumors (PTV volume/PTV length) has a greater impact on the high-dose region of the lung. However, the value of ACSA of tumors has no significant effect on the dosimetric parameters of the heart (D_mean and V₄₀ ). The linear regression equation of scatter plot showed that when ACSA of tumors increased by 10 cm² , the lung dose-volume parameters of V₁₀ , V_20, and V₃₀ increased by approximately 3.11%, 3.37%, and 4.01%, respectively.

Usefulness of Tumor Tissue Biopsy for Predicting the Biological Behavior of Hepatocellular Carcinoma

BACKGROUND/AIM

Assessment of the biological behavior of tumors is important for choosing an appropriate cancer therapy. In hepatocellular carcinoma (HCC), the biological behaviour can be assessed by tumor morphology and molecular biology. This study investigated the usefulness of tumor tissue biopsy for predicting the biological behavior of HCC.

PATIENTS AND METHODS

We studied 43 patients who underwent hepatectomy and preoperative liver tumor biopsy for HCC. We performed clinicopathological and immunohistochemical (IHC) analyses. The expression of the following molecules was examined: regulator of G-protein signaling 5 (RGS5), glypican-3 (GPC3), keratin 19 (K19), epithelial cell adhesion molecule (EpCAM), protein induced by vitamin K absence or antagonist-II (PIVKA-II), β-Catenin, and p53.

RESULTS

There was an overall 83.7% agreement regarding tumor differentiation between the preoperative biopsy specimens and the resected specimens. The accuracy of IHC analysis was more than 70% for all molecules between the preoperative biopsy specimens and the resected specimens. The RGS5-positive biopsy cases had higher serum α-fetoprotein levels (p=0.04), a higher rate of moderately or poorly differentiated tumors (p=0.02) and portal vein invasion (p=0.0003) than the RGS5-negative biopsy cases. The GPC3-positive biopsy cases were younger (p=0.04), had higher serum PIVKA-II levels (p=0.01), and a higher rate of portal vein invasion (p=0.03) than the GPC3-negative biopsy cases. The PIVKA-II-positive biopsy cases had significantly higher serum PIVKA-II levels than the PIVKA-II-negative biopsy cases (p=0.02). The other molecular markers showed no significantly different clinical findings between the positive and negative cases.

CONCLUSION

In HCC, there was a high agreement rate of both the histopathological and IHC findings between preoperative biopsy specimens and resected specimens. In the biopsy specimens of HCC, RGS5 and GPC3 expression were useful molecular makers for predicting portal vein invasion. Liver tumor biopsy is useful for predicting the biological behavior of HCC through histopathological and immunohistochemical findings.

Tumor-Infiltrating Lymphocytes/Plasmocytes in Chemotherapeutically Non-Influenced Triple-Negative Breast Cancers - Correlation with Morphological and Clinico-Pathological Parameters

BACKGROUND

Triple-negative breast cancers (TNBCs) are considered a morphologically heterogeneous group of breast carcinomas characterized by the absence or low protein expression of hormone receptors and HER2/neu/ERBB2 with a specific biological behavior and therapeutic response. This study aimed to evaluate correlations of the density of tumor-infiltrating lymphocytes/plasmocytes (TILs) in the tumor parenchyma, stroma, and invasive margins with tumor morphology, the proliferation rate, Bcl-2 expression, and selected clinical and pathological parameters in early breast cancer patients prior to mastectomy who had not received initial chemotherapy.

MATERIALS AND METHODS

Samples of 3,544 breast cancer patients investigated in our department between 2007 and 2017 were re-examined. In total, 413 (11.65%) patients were diagnosed with TNBC. Only 61 cases did not undergo neoadjuvant therapy prior to mastectomy. Correlations between the density of TILs and tumor morphology, Bcl-2 expression, proliferative activity measured by Ki-67, patient age at diagnosis, tumor grade, and metastases were investigated.

RESULTS

The samples were predominantly relatively well-localized invasive carcinomas of no special type with medullary features (80.32%) that measured on average 13.4mm (range 5-20mm, median 15mm) and exhibited central necrosis or fibrosis, a tendency to undergo spindle cell and/or apocrine-like differentiation, and intensive infiltration of TILs. There were significant positive correlations between TILs and premenopausal status (p=0.003), Ki-67 expression (p=0.015), and tumor grade (p=0.002), a marginal positive correlation between TILs and tumor size (p=0.065), and a significant negative correlation between TILs and Bcl-2 expression (p=0.035). In younger patients (&lt; 50 years) with tumor size less than or equal to 20 mm (pT1a-pT1c) we recorded a lower number of women with metastatic lymph node involvement (p=0.001).

CONCLUSION

The density and location of TILs in non-therapeutically influenced TNBCs, evaluated in the context of morphological changes and other clinicopathological parameters, may have prognostic significance and assist effective therapy planning.

Features of incident colorectal cancer in Lynch syndrome

Background and objective

Despite intensive colonoscopic surveillance, a substantial proportion of Lynch syndrome (LS) patients develop colorectal cancer (CRC). The aim of this study was to characterize incident CRC in LS patients.

Methods

All patients diagnosed with incident CRC after start of colonoscopic surveillance were identified in the Dutch LS Registry of 905 patients. A retrospective analysis of patient records was carried out for patient characteristics, survival, CRC characteristics and findings of previous colonoscopy.

Results

Seventy-one patients (7.8%) were diagnosed with incident CRC. Median interval between incident CRC diagnosis and previous colonoscopy was 23.8 (range 6.7-45.6) months. Median tumor diameter was 2.5 cm, and 17% of the tumors were sessile or flat. Most patients (83%) had no lymph node metastases. There was no association between tumor size and colonoscopy interval or lymph node status. Most patients (65%) had no adenomas during previous colonoscopy. Two patients (2.8%) eventually died from metastatic CRC.

Conclusion

The high frequency of incident CRC in LS likely results from several factors. Our findings lend support to the hypothesis of fast conversion of adenomas to CRC, as 65% of patients had no report of polyps during previous colonoscopy. High-quality colonoscopies are essential, especially as tumors and adenomas are difficult to detect because of their frequent non-polypoid appearance. Early detection due to surveillance as well as the indolent growth of CRC, as demonstrated by the lack of lymph node metastases, contributes to the excellent survival observed.

Assessment of tumor morphology on diffusion-weighted (DWI) breast MRI: Diagnostic value of reduced field of view DWI

PURPOSE

To compare the diagnostic value of conventional, bilateral diffusion-weighted imaging (DWI) and high-resolution targeted DWI of known breast lesions.

MATERIALS AND METHODS

Twenty-one consecutive patients with known breast cancer or suspicious breast lesions were scanned with the conventional bilateral DWI technique, a high-resolution, reduced field of view (rFOV) DWI technique, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) (3.0 T). We compared bilateral DWI and rFOV DWI quantitatively by measuring the lesions' apparent diffusion coefficient (ADC) values. For qualitative comparison, three dedicated breast radiologists scored image quality and performed lesion interpretation.

RESULTS

In a phantom, ADC values were in good agreement with the reference values. Twenty-one patients (30 lesions: 14 invasive carcinomas, 10 benign lesions [of which 5 cysts], 3 high-risk, and 3 in situ carcinomas) were included. Cysts and high-risk lesions were excluded from the quantitative analysis. Quantitatively, both bilateral and rFOV DWI measured lower ADC values in invasive tumors than other lesions. In vivo, rFOV DWI gave lower ADC values than bilateral DWI (1.11 × 10(-3) mm(2) /s vs. 1.24 × 10(-3) mm(2) /s, P = 0.002). Regions of interest (ROIs) were comparable in size between the two techniques (2.90 vs. 2.13 cm(2) , P = 0.721). Qualitatively, all three radiologists scored sharpness of rFOV DWI images as significantly higher than bilateral DWI (P ≤ 0.002). Receiver operating characteristic (ROC) curve analysis showed a higher area under the curve (AUC) in BI-RADS classification for rFOV DWI compared to bilateral DWI (0.71 to 0.93 vs. 0.61 to 0.76, respectively).

CONCLUSION

Tumor morphology can be assessed in more detail with high-resolution DWI (rFOV) than with standard bilateral DWI by providing significantly sharper images.

Computer simulation of glioma growth and morphology

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.