Prognostic influence of 3-dimensional tumor volume on breast cancer compared to conventional 1-dimensional tumor size

Comparison of Tumor Diameter and Tumor Volume in Terms of Aggressive Tumor Behavior and Prognosis in Papillary Thyroid Cancer

BACKGROUND

Tumor diameter may not reflect tumor burden accurately in all cancers. In this study, we aimed to investigate the relationship between tumor volume (TV) and aggressive features and prognosis in papillary thyroid cancer (PTC).

METHODS

Patients diagnosed with single foci PTC were recruited for the study. The largest tumor diameter was considered as the primary tumor diameter. TV was calculated using the formula for an ellipsoid shape, considering the three pathologically specified dimensions. Primary tumor diameter and TV were compared in terms of aggressive tumor characteristics and prognosis.

RESULTS

The data of 118 patients were analyzed. There was no significant relationship between primary tumor diameter and lymph node metastasis (LNM), extrathyroidal extension (ETE), and vascular invasion (p > 0.05 for each). In patients with tumor diameter >2 cm, TV was negatively associated with LNM (p = 0.015). One-unit increase in TV was associated with 1.629 times greater likelihood of absence of LNM (95% CI: 1.099-2.415). When the TV was ≤5.26 cm3, the sensitivity and specificity for the presence of LNM were 88.9% and 75.8%, respectively. Again in this group, the sensitivity for the occurrence of ETE was 100.0% and specificity was 45.7% when the TV was ≤9.49 cm3. There was no significant difference in the five-year disease-free survival between tumor diameter and TV.

CONCLUSIONS

In contrary to studies with other cancer types in the literature, there was a significant but negative relationship between TV and LNM. Further large-scale studies are needed to determine whether TV can be used as a prognostic factor in PTC.

Improving lesion volume measurements on digital mammograms

Lesion volume is an important predictor for prognosis in breast cancer. However, it is currently impossible to compute lesion volumes accurately from digital mammography data, which is the most popular and readily available imaging modality for breast cancer. We make a step towards a more accurate lesion volume measurement on digital mammograms by developing a model that allows to estimate lesion volumes on processed mammogram. Processed mammograms are the images routinely used by radiologists in clinical practice as well as in breast cancer screening and are available in medical centers. Processed mammograms are obtained from raw mammograms, which are the X-ray data coming directly from the scanner, by applying certain vendor-specific non-linear transformations. At the core of our volume estimation method is a physics-based algorithm for measuring lesion volumes on raw mammograms. We subsequently extend this algorithm to processed mammograms via a deep learning image-to-image translation model that produces synthetic raw mammograms from processed mammograms in a multi-vendor setting. We assess the reliability and validity of our method using a dataset of 1778 mammograms with an annotated mass. Firstly, we investigate the correlations between lesion volumes computed from mediolateral oblique and craniocaudal views, with a resulting Pearson correlation of 0.93 [95% confidence interval (CI) 0.92 - 0.93]. Secondly, we compare the resulting lesion volumes from true and synthetic raw data, with a resulting Pearson correlation of 0.998 [95%CI 0.998 - 0.998] . Finally, for a subset of 100 mammograms with a malignant mass and concurrent MRI examination available, we analyze the agreement between lesion volume on mammography and MRI, resulting in an intraclass correlation coefficient of 0.81 [95%CI 0.73 - 0.87] for consistency and 0.78 [95%CI 0.66 - 0.86] for absolute agreement. In conclusion, we developed an algorithm to measure mammographic lesion volume that reached excellent reliability and good validity, when using MRI as ground truth. The algorithm may play a role in lesion characterization and breast cancer prognostication on mammograms.

The Value of Micro-CT in the Diagnosis of Lung Carcinoma: A Radio-Histopathological Perspective

Micro-computed tomography (micro-CT) is a relatively new imaging modality and the three-dimensional (3D) images obtained via micro-CT allow researchers to collect both quantitative and qualitative information on various types of samples. Micro-CT could potentially be used to examine human diseases and several studies have been published on this topic in the last decade. In this study, the potential uses of micro-CT in understanding and evaluating lung carcinoma and the relevant studies conducted on lung and other tumors are summarized. Currently, the resolution of benchtop laboratory micro-CT units has not reached the levels that can be obtained with light microscopy, and it is not possible to detect the histopathological features (e.g., tumor type, adenocarcinoma pattern, spread through air spaces) required for lung cancer management. However, its ability to provide 3D images in any plane of section, without disturbing the integrity of the specimen, suggests that it can be used as an auxiliary technique, especially in surgical margin examination, the evaluation of tumor invasion in the entire specimen, and calculation of primary and metastatic tumor volume. Along with future developments in micro-CT technology, it can be expected that the image resolution will gradually improve, the examination time will decrease, and the relevant software will be more user friendly. As a result of these developments, micro-CT may enter pathology laboratories as an auxiliary method in the pathological evaluation of lung tumors. However, the safety, performance, and cost effectiveness of micro-CT in the areas of possible clinical application should be investigated. If micro-CT passes all these tests, it may lead to the convergence of radiology and pathology applications performed independently in separate units today, and the birth of a new type of diagnostician who has equal knowledge of the histological and radiological features of tumors.

Outcomes of surgical resection of super-giant (≥15 cm) hepatocellular carcinoma: Volume does matter, if not the size

BACKGROUND AND AIM

Resection for giant hepatocellular carcinoma (HCC) (≥10 cm) is deemed safe and feasible. However, a super-giant HCC (≥15 cm) poses unique technical complexity for hepatectomy with limited data suggesting feasibility and oncologic efficiency. This study aims to evaluate the short-term and long-term outcomes of hepatectomy in patients with super-giant HCC.

METHODS

A retrospective review was conducted on patients with super-giant HCC who underwent hepatectomy from 2011 to 2021. We report perioperative and oncologic outcomes such as length of stay (LOS), 30-day readmission, 90-day mortality, and cumulative survival rate.

RESULTS

Of the 18 patients, the median tumor diameter was 172.5 mm (range 150-250). The most common risk factor was chronic hepatitis B virus (HBV) infection (n=7, 38.9%). Most of the patients were Barcelona Clinic Liver Cancer (BCLC) Stage B (n=14, 77.8%) and Hong Kong Liver Cancer (HKLC) Stage IIb (n=15, 83.3%). Extended right hepatectomy was the most common procedure. The median LOS was 11 days (range 3-90). The most common post-operative complication was pneumonia (n=4, 22.2%). Fourteen patients were discharged well without any need for invasive therapy (n=7, 38.9% no complications, n=1, 5.6% Clavien Grade I, n=6, 33.3% Clavien Grade II). Thirty-day readmission rate was 5.6% (n=1) and 90-day mortality rate was 5.6% (n=1). There were 12 patients (66.7%) with microvascular invasion and three patients (16.7%) with macrovascular invasion. Most patients had Grade III (poorly differentiated) HCC (n=9, 50%). At a median follow-up of 11 months (range 2-95), 12 (66.7%) patients had local recurrence, and 9 (50%) developed distant metastasis. The 1-, 2-, and 3-year cumulative disease-free survival (DFS) was 36%, 18%, and 18%, respectively. The 1-, 2-, and 3-year cumulative overall survival was 49% and 39%, and 29%, respectively.

CONCLUSION

Primary hepatic resection is safe in patients with super-giant HCC. However, long-term outcomes are poor, and high tumor volume may be associated with inferior oncological outcomes in HCC.

RELEVANCE FOR PATIENTS

The presentation of super-giant HCCs may be asymptomatic and some patients are diagnosed late with limited treatment options. In some centers, this group of patients are denied surgical resection and recommended for only locoregional therapies like TACE. This paper demonstrates that hepatic resection is safe and may be an option in patients who present at an advanced stage with a high tumor burden.

Correlation between contrast-enhanced cone-beam breast computed tomography features and prognostic staging in breast cancer

OBJECTIVE

To evaluate whether contrast-enhanced cone-beam breast CT (CE-CBBCT) features can risk-stratify prognostic stage in breast cancer.

METHODS

Overall, 168 biopsy-proven breast cancer patients were analysed: 115 patients in the training set underwent scanning using v. 1.5 CE-CBBCT between August 2019 and December 2019, whereas 53 patients in the test set underwent scanning using v. 1.0 CE-CBBCT between May 2012 and August 2014. All patients were restaged according to the American Joint Committee on Cancer eighth edition prognostic staging system. Following the combination of CE-CBBCT imaging parameters and clinicopathological factors, predictors that were correlated with stratification of prognostic stage via logistic regression were analysed. Predictive performance was assessed according to the area under the receiver operating characteristic curve (AUC). Goodness-of-fit of the models was assessed using the Hosmer-Lemeshow test.

RESULTS

As regards differentiation between prognostic stage (PS) I and II/III, increased tumour-to-breast volume ratio (TBR), rim enhancement pattern, and the presence of penetrating vessels were significant predictors for PS II/III disease (p < 0.05). The AUCs in the training and test sets were 0.967 [95% confidence interval (CI) 0.938-0.996; p < 0.001] and 0.896 (95% CI, 0.809-0.983; p = 0.001), respectively. Two features were selected in the training set of PS II vs III, including tumour volume [odds ratio (OR)=1.817, p = 0.019] and calcification (OR = 4.600, p = 0.040), achieving an AUC of 0.790 (95% CI, 0.636-0.944, p = 0.001). However, there was no significant difference in the test set of PS II vs III (P＞0.05).

CONCLUSION

CE-CBBCT imaging biomarkers may provide a large amount of anatomical and radiobiological information for the pre-operative distinction of prognostic stage.

ADVANCES IN KNOWLEDGE

CE-CBBCT features have distinctive promise for stratification of prognostic stage in breast cancer.

Prognostic impact of dimensional factors in pT1 gastric cancer

BACKGROUND

The significance of the dimensional factors (tumor diameter, area and volume) as the prognostic factor has not been precisely evaluated in pT1 gastric cancer.

OBJECTIVES

This study aimed to identify the clinical impact and to confirm the clinical feasibility of the dimensional factors as prognostic factors in pT1 gastric cancer.

METHODS

We analyzed prognostic factors for disease-specific survival (DSS), overall survival (OS) using clinicopathological factors by univariate and multivariate analyses and the pattern of recurrence in 2011 pT1 gastric cancer (mucosal and submucosal cancers) undergoing R0 gastrectomy. The cut-off values of each dimensional factor was decided by the ROC curve.

RESULTS

Cox proportional hazard regression model showed that older age (≥75) and more advanced pN stage were adverse independent prognostic factors for DSS, and revealed that older age (≥75), greater preoperative co-morbid diseases, proximal and total gastrectomy, operative method and Clavien-Dindo classification (≥grade III) were independent adverse factors for OS. Any dimensional factors were not independent prognostic factors for any survival.

CONCLUSIONS

The dimensional factors do not influence both OS and DSS in pT1 gastric cancer patients and so it is difficult to apply these dimensional factors for conducting therapeutic strategies.

Complications and local relapse after intraoperative low-voltage X-ray radiotherapy in breast cancer

Purpose

To study those factors that influence the occurrence of surgical complications and local relapse in patients intervened for breast cancer and receiving intraoperative radiotherapy.

Methods

Observational study on patients intervened for breast cancer with conservative surgery and intraoperative radiotherapy with low-voltage X-ray energy source (INTRABEAM), from 2015 to 2017 with 24 months minimum follow-up. Variables possibly associated to the occurrence of postoperative complications were analyzed with the Student t-test and the Fisher exact test; P < 0.05 considered significant. Subsequently, the construction of multiple multivariate analysis models began, thus building a logistic regression analysis using the IBM SPSS Statistics ver. 23 software. Local relapse was described.

Results

The study included 102 patients, mean age of 61.2 years; mean global size of tumor, 12.2 mm. Complications occurred in 29.4%. Fibrosis was the most frequently observed complication, followed by postoperative seroma. Using a 45 mm or larger applicator were significantly associated with the occurrence of complications. Tumor size 2 cm or larger and reintervention showed borderline significant association. Only one case of local relapse was observed.

Conclusion

Certain factors may increase the risk of complication after the use of intraoperative radiotherapy. Using external complementary radiotherapy does not seem to increase the rate of complications. Select patients and the involvement of a multidisciplinary team are essential for achieving good results.