Correlation Factors Analysis of Breast Cancer Tumor Volume Doubling Time Measured by 3D-Ultrasound

Predicting Tumor Volume Doubling Time and Progression-Free Survival in Untreated Patients from Patient-Derived-Xenograft (PDX) Models: A Translational Model-Based Approach

Tumor volume doubling time (TVDT) has been shown to be a potential surrogate marker of biological tumor activity. However, its availability in clinics is strongly limited due to ethical and practical reasons, as its assessment requires at least two subsequent tumor volume measurements in untreated patients. Here, a translational modeling framework to predict TVDT distributions in untreated cancer patient populations from tumor growth data in patient-derived xenograft (PDX) mice is proposed. Eleven solid cancer types were considered. For each of them, a set of tumor growth studies in PDX mice was selected and analyzed through a mathematical model to characterize the distribution of the exponential tumor growth rate in mice. Then, assuming an exponential growth of the tumor mass in humans, the growth rates were scaled from PDX mice to humans through an allometric scaling approach and used to predict TVDTs in untreated patients. A very good agreement was found between model predicted and clinically observed TVDTs, with 91% of the predicted TVDT medians fell within 1.5-fold of observations. Further, exploiting the intrinsic relationship between tumor growth dynamics and progression free survival (PFS), the exponential growth rates in humans were used to generate the expected PFS curves in absence of anticancer treatment. Predicted curves were extremely close to published PFS data from studies involving patient cohorts treated with supportive care or low effective therapies. The proposed approach shows promise as a potential tool to increase knowledge about TVDT in humans without the need of directly measuring tumor dimensions in untreated patients, and to predict PFS curves in untreated patients, that could fill the absence of placebo-controlled arms against which to compare treaded arms during clinical trials. However, further validation and refinement are needed to fully assess its effectiveness in this regard.

Tumor Doubling Time and Screening Interval

The goal of screening is to detect breast cancers when still curable to decrease breast cancer-specific mortality. Breast cancer screening in the United States is routinely performed with digital mammography and digital breast tomosynthesis. This article reviews breast cancer doubling time by tumor subtype and examines the impact of doubling time on breast cancer screening intervals. By the article's end, the reader will be better equipped to have informed discussions with patients and medical professionals regarding the benefits and disadvantages of the currently recommended screening mammography intervals.

Prediction of the Nottingham prognostic index and molecular subtypes of breast cancer through multimodal magnetic resonance imaging

PURPOSE

To explore the ability of intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and background parenchyma enhancement (BPE) to predict the Nottingham prognostic index (NPI) and molecular subtypes of breast cancer (BC).

MATERIALS AND METHODS

In this study, 93 patients with BC were included, and they all underwent DKI, IVIM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examinations. The corresponding mean kurtosis value (MK), pure diffusion (MD), perfusion fraction (f), pseudo diffusion coefficient (D*), true diffusion coefficient (D), and BPE were measured. We used logistic regression analysis to investigate the relevance between the NPI, molecular subtypes and variables. The diagnostic efficacy was analyzed using receiver operating characteristic curves (ROC).

RESULTS

The MD and D values of the high-level NPI group were significantly lower than those of the low-level NPI group (p < 0.01), and the f value of the high-level NPI group was obviously higher than that of low-level NPI group (p < 0.001). The area under curve (AUC) of the combined model (f + D) was 0.824. Comparing with non-Luminal subtypes, the Luminal subtypes showed obviously lower MK, f and D*, and the AUC of the combined model (MK + f + D*) was 0.785. In comparison to other subtypes, the MK and D* values of triple-negative subtype were higher than other subtypes, and the combined model (MK + D*) represented an AUC of 0.865.

CONCLUSION

The quantitative parameters of DKI and IVIM have vital value in predicting the NPI and molecular subtypes of BC, while BPE could not provide additional information. Besides, these combined models can obviously improve the prediction performance.

Consulting a neurosurgeon upon initial medical assessment reduces the time to the first surgery and potentially contributes to improved prognosis for glioblastoma patients

BACKGROUND

The neurological status of glioblastoma patients rapidly deteriorates. We recently demonstrated that early diagnosis and surgery within 3 weeks from the initial symptoms are associated with improved survival. While glioblastoma is a semi-urgent disease, the prehospital behaviors and clinical outcomes of glioblastoma patients are poorly understood. We aimed to disclose how prehospital patient behavior influences the clinical outcomes of glioblastoma patients.

METHODS

Isocitrate dehydrogenase-wildtype glioblastoma patients treated at our institution between January 2010 and December 2019 were reviewed. Patients were divided into two groups, neurosurgeon and non-neurosurgeon groups, based on the primary doctor whom patients sought for an initial evaluation. Patient demographics and prognoses were examined.

RESULTS

Of 170 patients, 109 and 61 were classified into the neurosurgeon and non-neurosurgeon groups, respectively. The median age of neurosurgeon group was significantly younger than the non-neurosurgeon group (61 vs. 69 years old, P = 0.019) and in better performance status (preoperative Karnofsky performance status scores $\ge$80: 72.5 vs. 55.7%, P = 0.027). The neurosurgeon group exhibited a significantly shorter duration from the first hospital visit to the first surgery than the non-neurosurgeon group (18 vs. 29 days, P < 0.0001). Furthermore, the overall survival of the neurosurgeon group was significantly more prolonged than that of the non-neurosurgeon group (22.9 vs. 14.0 months, P = 0.038).

CONCLUSION

Seeking an initial evaluation by a neurosurgeon was potentially associated with prolonged survival in glioblastoma patients. A short duration from the first hospital visit to the first surgery is essential in enhancing glioblastoma patient prognosis.

Breast Cancer Growth on Serial MRI: Volume Doubling Time Based on 3-Dimensional Tumor Volume Assessment

BACKGROUND

The volume doubling time (VDT) of breast cancer was most frequently calculated using the two-dimensional (2D) diameter, which is not reliable for irregular tumors. It was rarely investigated using three-dimensional (3D) imaging with tumor volume on serial magnetic resonance imaging (MRI).

PURPOSE

To investigate the VDT of breast cancer using 3D tumor volume assessment on serial breast MRIs.

STUDY TYPE

Retrospective.

SUBJECTS

Sixty women (age at diagnosis: 57 ± 10 years) with breast cancer, assessed by two or more breast MRI examinations. The median interval time was 791 days (range: 70-3654 days).

FIELD STRENGTH/SEQUENCE

3-T, fast spin-echo T2-weighted imaging (T2WI), single-shot echo-planar diffusion-weighted imaging (DWI), and gradient echo dynamic contrast-enhanced imaging.

ASSESSMENT

Three radiologists independently reviewed the morphological, DWI, and T2WI features of lesions. The whole tumor was segmented to measure the volume on contrast-enhanced images. The exponential growth model was fitted in the 11 patients with at least three MRI examinations. The VDT of breast cancer was calculated using the modified Schwartz equation.

STATISTICAL TESTS

Mann-Whitney U test, Kruskal-Wallis test, Chi-squared test, intraclass correlation coefficients, and Fleiss kappa coefficients. A P-value <0.05 was considered statistically significant. The exponential growth model was evaluated using the adjusted R2 and root mean square error (RMSE).

RESULTS

The median tumor diameter was 9.7 mm and 15.2 mm on the initial and final MRI, respectively. The median adjusted R2 and RMSE of the 11 exponential models were 0.97 and 15.8, respectively. The median VDT was 540 days (range: 68-2424 days). For invasive ductal carcinoma (N = 33), the median VDT of the non-luminal type was shorter than that of the luminal type (178 days vs. 478 days). On initial MRI, breast cancer manifesting as a focus or mass lesion showed a shorter VDT than that of a non-mass enhancement (NME) lesion (median VDT: 426 days vs. 665 days).

DATA CONCLUSION

A shorter VDT was observed in breast cancer manifesting as focus or mass as compared to an NME lesion.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Novel predictions of invasive breast cancer risk in mammography screening cohorts

Mammography screening programs are aimed at reducing mortality due to breast cancer by detecting tumors at an early stage. There is currently interest in moving away from the age-based screening programs, and toward personalized screening based on individual risk factors. To accomplish this, risk prediction models for breast cancer are needed to determine who should be screened, and when. We develop a novel approach using a (random effects) continuous growth model, which we apply to a large population-based, Swedish screening cohort. Unlike existing breast cancer prediction models, this approach explicitly incorporates each woman's individual screening visits in the prediction. It jointly models invasive breast cancer tumor onset, tumor growth rate, symptomatic detection rate, and screening sensitivity. In addition to predicting the overall risk of invasive breast cancer, this model can make separate predictions regarding specific tumor sizes, and the mode of detection (eg, detected at screening, or through symptoms between screenings). It can also predict how these risks change depending on whether or not a woman will attend her next screening. In our study, we predict, given a future diagnosis, that the probability of having a tumor less than (as opposed to greater than) 10-mm diameter, at detection, will be, on average, 2.6 times higher if a woman in the cohort attends their next screening. This indicates that the model can be used to evaluate the short-term benefit of screening attendance, at an individual level.

Delayed Diagnosis and Prognostic Impact of Breast Cancer During the COVID-19 Pandemic

BACKGROUND

Breast screening services were suspended for several months owing to the coronavirus disease 2019 (COVID-19) pandemic. We estimated the potential impact on breast cancer mortality using long-term global observations. However, the magnitude of the impact may vary across countries; therefore, we conducted an analysis and modeling study of this impact in Japan.

PATIENTS AND METHODS

We compared the clinicopathological features of breast cancers between the nonpandemicgroup (April 1, 2019 to October 31, 2019) and the pandemic group (April 1, 2020 to October 31, 2020). We also compared the estimated 10-year survival rates between the two groups based on the weighted average of the 10-year survival rate by clinical stage and site (2004-2007).

RESULTS

Results...Pandemic-related disruption decreased the number of breast cancer cases from296 to 249 during both 7-month periods. The percentage of patients with stage IIB or higher disease was significantly higher in the pandemic group than in the non-pandemic group (22.0% vs. 31.3%, P = 0.0133). The percentage of cases with a Ki-67 labeling index higher than 20% tended to be higher in the pandemic group than in the non-pandemic group (62.2% vs. 54.4%). The estimated 10-year survival rate was lower in the pandemic group than in the non-pandemic group (83.9% vs. 87.9%, 95% confidence interval of the difference: 0.87-8.8, P > 0.05).

CONCLUSION

We found more aggressive and advanced disease afterthe suspension of breast cancer screening services owing to the COVID-19 pandemic. This may have affected the long-term clinical outcomes of patients with breast cancer.

Breast cancer: emerging principles of metastasis, adjuvant and neoadjuvant treatment from cancer registry data

PURPOSE

Growing primary breast cancers (PT) can initiate local recurrences (LR), regional lymph nodes (pLN) and distant metastases (MET). Components of these progressions are initiation, frequency, growth duration, and survival. These characteristics describe principles which proposed molecular concepts and hypotheses must align with.

METHODS

In a population-based retrospective modeling approach using data from the Munich Cancer Registry key steps and factors associated with metastasis were identified and quantified. Analysis of 66.800 patient datasets over four time periods since 1978, reliable evidence is obtained even in small subgroups. Together with results of clinical trials on prevention and adjuvant treatment (AT) principles for the MET process and AT are derived.

RESULTS

The median growth periods for PT/MET/LR/pLN comes to 12.5/8.8/5/3.5 years, respectively. Even if 30% of METs only appear after 10 years, a pre-diagnosis MET initiation principle not a delayed one should be true. The growth times of PTs and METs vary by a factor of 10 or more but their ratio is robust at about 1.4. Principles of AT are 50% PT eradication, the selective and partial eradication of bone and lung METs. This cannot be improved by extending the duration of the previously known ATs.

CONCLUSION

A paradigm of ten principles for the MET process and ATs is derived from real world data and clinical trials indicates that there is no rationale for the long-term application of endocrine ATs, risk of PTs by hormone replacement therapies, or cascading initiation of METs. The principles show limits and opportunities for innovation also through alternative interpretations of well-known studies. The outlined MET process should be generalizable to all solid tumors.

Early Diagnosis and Surgical Intervention Within 3 Weeks From Symptom Onset Are Associated With Prolonged Survival of Patients With Glioblastoma

BACKGROUND

Glioblastoma (GBM) is a rapidly growing and most life-threatening malignant brain tumor. The significance of early treatment to the clinical outcomes of patients with GBM is unclear.

OBJECTIVE

To determine whether early diagnosis and surgery improve the preoperative and postoperative Karnofsky performance status (KPS) and prognosis of patients with GBM.

METHODS

Data of isocitrate dehydrogenase-wildtype patients with GBM treated at our institution between January 2010 and December 2019 were reviewed. Patients were classified into early or late diagnosis groups with a threshold of 14 days from initial symptoms. In addition, patients were divided into early, intermediate, and late surgery groups with thresholds of 21 and 35 days. Representative symptoms and patient prognoses were examined.

RESULTS

Of 153 patients, 72 and 81 were classified into the early and late diagnosis groups. The median tumor volume was significantly smaller in the former group. The proportion of patients with preoperative KPS scores 90 was 48.6% and 29.6% in the early and late diagnosis groups ( P = .016). The early, intermediate, and late surgery groups included 43, 24, and 86 patients. The median overall survival was significantly longer in the early surgery group than in the late surgery group (28.4 vs 18.7 months, P = .006). Multivariate analysis demonstrated that significant predictors of shorter survival included extent of tumor resection (partial or biopsy), preoperative and postoperative KPS 60, and O6-methylguanine-DNA-methyltransferase promoter status (unmethylated).

CONCLUSION

Early diagnosis within 2 weeks and surgical interventions within 3 weeks from the symptom onset are associated with prolonged patient survival. Early GBM treatment will benefit patients with GBM.

Value of Histogram of Gray-Scale Ultrasound Image in Differential Diagnosis of Small Triple Negative Breast Invasive Ductal Carcinoma and Fibroadenoma

Objective

To investigate the value of gray-scale ultrasound (US) image histogram in the differential diagnosis between small (≤2.00 cm), oval, or round triple negative breast invasive ductal carcinoma (TN-IDC) and fibroadenoma (FA).

Methods

Fifty-five cases of triple negative breast invasive ductal carcinoma (TN-IDC group) and 57 cases of breast fibroadenoma (FA group) confirmed by pathology in Hubei cancer hospital from September 2017 to September 2021 were analyzed retrospectively. The gray-scale US images were analyzed by histogram analysis method, from which some parameters (including mean, variance, skewness, kurtosis and 1st, 10th, 50th, 90th and 99th percentile) can be obtained. Intraclass correlation coefficient (ICC) was used to evaluate the inter observer reliability of histogram parameters. Histogram parameters between the TN-IDC and FA groups were compared using independent Student’s t-test or Mann-Whitney U-test, respectively. In addition, the receiver operating characteristic (ROC) curve analysis was used for the significant parameters to calculate the differential diagnosis efficiency.

Results

All the histogram parameters showed excellent inter-reader consistency, with the ICC values ranged from 0.883 to 0.999. The mean value, 1st, 10th, 50th, 90th and 99th percentiles of TN-IDC group were significantly lower than those of FA group (P < 0.05). The area under ROC curve (AUC) values of mean and n percentiles were from 0.807 to 0.848. However, there were no significant differences in variance, skewness and kurtosis between the two groups (P > 0.05).

Conclusion

Histogram analysis of gray-scale US images can well distinguish small, oval, or round TN-IDC from FA.

Estimating Distributions of Breast Cancer Onset and Growth in a Swedish Mammography Screening Cohort

BACKGROUND

In recent years, biologically motivated continuous tumor growth models have been introduced for breast cancer screening data. These provide a novel framework from which mammography screening effectiveness can be studied.

METHODS

We use a newly developed natural history model, which is unique in that it includes a carcinogenesis model for tumor onset, to analyze data from a large Swedish mammography cohort consisting of 65,536 participants, followed for periods of up to 6.5 years. Using patient data on age at diagnosis, tumor size, and mode of detection, as well as screening histories, we estimate distributions of patient's age at onset, (inverse) tumor growth rates, symptomatic detection rates, and screening sensitivities. We also allow the growth rate distribution to depend on the age at onset.

RESULTS

We estimate that by the age of 75, 13.4% of women have experienced onset. On the basis of a model that accounts for the role of mammographic density in screening sensitivity, we estimated median tumor doubling times of 167 days for tumors with onset occurring at age 40, and 207 days for tumors with onset occurring at age 60.

CONCLUSIONS

With breast cancer natural history models and population screening data, we can estimate latent processes of tumor onset, tumor growth, and mammography screening sensitivity. We can also study the relationship between the age at onset and tumor growth rates.

IMPACT

Quantifying the underlying processes of breast cancer progression is important in the era of individualized screening.

Prediction of Prognostic Factors and Genotypes in Patients With Breast Cancer Using Multiple Mathematical Models of MR Diffusion Imaging

Purpose

To explore the clinical value of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) based on diffusion-weighted MRI (DW-MRI) for predicting genotypes and prognostic factors of breast cancer.

Materials and Methods

A total of 227 patients with breast cancer confirmed by pathology were reviewed retrospectively. Diffusion-weighted imaging (DWI), IVIM, and DKI were performed in all patients. The corresponding ADC, true diffusion coefficient (D), perfusion-related diffusion coefficient (D*), perfusion fraction (f), mean diffusion rate (MD), and mean kurtosis value (MK) were measured. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curve were used to analyze the diagnostic efficacy in predicting the Nottingham prognostic index (NPI), the expression of antigen Ki-67, and the molecular subtypes of breast cancer. The nomogram of the combined genotype-prediction model was established based on the multivariate logistic regression model results.

Results

D* and MK values were significantly higher in the high-grade Nottingham group (NPI ≥ 3.4) than the low-grade Nottingham group (NPI < 3.4) (p < 0.01). When D* ≥ 30.95 × 10⁻³ mm²/s and MK ≥ 0.69, the NPI tended to be high grade (with areas under the curve (AUCs) of 0.712 and 0.647, respectively). The combination of D* and MK demonstrated the highest AUC of 0.734 in grading NPI with sensitivity and accuracy of 71.7% and 77.1%, respectively. Additionally, higher D*, f, and MK and lower ADC and D values were observed in the high Ki-67 than low Ki-67 expression groups (p < 0.05). The AUC of the combined model (D + D* + f + MK) was 0.755, being significantly higher than that of single parameters (Z = 2.770~3.244, p = 0.001~0.006) in distinguishing high from low Ki-67 expression. D* and f values in the Luminal A subtype were significantly lower than in other subtypes (p < 0.05). Luminal B showed decreased D value compared with other subtypes (p < 0.05). The HER-2-positive subtype demonstrated increased ADC values compared with the Luminal B subtype (p < 0.05). Luminal A/B showed significantly lower D, D*, MD, and MK than the non-Luminal subtypes (p < 0.05). The combined model (D + D* + MD + MK) showed an AUC of 0.830 in diagnosing the Luminal and non-Luminal subtypes, which is significantly higher than that of a single parameter (Z = 3.273~4.440, p < 0.01). f ≥ 54.30% [odds ratio (OR) = 1.038, p < 0.001] and MK ≥ 0.68 (OR = 24.745, p = 0.012) were found to be significant predictors of triple-negative subtypes. The combination of f and MK values demonstrated superior diagnostic performance with AUC, sensitivity, specificity, and accuracy of 0.756, 67.5%, 77.5%, and 82.4%, respectively. Moreover, as shown in the calibration curve, strong agreements were observed between nomogram prediction probability and actual findings in the prediction of genotypes (p = 0.22, 0.74).

Conclusion

DWI, IVIM, and DKI, as MR diffusion imaging techniques with different mathematical models showed potential to identify the prognosis and genotype of breast cancer. In addition, the combination of these three models can improve the diagnostic efficiency and thus may contribute to opting for an appropriate therapeutic approach in clinic treatment.

Has tumor doubling time in breast cancer changed over the past 80 years? A systematic review

Over the past century, epidemiologic changes and implementation of screening may have had an impact on tumor doubling time in breast cancer. Our study was designed to evaluate changes in tumor doubling time in breast cancer over the past 80 years. A systematic review of published literature and meta-regression analysis was performed. An online electronic database search was undertaken using the PubMed platform from inception until June 2020. All studies that measured tumor doubling time in breast cancer were included. A total of 151 publications were retrieved. Among them, 16 full-text articles were included in the qualitative analysis. An exponential growth model was used for quantitative characterization of tumor growth rate. Tumor doubling time has remained stable over the past 80 years. Recent studies have not only identified "fast growing tumor" (grade 3, human epidermal growth factor receptor 2-positive, triple-negative, or tumor with an elevated Ki-67) but also "inactive breast cancer" feeding the ongoing debate of overdiagnosis due to screening programs. The stability of tumor doubling time over the past 80 years, despite increasing and changing risk factors, supports the validity for our screening guidelines. Prospective studies based on more precise measurement of tumor size and adjustment for tumor characteristics are necessary to more clearly characterize the prognostic and predictive impact of tumor doubling time in breast cancer.

Breast cancer progression when definitive surgery is delayed

Deferment of definitive surgery for some breast cancers has been proposed as a way to conserve hospital resources during the COVID-19 pandemic. However, it is currently unknown which, if any, breast cancers are capable of progressing during a few to several months of observation. The difference between clinical size at diagnosis and final pathology size was assessed in 315 stage I-III primary invasive breast cancer patients who were divided into three groups based on the time between diagnosis and definitive surgery. Size differences over time were used to estimate specific growth rates. Compared with the group with ≤60 days between diagnosis and surgery, tumor growth was observed for 12% of tumors in the 61- to 120-day group and 17% of tumors in the >120-day group (p for trend = 0.032). Significantly greater specific growth rates were observed for tumors >2 cm by pathology measurement and for pathology node-positive patients (p < 0.0001 and p = 0.006, respectively). Specific growth rates were significantly greater for luminal B breast cancers than for luminal A breast cancers (p = 0.029) but not for triple-negative or HER2-positive breast cancers not selected for neo-adjuvant chemotherapy. There was no evidence of nodal progression with surgery delay. Fewer than 20% of stage I-III breast cancers not selected for neo-adjuvant chemotherapy evidence size progression during follow-up periods ranging from 61 to 294 days. Clinical-pathological features cannot reliably predict which tumors will grow. Luminal B phenotype was the only clinical variable known at the time of diagnosis that strongly predicted growth. If resource limitations mandate prioritization schemes for breast cancer surgery, luminal B breast cancer may be the highest priority.

Sensitivity and missed cancer rate in the symptomatic breast clinic-A retrospective cohort study of 40 323 patients

INTRODUCTION

Symptomatic presentations account for the majority of invasive breast cancer diagnoses. While the National Health Service Breast Screening Programme is subjected to strict quality control, no such system for performance monitoring exists in the symptomatic clinic. We assess the sensitivity of cancer detection and missed cancer rate for symptomatic breast patients to benchmark future outcome measures.

METHODS

A retrospective cohort study of patients attending the symptomatic breast clinic between October 2013 and October 2018 was performed. Patients with new cancer diagnoses were identified and screened for those who had presented to the department within the 3 years prior to their diagnosis. From this, the sensitivity and missed cancer rate were calculated.

RESULTS

About 40 323 patients were seen over the 5-year study period. About 2155 new cancers were diagnosed, with 2033 identified at their initial clinic attendance. A further 122 patients had cancer diagnosed on a subsequent appointment, of which 23 patients were considered to have had a delay in diagnosis. The sensitivity of the one-stop symptomatic breast clinic was therefore 99.0%, and the missed cancer rate was 0.06% over 5 years.

CONCLUSION

The missed cancer rate reported in this study is favorable compared to the outcomes reported in the National Health Service Breast Screening Programme and superior to the only other study reporting outcomes on a much smaller cohort. The unit in question therefore is performing exceptionally against current standards and sets a benchmark against which future performance can be measured.

A Mathematical Model to Predict Diagnostic Periods for Secondary Distant Metastases in Patients with ER/PR/HER2/Ki-67 Subtypes of Breast Cancer

Previously, a consolidated mathematical model of primary tumor (PT) growth and secondary distant metastasis (sdMTS) growth in breast cancer (BC) (CoMPaS) was presented. The aim was to detect the diagnostic periods for visible sdMTS via CoMPaS in patients with different subtypes ER/PR/HER2/Ki-67 (Estrogen Receptor/Progesterone Receptor/Human Epidermal growth factor Receptor 2/Ki-67 marker) of breast cancer. CoMPaS is based on an exponential growth model and complementing formulas, and the model corresponds to the tumor-node-metastasis (TNM) staging system and BC subtypes (ER/PR/HER2/Ki-67). The CoMPaS model reflects (1) the subtypes of BC, such as ER/PR/HER2/Ki-67, and (2) the growth processes of the PT and sdMTSs in BC patients without or with lymph node metastases (MTSs) in accordance with the eighth edition American Joint Committee on Cancer prognostic staging system for breast cancer. CoMPaS correctly describes the growth of the PT in the ER/PR/HER2/Ki-67 subtypes of BC patients and helps to calculate the different diagnostic periods, depending on the tumor volume doubling time of sdMTS, when sdMTSs might appear. CoMPaS and the corresponding software tool can help (1) to start the early treatment of small sdMTSs in BC patients with different tumor subtypes (ER/PR/HER2/Ki-67), and (2) to consider the patient almost healthy if sdMTSs do not appear during the different diagnostic periods.

Cancer recurrence times from a branching process model

As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where metastatic lesions are initiated at a rate which depends on the size of the primary tumor. The evolution of each metastasis is described as an independent branching process. We assume that the primary tumor is resected at a given size and study the earliest time at which any metastasis reaches a minimal detectable size. The parameters of our model are estimated independently for breast, colorectal, headneck, lung and prostate cancers. We use these estimates to compare predictions from our model with values reported in clinical literature. For some cancer types, we find a remarkably wide range of resection sizes such that metastases are very likely to be present, but none of them are detectable. Our model predicts that only very early resections can prevent recurrence, and that small delays in the time of surgery can significantly increase the recurrence probability.

The tumor doubling time is a useful parameter for predicting the histological type of thymic epithelial tumors

PURPOSE

We assessed the utility of the tumor doubling time (TDT) for predicting the histological type of thymic epithelial tumors.

METHODS

We retrospectively reviewed 130 patients with thymic epithelial tumors who underwent computed tomography two or more times before surgery. The patients were divided into low-risk thymoma (types A, AB and B1), high-risk thymoma (types B2 and B3) and thymic carcinoma (thymic carcinoma and thymic neuroendocrine tumor) groups. In the 96 patients who showed tumor enlargement, the relationship between the histological type and the TDT of the tumor was investigated.

RESULTS

The study population included 55 men and 41 women from 26 to 82 years of age. The TDT of the thymic carcinoma group (median 205 days) was significantly shorter in comparison to the low-risk thymoma (median 607 days) and high-risk thymoma (median 459 days) groups. No significant differences were observed between the low-risk thymoma and high-risk thymoma groups. When we set the cutoff time for differentiating thymic carcinoma group from thymoma at 313 days, the sensitivity and specificity were 83.8% and 82.1%, respectively.

CONCLUSIONS

The TDT is a useful parameter for differentiating between thymoma and thymic carcinoma group.

Why is pancreatic cancer so deadly? The pathologist's view

The remarkable aggressiveness of pancreatic cancer has never been fully explained. Although clearly multifactorial, we postulate that venous invasion, a finding seen in most pancreatic cancers but not in most cancers of other organs, may be a significant, underappreciated contributor to the aggressiveness of this disease. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Does breast cancer growth rate really depend on tumor subtype? Measurement of tumor doubling time using serial ultrasonography between diagnosis and surgery

BACKGROUND

Breast cancer growth is generally expected to differ between tumor subtypes. We aimed to evaluate tumor doubling time (DT) using ultrasonography and verify whether each tumor subtype has a unique DT.

METHODS

This retrospective study included 265 patients with invasive breast cancer who received serial ultrasonography between diagnosis and surgery. Tumor diameters were measured in three directions and DTs were calculated according to an exponential growth model using the volume change during serial ultrasonography. We investigated the relationships between DT, tumor subtype, and histopathological factors.

RESULTS

Volumes did not change in 95 (36%) of 265 tumors and increased in 170 (64%) tumors during serial ultrasonography (mean interval, 56.9 days). The mean volume increases of all tumors and volume-increased tumors were 22.1% and 34.5%, respectively. Triple-negative tumors had greater volume increases (40% vs. 20%, p = 0.001) and shorter DT (124 vs. 185 days, p = 0.027) than estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)- tumors. Volume-increased tumors had higher Ki-67 indices than those of volume-stable tumors in ER+/HER2- (p = 0.002) and ER+/HER2+ tumors (p = 0.011) and higher histological grades in all tumors except triple-negative tumors (p < 0.001). Triple-negative tumors with DTs < 90 days (short-DT) showed higher Ki-67 indices than those with DTs > 90 days (long-DT) (p = 0.008). In ER+/HER2- tumors, histological grades were higher for short-DT than for long-DT tumors (p = 0.022).

CONCLUSION

Differences in tumor DT depending on breast cancer subtype, Ki-67 index, and histological grade were confirmed using serial ultrasonography even during preoperative short interval.

Effectiveness of 3-dimensional shoulder ultrasound in the diagnosis of rotator cuff tears: A meta-analysis

BACKGROUND

Numerous quantitatively based studies measuring the accuracy of 3D shoulder ultrasound (US) for the diagnosis of rotator cuff tears remain inconclusive. In order to determine how effective 3D shoulder US is for detecting rotator cuff tears, a meta-analysis was performed systematically.

METHODS

Six electronic databases, PubMed/Medline, Embase, Cochrane Library, CNKI, VIP data, and Wanfang data, were utilized to retrieve articles praising the diagnostic value of 3D shoulder US for use in detecting rotator cuff tears. After screening and diluting out the articles that met inclusion criteria to be used for statistical analysis, the pooled evaluation indexes including sensitivity, specificity, and diagnostic odds ratio (DOR) as well as the summary receiver operating characteristic curve (SROC) were calculated utilizing Meta-Disc v.1.4.

RESULTS

Screening determined that out of 4220, 7 studies involving a total of 282 patients were deemed viable for inclusion in the meta-analysis. The results of the analysis showed that the sensitivity and specificity were at 94% and 83%, respectively, with a DOR of 60.06, Q* index of 0.9058 and the area under SROC of 0.9609. Additionally, a satisfactory accuracy of 3D shoulder US was observed in detecting full- and partial-thickness rotator cuff tears.

CONCLUSION

This meta-analysis suggests that 3D shoulder US is very effective and highly accurate to detect full-thickness rotator cuff tears, but may lack accuracy in the diagnosis of partial tears.

Spontaneous Slowing and Regressing of Tumor Growth in Childhood/Adolescent Papillary Thyroid Carcinomas Suggested by the Postoperative Thyroglobulin-Doubling Time

Background

Children and adolescents with papillary thyroid carcinomas (PTCs) have generally excellent prognoses despite their frequent extended disease. The tumor growth of young patients' PTCs might show spontaneous slowing postoperatively. We compared young PTC patients' postoperative thyroglobulin-doubling time (Tg-DT) with their preoperative hypothetical tumor volume-doubling time (hTV-DT).

Methods

Fourteen PTC patients aged ≤18 years who underwent total thyroidectomy at Kuma Hospital in 1998–2016 had biochemically persistent disease postoperatively. We calculated their Tg-DTs and estimated their preoperative TV-DTs with the tumor size and the patient's age at surgery, presuming that a single cancer cell was present at the patient's birth.

Results

Twelve patients had positive Tg-DTs ranging from 2.0 to 147 years, and the remaining two had negative Tg-DTs, indicating slow growth or even regression. The hTV-DTs were 0.3–0.6 years (median 0.5 years), which were significantly shorter than the Tg-DTs (p < 0.001), indicating much faster growth preoperatively. The analyses of the nine patients without radioactive iodine administration (RAI) gave similar results (p < 0.01).

Conclusions

Irrespective of RAI, the patients' postoperative Tg-DTs were significantly longer than their preoperative hTV-DTs and were negative values in two patients, indicating that the growth of these young patients' PTCs had spontaneously slowed or even regressed postoperatively.