Biopsy Proven Breast Cancer Patients Research Articles

Targeted axillary dissection using carbon marking for patients with node-positive breast cancer following neoadjuvant therapy (TADCOM): study protocol for a prospective, multicenter, randomized controlled trial

BackgroundNeoadjuvant chemotherapy (NAC) for breast cancer enables pathological complete response (pCR) in patients initially diagnosed with axillary lymph node metastases, potentially obviating the need for axillary lymph node dissection (ALND). Current targeted axillary dissection (TAD) techniques, guided by traditional tissue markers placed prior to NAC, face challenges such as marker loss and high costs. Carbon nanoparticle suspension injection (CNSI) offers a stable and reliable alternative for marking, which could enhance the TAD procedure. This study aims to evaluate the feasibility and accuracy of different TAD strategies using CNSIs and to explore their clinical utility in locally advanced breast cancer.MethodsThis prospective, multicenter, randomized controlled trial will enroll 126 biopsy-proven breast cancer patients with suspicious axillary lymph node metastases (cN1-2a) who achieve ycN0 status following NAC. Participants will be randomized in a 1:1:1 ratio to undergo TAD guided by: [1] conventional tissue clips (CG-TAD); [2] CNSI lymph node marking (CN-LNM); or [3] peritumoral CNSI mapping (PCN-MAP). Primary endpoints include retrieval rate of marked lymph nodes, number of sentinel and marked lymph nodes, concordance rates, and complication rates. Secondary endpoints encompass regional and distant recurrence rates, survival outcomes, surgical duration, postoperative complications, quality of life scores, and margin status in breast-conserving surgery. Statistical analyses will adhere strictly to the CONSORT guidelines.DiscussionThis study aims to evaluate the feasibility and accuracy of CNSI for targeted axillary dissection in breast cancer patients following neoadjuvant chemotherapy and to explore its clinical significance in reducing surgical complications and costs, as well as improving surgical precision.Trial registrationClinicaltrials.gov, NCT04744506, Registered 27 December 2020, Updated 24 September 2024. Protocol Version Ver 1.2, 17/9/2024.

Breast Cancer in Young Women: Analysis of Incidence, Clinicopathological Profile and Biological Behaviour in a Tertiary Care Institute from South India

Aims and Objectives: There is an increasing incidence of breast cancer in young women and many of these patients are considered to have more aggressive disease biology. The study aimed to find out the demographic profile, clinicopathological profile, and management details in patients under the age of 40 years treated for breast cancer in a tertiary care institute. Materials and Methods: The study retrospectively analysed all the females with biopsy proven breast cancer treated at our oncology department between January 2012 and December 2018. Patients aged below 40 years were stratified from the total breast cancer patients. The data related to demographic profile, clinical staging, pathological staging, hormonal status and treatment details were collected from medical records for the patients and analysed. Results: A total of 1056 biopsy proven breast cancer patients were treated during the study period. Out of which, the breast cancer patients under the age of 40 years were 161 (15.24%). The mean age at presentation was 33 years. Maximum patients were between the age group of 35 to 40 years (45.4%). Most of the patients were presented with Stage III (44%). Infiltrating Ductal Carcinoma, Grade II was the most common histologic type and grade. ER (Oestrogen Receptor) positivity seen in 49% of patients and PR (Progesterone receptor) Positivity in 49.7% and 46% had HeR2 Positivity. Conclusion: Our study concludes that the incidence of breast cancer patients under the age of 40 years is increasing. These patients tend to have higher grade tumours, Her2 Positive and triple-negative breast cancer. Young patients presenting with breast lumps should undergo all standard screening and diagnostic investigations must be carried out for early diagnosis and proper interventions.

Detectability of Breast Cancer Through Inverse Heat Transfer Modeling Using Patient-Specific Surface Temperatures

Abstract Breast cancer in women is a prevalent disease which takes over 680,000 lives each year worldwide. Early detection of breast cancer through screening has played a significant role in reducing the mortality rates. The current screening paradigm has shown the difficulties in detecting cancers for patients with dense breasts, small and deep tumors, and cancer types that are difficult to visualize. Infrared imaging (IRI) aided by advanced thermal analysis of the breast has shown great promise in detecting cancer using surface temperatures effected by a metabolically active and highly perfused tumor region. We previously developed an inverse heat transfer approach to detect the presence and absence of breast cancer using IRI, called the IRI-Numerical Engine. It was validated with 23 biopsy-proven breast cancer patients irrespective of breast density and cancer type at various tumor depths (0.95 cm to 5.45 cm from the breast surface). The current work is aimed to obtain the detectability limit of the IRI-Numerical Engine by testing the capability of detecting 10-20 mm tumors at various depths in patient-specific digital breast models. In addition, a study on the effect of tumor size, tumor location, breast shape, and breast size on the surface temperatures of patient-specific models was conducted to verify that an IR camera could capture these surface temperature distributions. The algorithm was able to detect the presence of a tumor at various depths, and deep tumors are detectable given the appropriate thermal sensitive IR camera.

Abstract PO4-07-10: Validation of An Ultrasound-Based Scoring System of Axillary Metastasis in Breast Cancer

Abstract Introduction: Ultrasound is the imaging modality of choice in the evaluation of axillary involvement in breast cancer. Our group previously created a scoring method to predict axillary lymph node metastasis (ALNM) based on ultrasound characteristics. In this study we validated the model and tested it among different Memorial Sloan Kettering Breast Cancer Sentinel Lymph Node Metastasis Nomogram1 (MSK) subgroups. Methods: The ultrasound score (table 1) was previously developed using data collected at a single institution from 2019 – 2021 by allocating points based on the regression coefficients of variables found to significantly predict ALNM. Subsequent evaluation of the discrimination of this model found it was robust to different patient demographic and tumor characteristics based on receiver operating characteristic curve analysis2. In this study, we validated the test statistics of our score at an outside institution. We also pooled patients from both institutions and evaluated the score performance in different MSK subgroups by the likelihood for sentinel node metastasis based off of clinical and pathologic data without accounting for imaging findings. Results: Between 2019-2021, 140 patients with breast cancer were analyzed for validation of the axillary ultrasound scoring system and when combined with the dataset of patients from the index institution, 358 pooled patients were stratified by predicted ALNM positivity according to MSK. In the validation cohort, the NPV for low risk (0-1) scores was 87%, while the PPV for high-risk (5+) scores was 71%. Overall in the combined cohort, 241 (67%) patients had low risk (0-1) axillary ultrasound scores and 33 (9%) had high risk (5+) scores. In this combined cohort, NPV was 84% (203/241 low-risk score patients were node negative), while PPV for high-risk scores was 85% (28/33 high risk score patients were node positive). When analyzed according to level of MSK predicted ALNM rates, for patients with < 50% predicted ALNM positivity, the NPV of low-risk scores was 87-89% and the PPV for high-risk axillary scores was 100%. For patients with >50% predicted ALNM positivity, the NPV of low-risk scores was 66% and the PPV of high-risk scores was 82%. Conclusions: A scoring system to predict ALNM among biopsy proven breast cancer patients undergoing upfront surgery was successfully developed from a multivariate model based on axillary ultrasound characteristics. This model was validated at a separate institution. The scoring system shows advantageous negative and positive predictive values for axillary node metastasis, especially among patients with < 50% predicted nodal involvement based on the MSK nomogram. This data may help foster better communication about ALNM risk between radiologists and treating clinicians to inform treatment decisions. Table. Scoring System for Likelihood of ALNM based on Ultrasound Characteristics Citation Format: Spencer Van Decar, Elizabeth Carpenter, Alexandra Adams, Jason Shore, Iulian Dragusin, Erika Davis, Craig Tork, Robert Krell, Troy Graybeal, Katherine Clifton, Arianna Buckley, Guy Clifton. Validation of An Ultrasound-Based Scoring System of Axillary Metastasis in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-07-10.

Breast cancer detection using enhanced IRI-numerical engine and inverse heat transfer modeling: model description and clinical validation

Effective treatment of breast cancer relies heavily on early detection. Routine annual mammography is a widely accepted screening technique that has resulted in significantly improving the survival rate. However, it suffers from low sensitivity resulting in high false positives from screening. To overcome this problem, adjunctive technologies such as ultrasound are employed on about 10% of women recalled for additional screening following mammography. These adjunctive techniques still result in a significant number of women, about 1.6%, who undergo biopsy while only 0.4% of women screened have cancers. The main reason for missing cancers during mammography screening arises from the masking effect of dense breast tissue. The presence of a tumor results in the alteration of temperature field in the breast, which is not influenced by the tissue density. In the present paper, the IRI-Numerical Engine is presented as an adjunct for detecting cancer from the surface temperature data. It uses a computerized inverse heat transfer approach based on Pennes’s bioheat transfer equations. Validation of this enhanced algorithm is conducted on twenty-three biopsy-proven breast cancer patients after obtaining informed consent under IRB protocol. The algorithm correctly predicted the size and location of cancerous tumors in twenty-four breasts, while twenty-two contralateral breasts were also correctly predicted to have no cancer (one woman had bilateral breast cancer). The tumors are seen as highly perfused and metabolically active heat sources that alter the surface temperatures that are used in heat transfer modeling. Furthermore, the results from this study with twenty-four biopsy-proven cancer cases indicate that the detection of breast cancer is not affected by breast density. This study indicates the potential of the IRI-Numerical Engine as an effective adjunct to mammography. A large scale clinical study in a statistically significant sample size is needed before integrating this approach in the current protocol.

Stereotactic Radiosurgery for Women Older than 65 with Breast Cancer Brain Metastases.

Breast cancer is the second most common cause of brain metastases (BM). Despite increasing incidence of BM in older women, there are limited data on the optimal management of BM in this age group. In this study, we assessed the survival outcomes and treatment patterns of older breast cancer patients ≥65 years old with BM compared to younger patients at our institution. An IRB-approved single-institutional retrospective review of biopsy-proven breast cancer patients with BM treated with 1- to 5-fraction stereotactic radiation therapy (SRS) from 2015 to 2020 was performed. Primary endpoint was intracranial progression-free survival (PFS) defined as the time interval between the end of SRS to the date of the first CNS progression. Secondary endpoints were overall survival (OS) from the end of SRS and radiation treatment patterns. Kaplan-Meier estimates and Cox proportional hazard regression method were used for survival analyses. A total of 112 metastatic breast cancer patients with BMs were included of which 24 were ≥65 years old and 88 were <65 years old. Median age at RT was 72 years (range 65-84) compared to 52 years (31-64) in younger patients. There were significantly higher number of older women with ER/PR positive disease (75% vs. 49%, p = 0.036), while younger patients were more frequently triple negative (32% vs. 12%, p = 0.074) and HER2 positive (42% vs. 29%, p = 0.3). Treatment-related adverse events were similar in both groups. Overall, 14.3% patients had any grade radiation necrosis (RN) (older vs. young: 8.3% vs. 16%, p = 0.5) while 5.4% had grade 3 or higher RN (0% vs. 6.8%, p = 0.7). Median OS after RT was poorer in older patients compared to younger patients (9.5 months vs. 14.5 months, p = 0.037), while intracranial PFS from RT was similar between the two groups (9.7 months vs. 7.1 months, p = 0.580). On univariate analysis, significant predictors of OS were age ≥65 years old (hazard risk, HR = 1.70, p = 0.048), KPS ≤ 80 (HR = 2.24, p < 0.001), HER2 positive disease (HR = 0.46, p < 0.001), isolated CNS metastatic disease (HR = 0.29, p < 0.001), number of brain metastases treated with RT (HR = 1.06, p = 0.028), and fractionated SRS (HR = 0.53, p = 0.013). On multivariable analysis, KPS ≤ 80, HER2 negativity and higher number of brain metastases predicted for poorer survival, while age was not a significant factor for OS after adjusting for other variables. Patients who received systemic therapy after SRS had a significantly improved OS on univariate and multivariable analysis (HR = 0.32, p < 0.001). Number of brain metastases treated was the only factor predictive of worse PFS (HR = 1.06, p = 0.041), which implies a 6% additive risk of progression for every additional metastasis treated. Although older women had poorer OS than younger women, OS was similar after adjusting for KPS, extracranial progression, and systemic therapy; and there was no difference in rates of intracranial PFS, neurological deaths, and LMD in the different age groups. This study suggests that age alone may not play an independent role in treatment-selection and that outcomes for breast cancer patients with BMs and personalized decision-making including other clinical factors should be considered. Future studies are warranted to assess neurocognitive outcomes and other radiation treatment toxicities in older patients.

Performance of contrast-enhanced mammography for detecting multifocal and multicentric breast cancer and evaluating tumour size, and implications for surgical management: Early experience in a tertiary centre.

To compare diagnostic accuracy of contrast-enhanced mammography (CEM) with standard 2D digital mammography (equivalent to low-energy image; LEM) for detection of multifocal and multicentric breast cancer and evaluation of tumour size and disease extent for preoperative planning. Biopsy proven breast cancer patients who underwent CEM preoperatively between January 2021 and January 2023 were included in this study. CEM and LEM images were independently reviewed by at least two blinded readers. Lesion location, number, size (maximal diameter) and extension across the midline and/or nipple invasion were recorded. Tumour number and size estimated on imaging were compared with final operative histology, which served as the gold standard. Forty-nine patients (48 females and 1 male) and 50 cases (one patient had bilateral breast lesions) were included in the analysis. Median patient age was 60 (IQR 51, 69). CEM had significantly higher lesion detection rate compared with LEM, with sensitivities of 78% for LEM and 92% for CEM for the index tumour and 15% for LEM and 100% for CEM for multicentric and multifocal cancer. We found no statistically significant difference in median tumour size measurements on CEM and final surgical specimen (P value = 0.97); however, a significant difference was identified in the tumour size measured on LEM and surgical specimen (P value < 0.001). CEM is superior to standard 2D digital mammography for detection of multifocal and multicentric breast cancer and is a reliable and more accurate method for estimating tumour size.

Abstract P1-10-10: Radiation Treatment Patterns for Elderly Women with Breast Cancer Brain Metastases

Abstract Background Breast cancer is the second most common cause of brain metastases (BM). Despite increasing incidence of BM in elderly patients, there is limited data on the optimal management of BM in this age group. In this study, we assessed the survival outcomes and treatment patterns of elderly breast cancer patients with BM (≥ 65 yo) treated at our institution and compared them to younger patients. Methods An IRB-approved single-institutional review of biopsy-proven breast cancer patients with BM treated with 1 to 5-fraction stereotactic radiation therapy (SRT) from 2015 to 2020 was performed. Primary endpoint was intracranial progression free survival (PFS) defined as time interval between end of SRT to date of first CNS progression. Secondary endpoints were overall survival (OS) from end of SRT, and radiation treatment patterns. Kaplan-Meier estimates, and Cox proportional hazard regression method were used for survival analyses. SPSS v26.0 was used for statistical analysis and p-value &amp;lt; 0.05 was considered significant. Results A total of 115 metastatic breast cancer patients with BMs were included of which N=29 were ≥65 yo and N=86 were &amp;lt; 65 yo. They received a total of 43 and 143 courses of stereotactic linac-based radiation therapy (RT) respectively to a mean number of 4.3 BM lesions (range 1-22). Median age at RT was 70 years (range 65-84) compared to 50.5 years (31-64) in younger patients. About 55.2% of elderly patients were ER/PR positive/Her2 negative (vs 24.4% in younger cohort), 31% were Her2 positive (vs 41.9%) and 13.8% were triple negative (vs 33.7%). Among patient characteristics, there was significant difference among elderly and young patients in hormone receptor status (p = 0.016); CNS only oligometastatic disease (0% vs 11.2%, p = 0.005); and the presence of extracranial disease at SRS (97.7% vs 79.7%, p &amp;lt; 0.001). There was no significant difference between the two age groups in Karnofsky performance score (KPS) (62.7% vs 45.5% with KPS ≤ 80, p = 0.131), number of brain lesions treated (23.2% vs 30.1% with ≥ 5 BMs, p = 0.445), number of patients receiving prior whole brain radiotherapy (WBRT) (10.3% vs 19.8%, p = 0.062), surgery (23.2% vs 30.1%, p = 0.592), systemic therapy (including chemotherapy, targeted therapy and endocrine therapy) after SRT (86% vs 86.7%, p = 0.543), and salvage WBRT (10.3% vs 19.8%, p = 0.134). Median OS after RT was poorer in patients ≥ 65 yo compared to younger patients (7.9 months vs 14.4 months, p = 0.020), while intracranial PFS from RT was similar (8.5m vs 6.5m, p =0.345). The rates of freedom from neurological death and leptomeningeal disease (LMD) at 1 year were similar between the two groups (83.3% vs 87%, p = 0.780 and 87.6% vs 73.3%, p = 0.627, respectively). On univariate analysis, significant predictors of survival were age ≥65 yo (hazard risk, HR = 1.56), KPS &amp;lt; 80 (HR = 1.69), extracranial progression at RT (HR = 2.44), systemic therapy after RT (HR = 0.28) and LMD (HR = 1.57). On multivariate analysis, age was not a significant factor for survival after adjusting for KPS, extracranial progression and systemic therapy. Conclusions Although elderly women had poorer OS than younger women, OS was similar after adjusting for KPS, extracranial progression and systemic therapy; and there was no difference in rates of intracranial PFS, neurological deaths and LMD in the different age groups. This study suggests that age alone may not play an independent role in treatment-selection and outcomes for breast cancer patients with BMs and personalized decision making including other clinical factors should be considered. Future studies are warranted to assess neurocognitive outcomes and other radiation treatment toxicities in elderly patients. Citation Format: Rituraj Upadhyay, Haley K. Perlow, Nicole Williams, Brett Klamer, Julia White, Jose G. Bazan, Sachin R. Jhawar, Dukagjin M. Blakaj, John Grecula, Andrea Arnett, Evan Thomas, Arnab Chakravarti, Raju R. Raval, Maryam Lustberg, Joshua Palmer, Sasha Beyer. Radiation Treatment Patterns for Elderly Women with Breast Cancer Brain Metastases [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-10-10.

MRI Features of Synchronous Masses in Known Breast Cancer Patients in Predicting Benign Versus Malignant Lesions: A Case Based Review at Tertiary Care Cancer Hospital.

Sara RehmanObjectives The purpose of this study was to determine the diagnostic accuracy of breast magnetic resonance imaging (MRI) in classifying incidental satellite masses in biopsy-proven breast cancer patients as benign or malignant masses and assessing its impact on surgical management of these patients. We also analyzed the incidence of MRI-detected lesions, which were thereafter assessed with second look ultrasound (US). Materials and Methods A retrospective study was performed on breast cancer patients presenting from August 01, 2016 to July 31, 2019, with satellite masses seen on base line MRI. Satellite masses were classified as benign and malignant based on MRI features of shape, margin, T2-weighted imaging signals, internal enhancement pattern, enhancement kinetic curves, and diffusion restriction. This was compared with results of histopathological examination. The number of MRI-detected lesions, location of the satellite mass, and type of surgery were also documented. Results Out of 400 breast cancer patients undergoing MRI breast, 115 patients had multiple masses. Histopathological diagnosis was available for 73 patients; and a total of 93 satellite masses were evaluated. There was evidence of additional masses on second look ultrasound in 21 patients. Of 72 masses classified as malignant on MRI, 58 showed malignant pathological outcome; while out of 21 masses characterized as benign on MRI, 18 turned out to be benign on histopathology. A statistically significant association was found between MRI features and pathological outcome of satellite masses ( p = 0.001). The sensitivity, specificity, positive and negative predictive values, and accuracy were 95%, 56%, 80.56%, 85.7% and 81.7%, respectively. Based on these findings, modified radical mastectomy (MRM)/mastectomy was done for 42 patients, 5 patients underwent lumpectomy limited to a single tumor, extended resection done for 14 patients, 5 underwent bilateral breast conservation surgery (BCS), BCS for contralateral breast done for 4 patients undergoing ipsilateral MRM/mastectomy, and bilateral MRM/mastectomies were performed for 2 patients. One patient was lost to follow up. Conclusion Breast MRI is the most sensitive modality for the assessment of breast cancer and plays an essential role in the detection of additional tumor foci. These findings can modify the surgical approach in these patients. However, considering the low specificity, biopsy of satellite masses is imperative to determine the most appropriate surgical plan.

Imaging Features of Breast Cancer Subtypes on Mammography and Ultrasonography: an Analysis of 479 Patients.

To compare features of clinically defined subtypes of breast cancer on mammography (MG) and ultrasonography (USG). After obtaining approval from the institute ethics committee, a retrospective observational study was performed on biopsy-proven breast cancer patients who underwent baseline MG from 2016 to 2020. MG and USG features were evaluated and the patients were classified based on immunohistochemistry profile into luminal like (LL)-oestrogen receptor (ER)/progesterone receptor (PR) + , Her2neu-; basal like (BL)-ER/PR-, Her2neu-; Her2 like (HL)-Her2neu + . A total of 479 patients (mean age, 51.4 ± 11.7years; all females) were included: LL-198 (41.3%), BL-121 (25.2%) and HL-160 (33.3%). On MG, round shape (21/115, 18.3%, p < 0.001); circumscribed (16/115, 13.9%, p < 0.001) and microlobulated margins (28/115, 24.4%) were associated with BL tumours. Associated suspicious calcifications (96/160, 60%, p < 0.001) and skin thickening or retraction (75/149, 50.3%, p < 0.001) were more common in HL. On USG, round shape (12/95, 12.8%, p = 0.005); circumscribed (8/94, 8.5%) and microlobulated margins (44/94, 46.8%) and posterior acoustic enhancement (7/95, 7.5%, p = 0.012) were associated with BL. The logistic regression analysis revealed that spiculated margins on MG favoured LL (OR: 8.5, p = 0.001); round shape (OR: 6.8), circumscribed (OR: 10.8) or microlobulated margins (OR: 3.5) (p < 0.001 for each) favoured BL; whereas associated features of calcifications (OR: 3.3) (p = 0.019) and skin retraction or thickening (OR: 1.8) (p < 0.001) favoured HL. On USG, circumscribed (OR: 5.9, p = 0.005) or microlobulated margins (OR: 3, p < 0.001) and posterior acoustic enhancement (OR: 9.5, p = 0.006) favoured BL. Clinically defined subtypes of breast cancer show significant differences in the imaging appearances on mammography and USG. BL tumours may not show the typical imaging features of malignancy, necessitating clinicopathological correlation for accurate diagnosis.

Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer.

Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting. We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), macroscopic fractional anisotropy (FA), and microscopic fractional anisotropy (µFA) were estimated. The parameter differences were compared between IDC and normal fibroglandular breast tissue (FGBT), as well as the association between the diffusion parameters and histopathologic items. The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 vs. 1.34±0.29, P<0.001); however, MKT, MKA, MKI, FA, and µFA were significantly higher (P<0.005). Among all the diffusion parameters, MKI was positively correlated with the tumor size on both MRI and pathological specimen (rs=0.38, P<0.05 vs. rs=0.54, P<0.01), whereas MKT had a positive correlation with the tumor size in the pathological specimen only (rs=0.47, P<0.02). In addition, the lymph node (LN) metastasis group had significantly higher MKT, MKA, and µFA compared to the metastasis negative group (P<0.05). Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy.

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

To evaluate whether contrast-enhanced cone-beam breast CT (CE-CBBCT) features can risk-stratify prognostic stage in breast cancer. 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. 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). CE-CBBCT imaging biomarkers may provide a large amount of anatomical and radiobiological information for the pre-operative distinction of prognostic stage. CE-CBBCT features have distinctive promise for stratification of prognostic stage in breast cancer.

Radiomic Analysis of Pharmacokinetic Heterogeneity Within Tumor Based on the Unsupervised Decomposition of Dynamic Contrast-Enhanced MRI for Predicting Histological Characteristics of Breast Cancer.

Breast tumor heterogeneity is associated with histological characteristics. However, pharmacokinetic (PK) heterogeneity within tumor might merit further exploration. To enhance the predictive power of molecular subtypes, Ki-67, and tumor grade by analyzing PK heterogeneity within tumor based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Retrospective. Two hundred and eight biopsy-proven breast cancer patients, randomly divided into a training cohort (N=144) and a testing cohort (N=64). T1 -weighted DCE-MRI at 3.0 T. A convex analysis of mixtures-compartmental modeling decomposition method was used to estimate the PK parameter (i.e., the volume transfer constant Ktrans ) in tumor subregions with distinct physiological kinetic patterns, including fast-flow kinetics, slow-flow kinetics, and plasma input. Radiomic features based on the PK parameter were calculated from each tumor subregion. The training cohort was used to build random forest classifiers based on the optimal features determined by the 5-fold cross-validation method. The performance was assessed on the testing cohort using the area under the receiver operating characteristic curve (AUC). The AUCs derived from the tumor subregion-based PK parameter were compared with those of the original images of the entire tumor using the DeLong test. A P-value of <0.05 was considered statistically significant. The tumor subregion-based PK parameter, which yielded the highest AUCs of 0.8782, 0.7568, 0.7019, 0.7963, 0.8080, and 0.7375 for luminal A, luminal B, basal-like, human epidermal growth factor receptor 2, Ki-67, and tumor grade, respectively, obtained better diagnostic performance than the original images in the entire tumor (highest AUCs=0.8612, 0.6191, 0.5593, 0.7704, 0.7494, and 0.6261, respectively). In particular, statistically significant improvement in the diagnostic performance was obtained for luminal B. Radiomic analysis of PK heterogeneity within tumor can enhance the predictive performance of radiomic models compared with that of the entire tumor. 4 TECHNICAL EFFICACY STAGE: 3.

Abstract PS3-01: Quantitative dynamic contrast-enhanced (DCE) MRI radiomic phenotypes for prediction of nodal and distal metastasis in breast cancer patients

Abstract Background and Purpose:Image-based tumor phenotypes by using computer extraction techniques have been studied for evaluation of breast cancer invasiveness, stage, lymph node involvement, molecular subtypes and genomics. In this project we aimed to investigate ability of computer-extracted breast MR imaging radiomic phenotypes to predict nodal and distant metastasis in breast cancer patients. MATERIALS AND METHODS:This retrospective IRB approved study included 416 biopsy proven breast cancer patients who had pretreatment DCE MRI in a single institution between 2014 and 2018. Patient’s demographic, clinical data, pathology at diagnosis and surgery, nodal and distant metastasis (M1) at follow up were documented. Using QuantX imaging software, the tumor volume of interest was automatically-segmented using the multiple dynamic phases of DCE MRI. A total of 33 radiomic features describing tumor phenotype were extracted from each tumor site. A linear discriminant analysis (LDA) as a classifier with nested feature selection 10-fold cross validation was used to build the radiomic signature for prediction of nodal and distant metastasis occurrence. Receiver operating characteristic (ROC) and precision-recall analyses were used to evaluate performance, with 95% confidence intervals from 1000 bootstraps, and Kaplan-Meier was used to calculate the progression-free survival estimates and associated hazard ratio at the median cutpoint of the probability of metastasis calculated by the LDA in the 10-fold cross-validation. RESULTS:The quantitative DCE MRI radiomic model was able to differentiate between breast cancer patients with and without distant metastatic disease at follow up with area under the ROC of 0.75 (95% CI 0.65; 0.82) and precision-recall curves 0.46 (0.33;0.69), hazard ratio at median cut point is 3.76 (2.27; 6.24), p&amp;lt;0.001. Volume, surface area, sphericity, margin, maximum uptake, and washout rate variation features played the most important role in differentiating between breast cancer patients with and without distant metastasis. The DCE radiomic model was able predict presence of ipsilateral nodal disease (≥1 positive lymph nodes) at surgery with AUC 0.66 (95% CI: 0.60; 0.71), ≥4 positive lymph nodes at surgery with AUC 0.67 (95% CI: 0.60; 0.74), and N2/N3 disease with AUC 0.64 (95% CI: 0.56; 0.72). Effective radius was most important feature for nodal disease prediction. CONCLUSIONS:Our results show that DCE MRI based radiomic phenotypes were able to predict nodal involvement and distant metastasis in breast cancer patients. Quantitative breast DCE MRI radiomics shows promise for noninvasive image based phenotyping for prediction of nodal and distant metastatic disease in breast cancer patients. Citation Format: Gaiane Margishvili Rauch, Karen Drukker, Nabil Elshafeey, Rania M.m. Mohamed, Medina Boge, Beatriz E. Adrada, Rosalind P Candelaria, Mo Salama, Irene Shkatova, Maryellen Giger, Wei T Yang. Quantitative dynamic contrast-enhanced (DCE) MRI radiomic phenotypes for prediction of nodal and distal metastasis in breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-01.

Study of breast cancer surgeries at a tertiary hospital

Background: Breast cancer is commonly treated by various combinations of surgery, chemotherapy, radiation therapy, hormone therapy and targeted therapy via a multimodality approach. Surgery is the mainstay of treatment of the early stages of breast cancer, and it ranges from lumpectomy to modified radical mastectomy. Surgery typically includes sentinel lymph nodes (LN) dissection for staging the extent of spread into the axilla. In present study we aimed to study surgeries done in patients with breast cancer at our tertiary hospital. Material and Methods: Present study was a prospective, observational study conducted in patients who underwent surgery for breast cancer, followed by histopathological report positive for breast malignancy. Results: Total 86 biopsy proven breast cancer patients underwent surgery during study period. All patients were females, with mean age 47.4 ± 10.7 years, from rural areas (74%), 9% had positive family history, 13% received Hormone Replacement Therapy/Oral Contraceptive Pills (for more than 5 years), 5% were smokers, 64% were premenopausal and 7% had history of breast biopsy. Modified radical mastectomy with axillary node dissection (69%) was most common surgery performed followed by breast conservation surgery (26%). Most patients were from stage II (64%) followed by stage I (15%). Infiltrating ductal carcinoma was most common histopathological variant (81%). Histopathologically most cancers were grade II (52%). Lymph nodal involvement (48%) and positive surgical margins (7%) were noted. Conclusion: Surgery is mainstay in treatment of breast cancer With introduction of BCS cosmetic and other concerns are tackled effectively.

The Impact of Tumor Volume in Breast Cancer Liver Metastasis Patients Treated with Stereotactic Radiotherapy – Does Size Matter?

To investigate the relationship between tumor volume and survival in breast cancer liver metastasis (BCLM) patients treated with stereotactic radiotherapy. 39 biopsy proven breast cancer patients whom liver metastasis was treated with stereotactic radiotherapy (SRT) were retrospectively investigated. Patient characteristics, survival and their relation with tumor volume were analyzed. Median age was 47 years (range; 27-78 years). Median tumor size was 1.8 ± 1.1 cm. Median gross tumor volume (GTV) and planning tumor volume (PTV) were 6.8 cc (range, 0.7-55.2 cc) and 38.7 cc (range; 9.3-163.8 cc), respectively. SRT dose prescription was 3 fr x 18 Gy in 37 patients (96%), 3 fr x 20 Gy in 1 patient (2%) and 3 fr x 16 Gy in 1 patient (2%). 13 patients (33%) had solitary liver metastasis while 26 patients (67%) also had other organ metastases beyond liver. Median follow-up for entire cohort was 15.4 months (range; 1-49 months). At last visit 26 patients (67%) had disease progression. Among these patients 25 patients (64%) had distant metastasis while 2 patients (5%) had isolated local recurrence. The 1- and 2- years overall survival (OS) rates were %79.1 and %46.0, respectively. Median OS was 23.8 months (95% CI: 13.3-34.3 months). 1 and 2-years progression-free survival (PFS) rates were 38.1% and 11.5%, respectively. Median PFS was 8.7 months (95%CI: 5.6-11.8 months). 1 and 2-years of local control (LC) per tumor were 92.9% and 85%, respectively. Patients were divided into two groups according to tumor volume £30 cc or >30 cc. 1-year OS was 100% for patients with tumor volume £30 cc while 1-year OS was 34% for patients with tumor volume > 30 cc (p = 0.04). 4 patients developed grad 3 late toxicity. Among them 1 had duodenal ulcer, received medical treatment without any surgical intervention and 3 of them had rib fracture treated with symptomatic medical treatment. SRT is an efficient treatment with optimal LC and low toxicity profile in BCLM patients. Tumor volume of £30 cc had better survival.

Evaluation of estrogen expression of breast cancer using 18F-FES PET CT-A novel technique.

Estrogen receptor (ER) expression in breast cancer is routinely studied on immunohistochemistry (IHC) of tissue obtained from core biopsy or surgical specimen. Sampling error and heterogeneity of tumor may incorrectly label a breast tumor as ER negative, thus denying patient hormonal treatment. Molecular functional ER imaging can assess the in-vivo ER expression of primary tumor and metastases at sites inaccessible for biopsy and also track changes in expression over time. The aim was to study ER expression using 16α-18F-fluoro-17β-estradiol or 18F-fluoroestradiol (18F FES) positron emission tomography (PET) computed tomography (CT). Twenty-four biopsy-proven breast cancer patients consenting to participate in the study underwent FES PET CT. Standard uptake value (SUVmean) of maximum of 7 lesions/patient was analyzed, and tumor-to-background ratio was calculated for each lesion. Visual interpretation score was calculated for lesion on FES PET and correlated with the Allred score on IHC of tumor tissue samples for ER expression. The diagnostic indices of FES PET CT were assessed taking IHC as “gold standard.” On FES PET CT, the mean SUV for ER+ tumors was 4.75, whereas the mean SUV for ER − tumors was 1.41. Using receiver operating characteristic curve, tumors with an SUV of ≥ 1.8 on FES PET could be considered as ER+. The overall accuracy of FES PET CT to detect ER expression was 91.66%, with two false negatives noted in this study. 18F-FES PET CT appears promising in evaluating ER expression in breast cancer. It is noninvasive and has potential to assess the in-vivo ER expression of the entire primary tumor and metastasis not amenable for biopsy.

Breast cancer care in northern Ethiopia \u2013 cross-sectional analysis

BackgroundIn Ethiopia, the incidence of new cases of breast cancer is currently increasing resulting to high rates of morbidity and mortality. Breast cancer is by far the most common cancer accounting for more than one out of three cancer cases in women and one out of every five in the general population. The study was conducted in University of Gondar Hospital cancer center, located in the North-West Ethiopia; to evaluate the clino-pathologic characteristics of breast cancer and care provided for patients.MethodsAll biopsy proven breast cancer patients treated between 2016 and 2017, were identified and information regarding histology, stage, therapeutic procedure and follow up was retrospectively collected from their individual medical records and descriptive analysis was done.ResultsAmong 82 patients treated, 67 (82%) were women and 15 (18%) were men. The median age at the time of diagnosis was 45 years (25–82 years). Operation was performed for 56 (68%) patients. The predominant histology was ductal carcinoma in 61 patients (74%), followed by breast carcinoma of No Special Type (NST) in 17 (21%). The late presentation of the patients and the advanced stage at the time of presentation was observed in most of the patients. Chemotherapy was administered in 79 (96%) patients. Radiotherapy was not available in the hospital.ConclusionBreast cancer incidence is rising and becoming a major public health problem in Northern Ethiopia. Breast cancer care in northern-Ethiopia is limited in terms of both pathology, imaging and the offered treatment modalities, which need to be improved.

Is Background Parenchymal Enhancement on Magnetic Resonance Imaging Helpful in Risk Assessment of Breast Cancer?

Objectives: Background parenchymal enhancement (BPE) on contrast-enhanced magnetic resonance imaging (CE-MRI) corresponds to hormonally active breast fibroglandular tissue. Several studi.es have reported increased odds of breast cancer in patients with marked BPE. The purpose of the present study was to evaluate BPE in contralateral breast of biopsy proven breast cancer patients and comparison of the results with control group. Methods: In a case-control study, CE-MRI of the contralateral breasts of 40 biopsy-proven breast cancer patients and 40 patients with biopsy- proven benign breast lesions, were retrospectively reviewed by an experienced radiologist and degree of BPE, and pattern of enhancement were determined, finally, BPE was compared between case and control groups using chi square test. Pearson correlation test was used to determine association between FGT amount and BPE. P value < 0.05 was considered significant. Results: In the case group, 4, 17, 14, and 5 patients had minimal, mild, moderate, and marked BPE, respectively. In the control group, 12, 24, .and 4 participants had minimal, mild, and moderate BPE, respectively. BPE was significantly higher in the case group in comparison with the control group (P value < 0.05). Patients with invasive carcinoma had significantly higher BPE in comparison with the patients with carcinoma in situ. (P value < 0.05) There was a moderate correlation (r = 0.4, P value < 0.05) between FGT amount and degree of BPE. In the case group, 3, 26, and 11 patients had mass-non mass, mass, and non mass pattern of enhancement, respectively. In the control group, 25, antl15 participants had mass, and non mass pattern of enhancement, respectively. Pattern of enhancement was not significantly different between the two groups. Conclusions: Our study revealed that patients with the diagnosis of breast cancer have greater BPE in comparison with control group. The results may be indicative for higher probability of developing breast cancer in patients with higher BPE. Therefore, CE-MRI could be a useful tool for breast cancer risk assessment.

Serum butyrylcholinesterase and zinc in breast cancer.

Even though, a large number of serological, molecular markers have been proposed for breast cancer screening, most of them lack specificity, sensitivity, prognostic value, and cost effectiveness. Butyrylcholinesterase (BChE) and its genes are aberrantly expressed in a variety of human cancers. It has-been linked to tumorigenesis, cell proliferation, and cell differentiation. Zinc (Zn) is a cofactor for superoxide dismutase, an enzyme that protects cellular components against free radical-induced damage and carcinogenesis. Therefore, the aim of present study was to estimate and compare serum BChE and serum Zn levels in healthy controls and biopsy proven breast cancer patients before definitive therapy. To estimate and compare serum BChE and serum Zn levels in healthy controls and biopsy proven breast cancer patients before definitive therapy. Serum BChE and Zn were estimated in 46 newly diagnosed (preoperative) female patients with breast cancer and 50 healthy female volunteers. Serum BChE and Zn were estimated by spectrophotometric method. Data was expressed as median and inter quartile range. Comparisons between different stages of cancer were done using Kruskal-Wallis test. There was a significant increase in serum BChE and Zn in breast cancer patients compared to controls (P < 0.001). Serum BChE showed a significant increase and Zn was significantly decreased in different stages of breast cancer. Both BChE and Zn are inexpensive and can easily be analyzed and may play a role in the management of breast cancer.