Characterization and classification of ductal carcinoma tissue using four channel based stokes-mueller polarimetry and machine learning.

Interaction of polarized light with healthy and abnormal regions of tissue reveals structural information associated with its pathological condition. Even a slight variation in structural alignment can induce a change in polarization property, which can play a crucial role in the early detection of abnormal tissue morphology. We propose a transmission-based Stokes-Mueller microscope for quantitative analysis of the microstructural properties of the tissue specimen. The Stokes-Mueller based polarization microscopy provides significant structural information of tissue through various polarization parameters such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP), anisotropy (r) and Mueller decomposition parameters such as diattenuation, retardance and depolarization. Further, by applying a suitable image processing technique such as Machine learning (ML) output images were analysed effectively. The support vector machine image classification model achieved 95.78% validation accuracy and 94.81% testing accuracy with polarization parameter dataset. The study's findings demonstrate the potential of Stokes-Mueller polarimetry in tissue characterization and diagnosis, providing a valuable tool for biomedical applications.

Intra and peritumoral PET radiomics analysis to predict the pathological response in breast cancer patients receiving neoadjuvant chemotherapy.

OBJECTIVE: The aim of our study was to evaluate the contribution of 18Fluorine-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) radiomic data obtained from both the tumoral and peritumoral area in predicting pathological complete response (pCR) in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC). METHODS: Female patients with a diagnosis of invasive ductal carcinoma who received NAC were evaluated retrospectively. The volume of interest (VOI) of the primary tumor (VOI-T) was manually segmented, then a voxel-thick VOI was added around VOI-T to define the peritumoral area (VOI-PT). Morphological, intensity-based, histogram and texture parameters were obtained from VOIs. The patients were divided into two groups as pCR and non-complete pathological response (npCR). A "radiomic model" was created with only radiomic features, and a "patho-radiomic model" was created using radiomic features and immunohistochemical data. RESULTS: Of the 66 patients included in the study, 21 were in the pCR group. The only statistically significant feature from the primary tumor among patients with pCR and npCR was Morphological_Compacity-T (AUC: 0.666). Between response groups, a significant difference was detected in 2 morphological, 1 intensity, 4 texture features from VOI-PT; no correlation was found between Morphological_Compacity-PT and NGTDM_contrast-PT. The obtained radiomic model's sensitivity and accuracy values were calculated as 61.9% and 75.8%, respectively (AUC: 0.786). When HER2 status was added, sensitivity and accuracy values of the patho-radiomic model increased to 85.7% and 81.8%, respectively (AUC: 0.903). CONCLUSIONS: Evaluation of PET peritumoral radiomic features together with the primary tumor, rather than just the primary tumor, provides a better prediction of the pCR to NAC in patients with breast cancer.

Value of magnetic resonance imaging radiomics features in predicting histologic grade of invasive ductal carcinoma of the breast.

BACKGROUND: Breast cancer has the second highest mortality rate of all cancers and occurs mainly in women. OBJECTIVE: To investigate the relationship between magnetic resonance imaging (MRI) radiomics features and histological grade of invasive ductal carcinoma (IDC) of the breast and to evaluate its diagnostic efficacy. METHODS: The two conventional MRI quantitative indicators, i.e. the apparent diffusion coefficient (ADC) and the initial enhancement rate, were collected from 112 patients with breast cancer. The breast cancer lesions were manually segmented in dynamic contrast-enhanced MRI (DCE-MRI) and ADC images, the differences in radiomics features between Grades I, II and III IDCs were compared and the diagnostic efficacy was evaluated. RESULTS: The ADC values (0.77 ± 0.22 vs 0.91 ± 0.22 vs 0.92 ± 0.20, F= 4.204, p< 0.01), as well as the B_sum_variance (188.51 ± 67.803 vs 265.37 ± 77.86 vs 263.74 ± 82.58, F= 6.040, p< 0.01), L_energy (0.03 ± 0.02 vs 0.13 ± 0.11 vs 0.12 ± 0.14, F= 7.118, p< 0.01) and L_sum_average (0.78 ± 0.32 vs 16.34 ± 4.23 vs 015.45 ± 3.74, F= 21.860, p< 0.001) values of patients with Grade III IDC were significantly lower than those of patients with Grades I and II IDC. The B_uniform (0.15 ± 0.12 vs 0.11 ± 0.04 vs 0.12 ± 0.03, F= 3.797, p< 0.01) and L_SRE (0.85 ± 0.07 vs 0.78 ± 0.03 vs 0.79 ± 0.32, F= 3.024, p< 0.01) values of patients with Grade III IDC were significantly higher than those of patients with Grades I and II IDC. All differences were statistically significant (p< 0.05). The ADC radiomics signature model had a higher area-under-the-curve value in identifying different grades of IDC than the ADC value model and the DCE radiomics signature model (0.869 vs 0.711 vs 0.682). The accuracy (0.812 vs 0.647 vs 0.710), specificity (0.731 vs 0.435 vs 0.342), positive predictive value (0.815 vs 0.663 vs 0.669) and negative predictive value (0.753 vs 0.570 vs 0.718) of the ADC radiomics signature model were all significantly better than the ADC value model and the DCE radiomics signature model. CONCLUSION: ADC values and breast MRI radiomics signatures are significant in identifying the histological grades of IDC, with the ADC radiomics signatures having greater value.

Could breast multiparametric MRI discriminate between pure ductal carcinoma in situ and microinvasive carcinoma?

BACKGROUND: Ductal carcinoma in situ (DCIS) is often reclassified as invasive cancer in the final pathology report of the surgical specimen. It is of significant clinical relevance to acknowledge the possibility of underestimating invasive disease when utilizing preoperative biopsies for a DCIS diagnosis. In cases where such histologic upgrades occur, it is imperative to consider them in the preoperative planning process, including the potential inclusion of sentinel lymph node biopsy due to the risk of axillary lymph node metastasis. PURPOSE: To assess the capability of breast multiparametric magnetic resonance imaging (MP-MRI) in differentiating between pure DCIS and microinvasive carcinoma (MIC). MATERIAL AND METHODS: Between January 2018 and November 2022, this retrospective study enrolled patients with biopsy-proven DCIS who had undergone preoperative breast MP-MRI. We assessed various MP-MRI features, including size, morphology, margins, internal enhancement pattern, extent of disease, presence of peritumoral edema, time-intensity curve value, diffusion restriction, and ADC value. Subsequently, a logistic regression analysis was conducted to explore the association of these features with the pathological outcome. RESULTS: Of 129 patients with biopsy-proven DCIS, 36 had foci of micro-infiltration on surgical specimens and eight were diagnosed with invasive ductal carcinoma (IDC). The presence of micro-infiltration foci was significantly associated with several MP-MRI features, including tumor size (P <0.001), clustered ring enhancement (P <0.001), segmental distribution (P <0.001), diffusion restriction (P = 0.005), and ADC values <1.3 × 10-3 mm2/s (P = 0.004). CONCLUSION: Breast MP-MRI has the potential to predict the presence of micro-infiltration foci in biopsy-proven DCIS and may serve as a valuable tool for guiding therapeutic planning.

The Effect of Intraoperative Margin Assessment During Breast Conserving Surgery for Breast Cancer in a Dutch Cohort.

INTRODUCTION: Intraoperative specimen radiography is a routinely used procedure to ensure adequate resection of non-palpable breast tumors. Intraoperative digital specimen mammography (IDSM) is an alternative to conventional specimen radiography (CSR) which provides immediate specimen evaluation and can potentially decrease operation time. IDSM may also result in lower positive margin and re-excision rates. IDSM was implemented in our hospital in 2018. The objective of this study was to evaluate the effect of using IDSM versus CSR on operation time, margin status and re-excision rates in breast conserving surgery. METHODS: The present study is a single-center retrospective cohort study with 2 patient cohorts: one which underwent CSR (n = 532) and one which underwent IDSM (n = 475). The primary outcome was the operation time. Secondary outcomes were the margin status of the primary surgery, the cavity shaving rate, and the re-excision rate. Differences between cohorts were compared using univariate statistics and multiple regression analyses to adjust for variables that were significantly different between the groups. RESULTS: IDSM use was associated with an 8-minute reduction in surgery time (B = -8.034, 95% CI [-11.6, -4.5]; P < .001). Treatment variables independently associated with the operation time included use of IDSM, type of surgery, and performance of cavity shaving. Cavity shaves were more often performed when IDSM was used (24% for IDSM vs. 14% for CSR, P < .001), while the proportion of negative margin rates (93% for IDSM vs. 96% for CSR, P = .070) was comparable. CONCLUSION: IDSM was associated with a modest reduction in operation time. Surgeons performed more cavity shaves since the introduction of IDSM, but this increase was not reflected by difference in negative margin rates.

Perioperative care of nipple-areola complex-sparing mastectomy and one-stage breast reconstruction via endoscopic axillary approach for ductal carcinoma in situ: A case report.

RATIONALE: Breast cancer represents a prevalent malignancy that primarily impacts women, with pronounced consequences on their overarching health. The major therapeutic approach, encompassing surgical procedures, can often culminate in mastectomy, potentially inciting psychological turmoil and disorders. PATIENT CONCERNS: A patient was admitted to our facility on May 5, 2023, precipitated by the discovery of bilateral breast masses during a routine physical examination conducted 3 days before admission. DIAGNOSIS: The breasts were symmetric, with the right nipple inverted and a palpable mass in the upper outer quadrant of the right breast, measuring approximately 5 cm × 4 cm. The mass was firm with indistinct borders, relatively regular morphology, poor mobility, and no tenderness. Outpatient color Doppler ultrasound revealed heterogeneous echogenicity in the right breast, classified as Breast Imaging Reporting and Data System (BI-RADS) category 0, along with multiple ductal dilatations. The left breast exhibited a hypoechoic area (BI-RADS 3), indicative of proliferative changes. Radiographic mammography confirmed diffuse changes in the right breast (BI-RADS 0) and proliferative signs in the left breast (BI-RADS 2). Biopsy results reveal significant atypical ductal hyperplasia consistent with intermediate-grade ductal carcinoma in situ. This patient was diagnosed as ductal carcinoma in situ of the right breast (cTisN0M0 and Stage 0), accompanied by a left breast mass. INTERVENTIONS: On May 15, 2023, the patient was readmitted for further surgical intervention. Following relevant auxiliary examinations, the patient underwent nipple-areola complex-sparing radical mastectomy for the right breast, sentinel lymph node biopsy in the right axillary area, prosthesis-based breast reconstruction for the right breast, and microrotatotomy of the left breast mass on the left side on May 17. OUTCOMES: The patient made a successful recovery under scrupulous perioperative supervision and was discharged 7 days post-surgery. LESSONS: The axillary approach for endoscopic mammary gland excision and immediate implant reconstruction permits patients to preserve the esthetics of the female form while undergoing conventional medical treatment. This methodology considerably enhances the psychophysical health of the patients, thereby marking it as an advantageous practice worthy of broad dissemination in the medical community.

Digital mammography and digital breast tomosynthesis for detecting invasive lobular and ductal carcinoma.

PURPOSE: Invasive lobular carcinoma (ILC) is a distinct histological subtype of breast cancer that can make early detection with mammography challenging. We compared imaging performance of digital breast tomosynthesis (DBT) to digital mammography (DM) for diagnoses of ILC, invasive ductal carcinoma (IDC), and invasive mixed carcinoma (IMC) in a screening population. METHODS: We included screening exams (DM; n = 1,715,249 or DBT; n = 414,793) from 2011 to 2018 among 839,801 women in the Breast Cancer Surveillance Consortium. Examinations were followed for one year to ascertain incident ILC, IDC, or IMC. We measured cancer detection rate (CDR) and interval invasive cancer rate/1000 screening examinations for each histological subtype and stratified by breast density and modality. We calculated relative risk (RR) for DM vs. DBT using log-binomial models to adjust for the propensity of receiving DBT vs. DM. RESULTS: Unadjusted CDR per 1000 mammograms of ILC overall was 0.33 (95%CI: 0.30-0.36) for DM; 0.45 (95%CI: 0.39-0.52) for DBT, and for women with dense breasts- 0.33 (95%CI: 0.29-0.37) for DM and 0.54 (95%CI: 0.43-0.66) for DBT. Similar results were noted for IDC and IMC. Adjusted models showed a significantly increased RR for cancer detection with DBT compared to DM among women with dense breasts for all three histologies (RR; 95%CI: ILC 1.53; 1.09-2.14, IDC 1.21; 1.02-1.44, IMC 1.76; 1.30-2.38), but no significant increase among women with non-dense breasts. CONCLUSION: DBT was associated with higher CDR for ILC, IDC, and IMC for women with dense breasts. Early detection of ILC with DBT may improve outcomes for this distinct clinical entity.

Prediction of coexisting invasive carcinoma on ductal carcinoma in situ (DCIS) lesions by mass spectrometry imaging.

Due to limited biopsy samples, ~20% of DCIS lesions confirmed by biopsy are upgraded to invasive ductal carcinoma (IDC) upon surgical resection. Avoiding underestimation of IDC when diagnosing DCIS has become an urgent challenge in an era discouraging overtreatment of DCIS. In this study, the metabolic profiles of 284 fresh frozen breast samples, including tumor tissues and adjacent benign tissues (ABTs) and distant surrounding tissues (DSTs), were analyzed using desorption electrospray ionization-mass spectrometry (DESI-MS) imaging. Metabolomics analysis using DESI-MS data revealed significant differences in metabolite levels, including small-molecule antioxidants, long-chain polyunsaturated fatty acids (PUFAs) and phospholipids between pure DCIS and IDC. However, the metabolic profile in DCIS with invasive carcinoma components clearly shifts to be closer to adjacent IDC components. For instance, DCIS with invasive carcinoma components showed lower levels of antioxidants and higher levels of free fatty acids compared to pure DCIS. Furthermore, the accumulation of long-chain PUFAs and the phosphatidylinositols (PIs) containing PUFA residues may also be associated with the progression of DCIS. These distinctive metabolic characteristics may offer valuable indications for investigating the malignant potential of DCIS. By combining DESI-MS data with machine learning (ML) methods, various breast lesions were discriminated. Importantly, the pure DCIS components were successfully distinguished from the DCIS components in samples with invasion in postoperative specimens by a Lasso prediction model, achieving an AUC value of 0.851. In addition, pixel-level prediction based on DESI-MS data enabled automatic visualization of tissue properties across whole tissue sections. Summarily, DESI-MS imaging on histopathological sections can provide abundant metabolic information about breast lesions. By analyzing the spatial metabolic characteristics in tissue sections, this technology has the potential to facilitate accurate diagnosis and individualized treatment of DCIS by inferring the presence of IDC components surrounding DCIS lesions. © 2023 The Pathological Society of Great Britain and Ireland.

Effectiveness of Carbon Localization for Invasive Breast Cancer: An Institutional Experience.

Introduction: The final oncological and aesthetic results of breast-conserving surgery (BCS) are influenced by the precise localization of breast cancer (BC) tumors and by the quality of the intraoperative margin assessment technique. This study aimed to assess the effectiveness of the carbon localization (CL) technique by determining the success rate of BC identification and the proportion of adequate complete resection of BC lesions. Methods: We conducted a cross-sectional retrospective study of patients treated with primary BCS for invasive BC who underwent CL of their BC lesion at the Jules Bordet Institute between January 2015 and December 2017. Descriptive statistics with categorical and continuous variables were used. The success rate of tumor identification and the rate of adequate excision were calculated using the test of percentages for independent dichotomous data. Results: This study included 542 patients with 564 nonpalpable BC lesions. The median pathological tumor size was 12 mm. Of these, 460 were invasive ductal carcinomas. Most of the tumors were of the luminal subtype. CL was performed using ultrasound guidance in 98.5% of cases. The median delay between CL and surgery was 5 days, with 46% of the patients having CL one day before surgery. The lumpectomy weighed 38 g on average, with a median diameter of the surgical sample at 6 cm and a median volume of 44 cm3 (6-369). One-stage complete resection was successfully performed in 93.4% of cases. In 36% of cases, an intraoperative re-excision was performed, based on intraoperative macroscopic pathological margin evaluation. The tumor was identified in 98.9% of cases in the breast surgical specimen. Conclusion: This study demonstrated high success rates for BC tumor identification (99%) and one-stage complete resection (93.4%) after BCS and CL. These results show that CL is an effective, simple, and inexpensive localization technique for successful excision of BC lesions during BCS.

Prediction of nipple involvement in breast cancer after neoadjuvant chemotherapy: Should we rely on breast MRI to preserve the nipple?

BACKGROUND: Indications for nipple sparing mastectomy (NSM) is extending to post-neoadjuvant chemotherapy (NAC) setting. Eligibility for NSM with an optimum tumor-nipple distance (TND) after NAC is unclear. We examined predictive factors for nipple tumor involvement in patients undergoing total mastectomy following NAC. METHODS: Clinical and pathological data from prospectively collected medical records of women with invasive breast carcinoma, who were undergone NAC and total mastectomy with sentinel lymph node biopsy and/or axillary lymph node dissection were analyzed. PreNAC and postNAC magnetic resonance imaging (MRI) views were examined and a cut-off TND value for predicting the negative nipple tumor status was determined. RESULTS: Among 180 women, the final mastectomy specimen analysis revealed that 12 (7%) had nipple involvement as invasive carcinoma. Patients with nipple involvement had more postNAC multifocal/multicentric tumors (p: 0.03), larger tumors on preNAC and postNAC images (p: 0.002 and p < 0.001), shorter median TNDs on preNAC and postNAC images (7 mm-IQR 1.5-14, p: 0.005 and 8.5 mm-IQR 3-15.5, p < 0.001, respectively), more nipple retraction on preNAC and postNAC images (p: 0.007 and p: 0.006) and more nipple areola complex skin thickening (> 2mm) on preNAC and postNAC images (p < 0.001 and p: 0.01). The best likelihood ratios (LR) belonged to the postNAC positivity of the < 20 mm TND, with a + LR of 3.40, and - LR of 0.11 for nipple involvement. PreNAC positivity of the < 20 mm TND also had a similar - LR of 0.14. CONCLUSION: A TND-cut-off  ≥ 2 cm on preNAC and postNAC MRI was shown to be highly predictive of negative nipple tumor involvement.

Does Preoperative MRI Reduce Positive Margins after Breast-Conserving Surgery?

BACKGROUND: Breast-conserving surgery (BCS) is a mainstay for breast cancer management, and obtaining negative margins is critical. Some have advocated for the use of preoperative magnetic resonance imaging (MRI) in reducing positive margins after BCS. We sought to determine whether preoperative MRI was associated with reduced positive margins. PATIENTS AND METHODS: The SHAVE/SHAVE2 trials were multicenter trials in ten US centers with patients with stage 0-3 breast cancer undergoing BCS. Use of preoperative MRI was at the discretion of the surgeon. We evaluated whether or not preoperative MRI was associated with margin status prior to randomization regarding resection of cavity with shave margins. RESULTS: A total of 631 patients participated. Median age was 64 (range 29-94) years, with a median tumor size of 1.3 cm (range 0.1-9.3 cm). Patient factors included 26.1% of patients (165) had palpable tumors, and 6.5% (41) received neoadjuvant chemotherapy. Tumor factors were notable for invasive lobular histology in 7.0% (44) and extensive intraductal component (EIC) in 32.8% (207). A preoperative MRI was performed in 193 (30.6%) patients. Those who underwent preoperative MRI were less likely to have a positive margin (31.1% versus 38.8%), although this difference was not statistically significant (p = 0.073). On multivariate analysis, controlling for patient and tumor factors, utilization of preoperative MRI was not a significant factor in predicting margin status (p = 0.110). Rather, age (p = 0.032) and tumor size (p = 0.040) were the only factors associated with margin status. CONCLUSION: These data suggest that preoperative MRI is not associated margin status; rather, patient age and tumor size are the associated factors.

Recurrence Network Analysis of Histopathological Images for the Detection of Invasive Ductal Carcinoma in Breast Cancer.

The histopathological image analysis is one of the most crucial diagnostic procedures to identify Invasive ductal carcinoma (IDC) in breast cancers. However, this diagnosis process is currently time-consuming and heavily dependent on human expertise. Prior research has shown that different degrees of tumors present various microstructures in the histopathological images. However, very little has been done to utilize spatial recurrence features of microstructures for identifying IDC. This paper presents a novel recurrence analysis methodology for automatic image-guided IDC detection. We first utilize wavelet decomposition to delineate the subtle information in the images. Then, we model the patches with a weighted recurrence network approach to characterize the recurrence patterns of the histopathological images. Finally, we develop automated IDC detection models leveraging machine learning methods with spatial recurrence features extracted. The developed recurrence analysis models successfully characterize the complex microstructures of histopathological images and achieve the IDC detection performances of at least AUC = 0.96. This research developed a spatial recurrence analysis methodology to effectively identify IDC regions in histopathological images for BC. It shows a high potential to assist physicians in the decision-making process. The proposed methodology can further be applicable to image processing for other medical or biological applications.

Computer Vision Identifies Recurrent and Nonrecurrent Ductal Carcinoma in Situ Lesions with Special Emphasis on African-American Women.

Although nonrecurrent and recurrent forms of ductal carcinoma in situ (DCIS) of the breast are observed, no evidence-based test can make this distinction. The current retrospective case-control study used archival DCIS samples stained with anti-phospho-Ser226-glucose transporter type 1 and anti-phosphofructokinase type L antibodies. Immunofluorescence micrographs were used to create machine learning models of recurrent and nonrecurrent biomarker patterns, which were evaluated in cross-validation studies. Clinical performance was assessed by holdout studies using patients whose data were not used in training. Micrographs were stratified according to the recurrence probability of each image. Recurrent patients were defined by at least one image with a probability of recurrence ≥98%, whereas nonrecurrent patients had none. These studies found no false-negatives, identified true-positives, and uniquely identified true-negatives. Roughly 20% of the microscope fields of recurrent lesions were computationally recurrent. Strong prognostic results were obtained for both white and African-American women. This machine tool provides the first means to accurately predict recurrent and nonrecurrent patient outcomes. Data indicate that at least some false-positive findings were true-positive findings that benefited from surgical intervention. The intracellular locations of phospho-Ser226-glucose transporter type 1 and phosphofructokinase type L likely participate in cancer recurrences by accelerating glucose flux, a key feature of the Warburg effect.

Pathologic Tumor Size versus Mammography, Sonography, and MRI in Breast Cancer Based on Pathologic Subtypes.

INTRODUCTION: The standard of care for imaging of breast pathology has historically been mammography and sonography. MRI is a modern adjunct in the surgeon's toolkit. We looked to examine the differences in imaging modalities and their ability to predict the size in relation to the pathologic size after excision with focus on pathologic subtypes. METHODS: We analyzed patient records across a 4-year period from 2017 to 2021 who were treated surgically for breast cancer at our facility. We used a retrospective chart review to collect measurements that were recorded of the tumors by the radiologist for available mammography, ultrasound, and MRI which were compared to pathology report measurements of the final specimens. We subdivided the results by pathologic subtypes including invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and ductal carcinoma in situ (DCIS). RESULTS: 658 total patients met criteria for analysis. Mammography overestimated specimens with DCIS by 1.93 mm (P = .15), US underestimated by .56 (.55), and MRI overestimated by 5.77 mm (P < .01). There was no statistically significant difference in any modalities with IDC. With specimens of ILC, all 3 imaging modalities underestimated tumor size, with only US being significant. DISCUSSION: Mammography and MRI consistently overestimated tumor size with the exception of ILC while US underestimated tumor size on all pathologic subtypes. MRI significantly overestimated tumor size in DCIS by 5.77 mm. Mammography was the most accurate imaging modality for all pathologic subtypes and never had a statistically significant difference from actual tumor size.

Feasibility of Quantitative MRI Using 3D-QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast.

BACKGROUND: Two-dimensional synthetic MRI of the breast has limited spatial coverage. Three-dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast. PURPOSE: To evaluate the feasibility of 3D synthetic MRI using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki-67 expression in IDC. STUDY TYPE: Prospective observational study. POPULATION: A total of 33 females with IDC of the breast (mean, 52.3 years). FIELD STRENGTH/SEQUENCE: A 3-T, 3D-QALAS gradient-echo and fat-suppressed T1-weighted 3D fast spoiled gradient-echo sequences. ASSESSMENT: Two radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1-weighted images acquired from 3D-QALAS. The mean T1 and T2 were measured for each IDC. STATISTICAL TESTS: Intraclass correlation coefficient for assessing interobserver agreement. Mann-Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant. RESULTS: The interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR-positive and HR-negative lesions, while the mean T2 value differed between HR-positive and HR-negative lesions, between the triple-negative and HR-positive or HER2-positive lesions, and between the Ki-67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR-negative IDC than in HR-positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple-negative status, and Ki-67 level. DATA CONCLUSION: 3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.

Predicting Upgrade of Ductal Carcinoma In Situ to Invasive Breast Cancer at Surgery With Ultrafast Imaging.

BACKGROUND. Biopsy-proven ductal carcinoma in situ (DCIS) lesions are often upgraded to invasive cancer at surgery. Therefore, accurate prediction of the likelihood of invasion is helpful for surgical planning, including the need for sentinel lymph node biopsy (SLNB). OBJECTIVE. The purpose of the present study was to investigate whether kinetic features of clinically available ultrafast MRI (UF-MRI) can predict upgrade of biopsy-proven DCIS to invasive cancer at surgical excision. METHODS. Consecutive patients with biopsy-proven pure DCIS lesions who underwent UF-MRI with conventional dynamic contrast-enhanced MRI (DCE-MRI) and subsequently underwent surgery between August 2019 and January 2021 were identified. Patient and lesion characteristics, biopsy method and pathology, and lesion features on mammography, ultrasound, DCE-MRI, and UF-MRI were assessed to determine predictors of upgrade to invasive cancer. The Fisher exact test and Kruskal-Wallis test were used for association analysis. RESULTS. In 68 patients (median age, 52.0 years; range, 31-79 years) with 68 biopsy-proven pure DCIS lesions, 26 lesions (38%) were upgraded from in situ to invasive cancer. An upgrade of DCIS to invasive cancer was significantly associated with a shorter time to enhancement (TTE) on preoperative UF-MRI (p = .03), with a threshold of 11 seconds providing maximum specificity (50%) and sensitivity (76%) for upgrade. Larger lesion size on DCE-MRI (p = .001) and mammography (p = .04) was also significantly associated with upgrade; an optimal predictive threshold of 4.4 cm on DCE-MRI yielded sensitivity of 88% and specificity of 56%. No other specific variables were significantly associated with upgrade after surgery. Logistic regression of selected features combined with TTE produced a higher AUC (0.85) in predicting upgrade to invasive disease than did each factor alone, but this result was not statistically significant. CONCLUSION. Preoperative UF-MRI TTE and lesion size on DCE-MRI and mammography show potential in predicting upgrade of DCIS to invasive cancer at surgery. CLINICAL IMPACT. UF-MRI provides useful information that can be used in surgical planning, including determination of the need to perform SLNB.

Imaging of lumpectomy surface with large field-of-view confocal laser scanning microscopy 'Histolog® scanner' for breast margin assessment in comparison with conventional specimen radiography.

PURPOSE: The Histolog® Scanner (SamanTree Medical SA, Lausanne, Switzerland) is a large field-of-view confocal laser scanning microscope designed to allow intraoperative margin assessment by the production of histological images ready for assessment in the operating room. We evaluated the feasibility and the performance of the Histolog® Scanner (HS) to correctly identify infiltrated margins in clinical practice of lumpectomy specimens. It was extrapolated if the utilization of the HS has the potential to reduce infiltrated margins and therefore reduce re-operation rates in patients undergoing breast conserving surgery (BCS) due to a primarily diagnosed breast cancer including ductal carcinoma in situ. METHODS: This is a single-center, prospective, non-interventional, diagnostic pilot study including 50 consecutive patients receiving BCS. The complete surface of the specimen was scanned using the HS intraoperatively. The surgery and the intraoperative margin assessment of the specimen was performed according to the clinical routine consisting of conventional specimen radiography as well as the clinical impression of the surgeon. Three surgeons and an experienced pathologist assessed the scans produced by the HS for cancer cells on the surface. The potential of the HS to correctly identify involved margins was compared to the results of the conventional specimen radiography alone as well as the clinical routine. The histopathological report served as the gold standard. RESULTS: 50 specimens corresponding to 300 surfaces were scanned by the HS. The mean sensitivity of the surgeons to identify involved margins with the HS was 37.5% ± 5.6%, the specificity was 75.2% ± 13.0%. The assessment of resection margins by the pathologist resulted in a sensitivity of 37.5% and a specificity of 81.0%, while the local clinical routine resulted in a sensitivity of 37.5% and a specificity of 78.2%. CONCLUSION: Acquisition of high-resolution histological images using the HS was feasible in clinical practice. Sensitivity and specificity were comparable to clinical routine. With more specific training and experience on image interpretation and acquisition, the HS may have the potential to enable more accuracy in the margin assessment of BCS specimens.

High rate of postoperative upstaging of ductal carcinoma in situ when prioritizing ultrasound evaluation of mammography-detected lesions: a single-center retrospective cohort study.

BACKGROUND: The initial diagnosis of ductal carcinoma in situ (DCIS) can be upstaged to invasive cancer after definitive surgery. This study aimed to identify risk factors for DCIS upstaging using routine breast ultrasonography and mammography (MG) and to propose a prediction model. METHODS: In this single-center retrospective study, patients initially diagnosed with DCIS (January 2016-December 2017) were enrolled (final sample size = 272 lesions). Diagnostic modalities included ultrasound-guided core needle biopsy (US-CNB), MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy. Breast ultrasonography was routinely performed for all patients. US-CNB was prioritized for lesions visible on ultrasound. Lesions initially diagnosed as DCIS on biopsy with a final diagnosis of invasive cancer at definitive surgery were defined as "upstaged." RESULTS: The postoperative upstaging rates were 70.5%, 9.7%, and 4.8% in the US-CNB, MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy groups, respectively. US-CNB, ultrasonographic lesion size, and high-grade DCIS were independent predictive factors for postoperative upstaging, which were used to construct a logistic regression model. Receiver operating characteristic analysis showed good internal validation (area under the curve = 0.88). CONCLUSIONS: Supplemental screening breast ultrasonography possibly contributes to lesion stratification. The low upstaging rate for ultrasound-invisible DCIS diagnosed by MG-guided procedures suggests that it is unnecessary to perform sentinel lymph node biopsy for lesions invisible on ultrasound. Case-by-case evaluation of DCIS detected by US-CNB can help surgeons determine if repeating biopsy with vacuum-assisted breast biopsy is necessary or if sentinel lymph node biopsy should accompany breast-preserving surgery. TRIAL REGISTRATION: This single-center retrospective cohort study was conducted with the approval of the institutional review board of our hospital (approval number 201610005RIND). As this was a retrospective review of clinical data, it was not registered prospectively.

Prediction of Clinical Molecular Typing of Breast Invasive Ductal Carcinoma Using 18F-FDG PET/CT Dual-Phase Imaging.

RATIONALE AND OBJECTIVES: To investigate the diagnostic value of Fluorine-18-labeled 2-fluoro-2-deoxy-D-glucose positron emission tomography and computed tomography (18F-FDG PET/CT) dual-phase imaging for the different molecular subtypes of invasive ductal carcinoma of the breast. MATERIALS AND METHODS: Clinical imaging data of 164 women with invasive ductal carcinoma of the breast confirmed by pathology who underwent 18F-FDG PET/CT dual-phase imaging were retrospectively analyzed. The maximum standard uptake values (SUVmax) of the early and delayed phases of the lesion were measured and recorded as SUVmax1 and SUVmax2, respectively, and the retention index (RI) was calculated. We analyzed the change rule of SUVmax1, SUVmax2, and RI for the different molecular subtypes and molecular marker expression groups. The diagnostic threshold of different molecular marker expression status was determined using receiver operating characteristic curve analysis. RESULTS: SUVmax1 and SUVmax2 were highest in the TNBC group and lowest in the luminal A group (p<0.001). TNBC and HER2 overexpression groups had higher RI than the luminal A and B groups (p<0.001), with no significant difference between the TNBC and HER2 overexpression groups or between the luminal A and B groups (p=0.640 and 0.345, respectively). The ER- and PR-negative groups had significantly higher SUVmax1, SUVmax2, and RI than the PR-positive group (p<0.001). The HER2-positive group had higher SUVmax1 and SUVmax2 than the negative group (p<0.001). The Ki67 overexpression group had higher SUVmax1 and SUVmax2 levels than the low expression group (p<0.001). There was no significant difference in RI between HER2-positive and negative groups or between Ki67 high and low expression groups (p=0.904 and 0.216, respectively). For ER-negative and positive expression status, the maximum area under the curve (AUC) of SUVmax2 was 0.852, diagnostic threshold was 10.87, sensitivity was 79.6%, and specificity was 74.5%. For PR-negative and positive expression status, the AUC of SUVmax2 was 0.858, diagnostic threshold was 10.45, sensitivity was 83.1%, and specificity was 75.3%. For HER2-negative and positive expression status, the AUC of SUVmax1 was 0.714, diagnostic threshold was 9.28, sensitivity was 79.6%, and specificity was 60.9%. For Ki67 high- and low expression status, the AUC of SUVmax2 was 0.915 at maximum, diagnostic threshold was 10.21, sensitivity was 83.4%, and specificity was 93.9%. CONCLUSION: 18F-FDG PET/CT dual-phase imaging facilitates the prediction of the expression of molecular markers and subtypes of invasive ductal carcinoma of the breast and the development of more tailored treatment plans for patients with this disease.